Undergraduate Catalog
Source: http://coursecatalog.web.cmu.edu/schools-colleges/schoolofcomputerscience/ Parent: http://coursecatalog.web.cmu.edu/schools-colleges/schoolofcomputerscience/scsconcentrations/
School of Computer Science
Martial Hebert, Dean\ \ Thomas Cortina, Associate Dean for Undergraduate Programs\ \ Veronica Peet, Assistant Dean for Undergraduate Experience\ \ Location: GHC 4115\ www.cs.cmu.edu/undergraduate-programs\
Carnegie Mellon founded one of the first Computer Science departments in the world in 1965. As research and teaching in computing grew at a tremendous pace at Carnegie Mellon, the university formed the School of Computer Science (SCS) at the end of 1988. Carnegie Mellon was one of the first universities to elevate Computer Science into its own academic college at the same level as the Mellon College of Science and the College of Engineering. Today, SCS consists of seven departments and institutes, including the Computer Science Department that started it all, along with the Ray and Stephanie Lane Computational Biology Department, the Human-Computer Interaction Institute, the Language Technologies Institute, the Machine Learning Department, the Robotics Institute and the Software and Societal Systems Department. Together, these units make SCS a world leader in research and education. Over the last eight years, SCS has launched four new primary undergraduate majors in Computational Biology, Artificial Intelligence (the first of its kind in the United States), Human-Computer Interaction, and Robotics. These new majors, along with the highly-ranked Computer Science major, give students in SCS distinct paths in the field of computing with ample opportunities in industry and advanced research.
The School of Computer Science offers the following majors and minors:
- B.S. in Artificial Intelligence
- B.S. in Computational Biology
- B.S. in Computer Science
- B.S. in Human-Computer Interaction
- B.S. in Robotics
- Bachelor's in Computer Science and Art (joint with the College of Fine Arts)
- Additional major in Artificial Intelligence
- Additional major in Computational Biology
- Additional major in Computer Science
- Additional major in Human-Computer Interaction (Interdisciplinary)
- Additional major in Robotics
- Minor in Artificial Intelligence
- Minor in Computational Biology
- Minor in Computer Science
- Minor in Human-Computer Interaction
- Minor in Information Security, Privacy and Policy
- Minor in Language Technologies
- Minor in Machine Learning
- Minor in Neural Computation
- Minor in Robotics
- Minor in Software Engineering
Information for these majors and minors can be found through the navigation menu or through the links below:
- Artificial Intelligence (B.S. degree, additional major, minor)
- Computational Biology (B.S. degree, additional major, minor)
- Computer Science (B.S. degree, additional major, minor)
- Human-Computer Interaction (B.S. degree, additional interdisciplinary major, minor)
- Robotics (B.S. degree, additional major, minor)
- SCS additional majors and minors
Students who apply to, and are directly admitted into, the School of Computer Science can choose between five primary majors: Artificial Intelligence, Computational Biology, Computer Science, Human-Computer Interaction and Robotics. Students with artistic and computing interests may be given the option to pursue a major in Computer Science and Art. Suitably prepared students from other Carnegie Mellon colleges are eligible to apply for internal transfer to the School of Computer Science and will be considered for transfer if grades in specific requirements are sufficiently high and space is available. Consult the program websites for specific requirements for transfer requests. Computation-oriented programs are also available within the Mellon College of Science, the Dietrich College of Humanities and Social Sciences, the College of Engineering and the College of Fine Arts.
Policies & Procedures
Academic Standards and Actions
Grading Practices
Grades given to record academic performance in SCS are detailed under Grading Practices at Undergraduate Academic Regulations.
Dean's List WITH HIGH HONORS
SCS recognizes each semester those undergraduates who have earned outstanding academic records by naming them to the Dean's List with High Honors. The criterion for such recognition is a semester quality point average of at least 3.75 while completing a minimum of 36 factorable units and earning no incomplete grades.
Overload
An overload in SCS is defined as any schedule with more than 54 units in one semester. First-year SCS students with a QPA of 3.75 or higher may request an overload of up to 6 additional units in their second semester; first-year SCS students cannot overload in their first semester. SCS second-year and higher students may request an overload of up to 12 additional units. Overloads are not automatically granted; they must be approved by the student’s academic advisor and the SCS Associate Dean of Undergraduate Programs.
For an overload to be approved, the overall workload should be only slightly higher (5-6 hours per week) than a workload the student has had in a recent semester that demonstrated a successful outcome. Before requesting an overload, a student should consult with his or her academic advisor to determine whether an overload is truly needed. Overload requests will be granted by the academic advisor in circumstances when they are necessary to further the educational goals of the student while addressing the need to support the student's overall academic progress, participation in extracurricular activities and personal well-being.
Graduate Courses
First-year students are not permitted to register for graduate courses. SCS second-year and higher students might be able to register for a graduate course if the course is necessary for their educational goals and they achieve success in advanced courses in prior semesters. Registration for graduate course(s) is at the discretion and recommendation of a student’s academic advisor. Before attempting to register for a graduate course, a student should consult with their academic advisor.
Academic Actions
To maintain good academic standing, students from SCS must attain a quality point average (QPA) of at least 2.0 for each semester and a cumulative QPA of 2.0 and maintain adequate progress toward completing their degree requirements. For students with incomplete grade(s), default grade(s) will be used in the QPA calculation. For SCS, adequate progress toward completing degree requirements includes passing foundational courses of 15-112, 15-122, 15-151 (or 21-127 if applicable), with grades of C or higher, 21-120 and 21-122 with grades of D or higher by the end of the sophomore year. A review of a student’s academic record is completed after each Fall and Spring semester.
A student will no longer be in good standing if they meet any of the following criteria:
- Their semester QPA is below 2.00.
- Their cumulative QPA is below 2.00.
- They fail to complete a required foundational CS or math course after two or more attempts with a C or higher. These courses include: 15-112, 15-122, 15-151 (or 21-127), 21-120, 21-122.
- They do not complete their required foundational CS and math requirements by the end of the sophomore year.
Students who are not in good standing are first put on Academic Warning for the following semester. After that following semester, if the student is still not in good standing, the student will be put on Academic Suspension. However, a student on Academic Warning who is meeting the semester QPA requirement but is not yet meeting other requirements may be continued on Academic Warning. If the QPA is impacted by an incomplete grade, the action will be reviewed once the final grade is posted, and the action will be rescinded if appropriate.
A student is removed from Academic Warning and returned to good academic standing when both the semester and cumulative quality point averages are at least 2.0, and if adequate progress toward completing degree requirements is being made (i.e. completing foundational courses).
The minimum period of Academic Suspension is one academic year (two non-summer semesters). Academic suspension is meant to allow a student to take a pause from their academic studies to address the issues that are causing poor academic performance. At the end of that period a student may return to campus (on Final Academic Warning) by:
- completing a Return from Leave form from the HUB and submitting this form to their academic advisor, and
- submitting an additional written statement to their academic advisor and the SCS Associate Dean for Undergraduate Programs, minimum one page, that outlines what the student did while on leave to address the issues that led to the suspension and that would indicate future success on return, and
- (optional) submitting up to two letters of support from individuals supporting the student's return to the academic advisor and the SCS Associate Dean for Undergraduate Programs.
Upon review by the student's academic advisor and the Associate Dean for Undergraduate Programs, in consultation with the Office of Student Affairs and the Office of International Education as appropriate, the student may be approved to continue their studies.
SCS students who return from Academic Suspension will be placed on Final Academic Warning for up to 2 semesters to allow them to return to good academic standing or transfer to another major that is more suitable to their interests and abilities. Students who return to good standing after a return from suspension will be removed from Final Academic Warning. Students who return to good standing after suspension but then do not meet one or more conditions as outlined above will return to Final Academic Warning.
Students who fail to return to good academic standing after two semesters on Final Academic Warning will be dropped from the School of Computer Science. Students who have been dropped and are not admitted to another program at the university are required to absent themselves from the campus (including residence halls and Greek houses) within a maximum of two days after the action.
Students may appeal an academic warning, suspension or drop decision in writing within 10 business days of notification. Students should consult with their academic advisor before appealing, and should typically only appeal if they believe that an academic action was not correctly determined by the above criteria or if they have substantial additional information which was not available when the academic action was decided and which indicates a timely return to good academic standing. Instructions on the appeal process are given in the warning, suspension or drop letter that is sent to the student.
Leave of Absence and Return from Leave of Absence
SCS undergraduate students may elect to take a leave of absence for a variety of reasons, after consultation with their academic advisor. Students who wish to take a leave of absence must do so by the last day of classes before final exams begin and before final grades are posted (in case this is earlier). Students requesting a leave of absence must complete a form from the HUB and have this signed by their academic advisor and SCS Associate Dean for Undergraduate Programs. Students who take a leave of absence up to the last day to drop classes will have all of their classes dropped. Students who take a leave of absence after the last day to drop classes will be assigned a grade of W (withdrawal) for all of their classes.
Students returning from a leave of absence are required to submit a Return from Leave of Absence form to their academic advisor for approval by the student's academic advisor and the SCS Associate Dean for Undergraduate Programs. In addition, for students taking a leave for academic performance reasons, the student must also supply a letter that explains the reason for the leave, the actions that were performed during the leave to prepare the student for a successful return, and a description of the on-campus resources, if required, that would be used by the student in order to increase the likelihood of success. Students returning from a leave are also encouraged to provide up to two letters of support from people close to the student (e.g. family, friends, clergy, teachers, coaches, others as appropriate). Requests to return are reviewed by the student's academic advisor, the Associate Dean and the Student Affairs liaison to determine eligibility and any resources that need to be put into place to assist the student upon return. Contact the SCS Undergraduate Office (GHC 4115) for more information.
Internal Transfer within SCS
First year students admitted to SCS are considered undeclared during their first year. These students declare their SCS major in the middle of the second semester of their first year of study. SCS students who wish to transfer from one SCS major to another SCS major may do so by applying for transfer by mid-semester break during the semester the transfer is desired (or the end of the summer session for summer transfers). These students should consult with their academic advisor and the program director of the intended major for more information about specific course requirements and academic plans. Internal SCS transfers do not have any grade requirements. Transfers are approved based on demonstrated interest, ability, and available space in the intended major. Consult the website for the individual SCS major for more information about expected courses to take to demonstrate interest and ability. The transfer request form is available on the SCS website.
Transfer into SCS / Dual-Degree
Undergraduate students admitted to colleges at CMU other than SCS and wishing to transfer to SCS or pursue a dual degree in SCS should consult with the Director or Program Coordinator of the desired SCS major during their first year. See the individual program pages for the names of the current directors and program coordinators, along with their contact information.
- For the Artificial Intelligence primary major, students must complete 15-122, 15-150, 15-281, 10-315, one of 15-210, 15-213 or 15-251, and one of 36-225, 21-325, 36-218 or 15-259, with an expected overall QPA over these six courses of 3.6 or higher.and an overall QPA of at least 3.0, in order to be considered for transfer or dual degree.
- For the Computational Biology primary major, students must complete 21-127 (or equivalent), 15-122, 15-251, 15-351 (or 15-210*), 03-121 and either 02-251 or 02-250 with an expected overall QPA over these six courses of 3.6 or higher and an overall QPA of at least 3.0, in order to be considered for transfer or dual degree. (*Students who take 15-210 will need to also take 15-150; this course is not required for the B.S. in Computational Biology but can count as an elective.)
- For the Computer Science primary major, students must complete 21-127 (or equivalent), 15-122, 15-150, 15-210, 15-213, 15-251 with an expected overall QPA over these six courses of 3.6 or higher and an overall QPA of at least 3.0, in order to be considered for transfer or dual degree.
- For the Human-Computer Interaction primary major, students must complete 21-127 (or equivalent), 15-122, 15-150, 05-410, one of 15-210 or 15-213, and one of 05-380 or 05-431, with an expected overall QPA over these six courses of 3.6 or higher and an overall QPA of at least 3.0, in order to be considered for transfer or dual degree.
- For the Robotics primary major, students must complete 21-127 (or equivalent), 15-122, 15-213, 15-251, one of the following robotics courses: 16-211, 16-299, 16-311 (or Robot Building when launched), and one of 36-225, 21-325, 36-218 or 15-259, with an expected overall QPA over these 6 courses of 3.6 or higher and an overall QPA of at least 3.0, in order to be considered for transfer or dual degree.
Students may apply for transfer by the start of the mid-semester break in the semester when the final course(s) of the six required courses will be completed (or the end of the summer session for summer transfer requests). In the case of course(s) in progress, the mid-semester grades will be used in the QPA calculation. The decision to allow transfer or dual degree will be made by committee based on the student's academic performance (in the specified courses and in their courses overall if necessary), additional involvement in SCS and other computing-related activities, and availability of space in the student's class level. Students should consult the SCS Undergraduate Office for complete information concerning minimum requirements, instructions and deadlines.
External Transfer
A student currently enrolled at another university or college who wishes to transfer to SCS should first apply through the Office of Admission. If the Office of Admission believes the applicant meets admission guidelines, the student's record is sent to SCS for evaluation. Admission is based on seat availability, overall academic performance and course rigor from the student's current institution, ability to complete the rigorous SCS program on time, and the application material including recommendations and reflection essay(s). It is important to note that extremely few external transfers are admitted to the SCS program at Carnegie Mellon University due to space limitations. Additionally, any external transfer that is admitted into a major in SCS is not allowed to change majors within SCS for a minimum of one year and must meet all transfer requirements as defined above for students applying to transfer into SCS from another college/school at Carnegie Mellon (minus any courses that were granted as transfer courses).
Graduation Requirements
- A requirement for graduation is the completion of the program specified for a degree with a cumulative quality point average of 2.00 or higher for all courses taken at CMU.
- Students must be recommended for a degree by the faculty of SCS.
- A candidate for the bachelor's degree must complete at the University a minimum of four semesters of full-time study, or the equivalent of part-time study, comprising at least 180 units of course work.
- Students will be required to have met all financial obligations to the university before being awarded a degree.
General Education Requirements
All undergraduate degrees in the School of Computer Science include depth in their particular field of study but also breadth through the general education requirements. General education requirements are part of SCS degrees to give students an opportunity to learn more about the world from scientific and humanistic points of view. These additional skills are useful for graduates since computing is often embedded in domains that are not entirely within the bounds of computing. SCS students will need to use their computing skills to solve problems alongside scientists and engineers, artists, social and cognitive scientists, historians, linguists, economists and business experts, and SCS students will need to communicate effectively and understand the ethical implications of their work. The general education requirements help SCS students gain this broad perspective so they can work well in a wide variety of domains.
Science and Engineering
All candidates for a B.S. degree in the School of Computer Science must complete a minimum of 36 units offered by the Mellon College of Science and/or the College of Engineering (CIT). This includes at least four undergraduate courses in science and engineering, 9 units or more for each course, where at least one course must have a laboratory component and at least two courses must be from the same department.
For Computational Biology majors, consult the Computational Biology program page for specific science and engineering requirements. The required science and engineering courses for the Computational Biology major also satisfy the General Education requirement for SCS by default.
For all other SCS majors, courses for this requirement come from these CIT and MCS departments at Carnegie Mellon University:
- Biology [03-xxx]
- Biomedical Engineering [42-xxx]
- Chemical Engineering [06-xxx]
- Chemistry [09-xxx]
- Civil and Environmental Engineering [12-xxx]
- Electrical and Computer Engineering [18-xxx]
- Materials Science and Engineering [27-xxx]
- Mechanical Engineering [24-xxx]
- Physics [33-xxx]
Laboratory Requirement
Courses meeting the laboratory requirement for Science and Engineering include:
| 02-261 | Quantitative Cell and Molecular Biology Laboratory (can be paired with a course in Biology 03-xxx for two courses in one department) | 9 |
| 02-262 | Computation and Biology Integrated Research Lab (can be paired with a course in Biology 03-xxx for two courses in one department) | Var. |
| 03-124 | Modern Biology Laboratory | 9 |
| 03-206 | Biomedical Engineering Laboratory | 9 |
| 03-351 | Computation and Biology Integrated Research Lab | 9 |
| 09-101 | Introduction to Experimental Chemistry (This 3 unit lab together with 09-105 satisfies the lab requirement.) | 3 |
| 09-221 | Laboratory I: Introduction to Chemical Analysis | 12 |
| 27-100 | Engineering the Materials of the Future | 12 |
| 33-104 | Experimental Physics | 9 |
| 33-228 | Electronics I | 10 |
| 42-203 | Biomedical Engineering Laboratory | 9 |
| 85-310 | Research Methods in Cognitive Psychology | 9 |
| 85-370 | Cognitive Neuroscience Research Methods | 9 |
Deletions
Some courses from the Mellon College of Science or the College of Engineering may not count toward Science and Engineering due to the technical (computing and/or mathematical) nature of the courses or due to the level of presentation. Any MCS or CIT courses that are cross-listed with SCS courses cannot be used for this requirement. Courses from Engineering & Public Policy [19-xxx] cannot be used except those listed under Additions (see below). All courses in MCS and CIT that are affiliated with the IDeATe program cannot be used for this requirement.
Along with the constraints above, the following courses cannot be used for this requirement:
| 03-511 | Computational Molecular Biology and Genomics | 9 |
| 04-330 | Fundamentals of Software Development and Problem Solving | 12 |
| 06-262 | Mathematical Methods of Chemical Engineering | 12 |
| 09-103 | Atoms, Molecules and Chemical Change | 9 |
| 09-108 | The Illusion and Magic of Food | 6 |
| 09-109 | Kitchen Chemistry Sessions | 3 |
| 09-110 | The Design and Making of Skin and Hair Products | 3 |
| 09-114 | Basics of Food Science | 3 |
| 09-204 | Professional Communication Skills in Chemistry | 3 |
| 09-209 | Kitchen Chemistry Sessions | 3 |
| 09-231 | Mathematical Methods for Chemists | 9 |
| 12-215 | Introduction to Professional Writing in CEE | 9 |
| 12-271 | Computation and Data Science for Civil & Environmental Engineering | 9 |
| 18-200 | ECE Sophomore Seminar | 1 |
| 18-202 | Mathematical Foundations of Electrical Engineering | 12 |
| 18-213 | Introduction to Computer Systems | 12 |
| 18-330 | Introduction to Computer Security | 12 |
| 18-334 | Network Security | 12 |
| 18-441 | Computer Networks | 12 |
| 18-460 | Optimization | 12 |
| 18-461 | Introduction to Machine Learning for Engineers | 12 |
| 18-462 | Principles and Engineering Applications of AI | 12 |
| 18-465 | Advanced Probability & Statistics for Engineers | 12 |
| 18-540 | Rapid Prototyping of Computer Systems | 12 |
| 24-281 | Introduction to Scientific Computing | 2 |
| 24-311 | Numerical Methods | 10 |
| 27-410 | Computational Techniques in Engineering | 12 |
| 33-100 | Basic Experimental Physics | 6 |
| 33-115 | Physics for Future Presidents | 9 |
| 33-124 | Introduction to Astronomy | 9 |
| 33-231 | Physical Analysis | 10 |
| 33-232 | Mathematical Methods of Physics | 10 |
| 42-201 | Professional Issues in Biomedical Engineering | 3 |
| 49-300 | Integrated Product Conceptualization | 12 |
Additions
The following additional courses have been approved for Science and Engineering:
| 19-429 | Climate Change Science and Solutions | 9 |
| 19-440 | Combustion and Air Pollution Control | 9 |
| 85-170 | Foundations of Brain and Behavior | 9 |
New Courses
In the event that a new course is taught in MCS or CIT, consult with an advisor before taking the course. Your academic advisor will notify the SCS General Education Committee who will review the request and make adjustments to the academic audit if approved. Courses are reviewed based on the constraints given above.
Humanities and Arts
All candidates for a B.S. degree in the School of Computer Science must complete a minimum of 63 units offered by the Dietrich College of Humanities & Social Sciences (DC) and the College of Fine Arts (CFA). In addition, select courses from the Tepper School of Business (TSB) may also count toward this requirement, as indicated below. Students pursuing a Bachelor's in Computer Science and Art should consult the general education requirements for that program.
Courses for this requirement come from these schools, departments and institutes at Carnegie Mellon University:
- Architecture [48-xxx]
- Business Administration [70-xxx]
- Design [51-xxx]
- Drama [54-xxx]
- English [76-xxx]
- Fine Arts [60-xxx and 62-xxx]
- History [79-xxx]
- Languages, Cultures and Applied Linguistics [82-xxx]
- Music [57-xxx]
- Philosophy [80-xxx]
- Psychology [85-xxx]
- Social and Decision Sciences [88-xxx]
- Strategy and Technology [84-xxx]
A. First Year Writing Requirement (9 units)
| Complete one of the following writing options for 9 units: | ||
| 76-101 | Interpretation and Argument | 9 |
| 76-102 | Advanced First Year Writing: Special Topics (by invitation only) | 9 |
| or two of these three writing minis for 9 units total: | ||
| 76-106 | Writing about Literature, Art and Culture | 4.5 |
| 76-107 | Writing about Data | 4.5 |
| 76-108 | Writing about Public Problems | 4.5 |
B. Breadth Requirement (minimum 27 units: 9 units each)\ Complete three courses, one each from Category 1, Category 2, and Category 3. Artificial Intelligence majors replace Category 1 with Category 1A: Cognitive Studies which is a subset of Category 1. Human-Computer Interaction majors satisfy Category 1 with their required Psychology elective.
Category 1 (for all SCS majors except Artificial Intelligence): Cognition, Choice and Behavior - this requirement explores the process of thinking, decision making, and behavior in the context of the individual. | | || | | | | --- | --- | --- | | 70-311 | Organizational Behavior | 9 | | 70-318 | Managing Effective Work Teams | 9 | | 70-385 | Consumer Behavior | 9 | | 80-101 | Dangerous Ideas in Science and Society | 9 | | 80-130 | Introduction to Ethics | 9 | | 80-150 | Nature of Reason | 9 | | 80-180 | Introduction to Linguistics | 9 | | 80-221 | Philosophy of Social Science | 9 | | 80-252 | Kant | 9 | | 80-270 | Problems of Mind and Body: Meaning and Doing | 9 | | 80-271 | Mind and Body: The Objective and the Subjective | 9 | | 80-275 | Metaphysics | 9 | | 80-330 | Ethical Theory | 9 | | 85-100 | Introduction to Psychology | 9 | | 85-106 | Animal Minds | 9 | | 85-107 | The Psychology of Video Games | 9 | | 85-110 | Cognitive Psychology | 9 | | 85-130 | Developmental Psychology | 9 | | 85-150 | Social Psychology | 9 | | 85-190 | Psychopathology | 9 | | 85-213 | Human Information Processing and Artificial Intelligence | 9 | | 85-251 | Personality | 9 | | 85-261 | Psychopathology | 9 | | 85-413 | Perception | 9 | | 85-421 | Language and Thought | 9 | | 85-472 | Cognitive Neuropsychology | 9 | | 88-120 | Reason, Passion and Cognition | 9 | | 88-230 | Human Intelligence and Human Stupidity | 9 | | 88-231 | Thinking in Person vs. Thinking Online | 9 |
Category 1A (for Artificial Intelligence majors): Cognitive Studies - this requirement explores how the brain and the mind work. | | || | | | | --- | --- | --- | | 85-110 | Cognitive Psychology | 9 | | 85-213 | Human Information Processing and Artificial Intelligence | 9 | | 85-408 | Visual Cognition | 9 | | 85-413 | Perception | 9 | | 85-421 | Language and Thought | 9 |
Category 2 (all SCS majors): Economic, Political and Social Institutions - this requirement explores the processes by which institutions organize individual preferences and actions into collective outcomes. | | || | | | | --- | --- | --- | | 19-101 | Introduction to Engineering and Public Policy | 12 | | 36-303 | Sampling, Survey and Society | 9 | | 66-221 | Topics of Law: Introduction to Intellectual Property Law | 9 | | 70-332 | Business, Society and Ethics | 9 | | 73-102 | Principles of Microeconomics | 9 | | 73-103 | Principles of Macroeconomics | 9 | | 73-104 | Principles of Microeconomics Accelerated | 9 | | 73-369 | Islamic Economics | 9 | | 76-425 | Rhetoric, Science, and the Public Sphere | 9 | | 79-101 | Making History: How to Think About the Past (and Present) | 9 | | 79-155 | Introduction to African American Studies | 9 | | 79-189 | Democracy and History: Thinking Beyond the Self | 9 | | 79-212 | Jim Crow America | 9 | | 79-237 | Comparative Slavery | 9 | | 79-246 | War, Genocide, and Gender in Modern Europe | 9 | | 79-253 | Imperialism and Decolonization in South Asia | 9 | | 79-255 | Modern Ireland: Politics and Culture from the Famine (1847) to Today | 9 | | 79-275 | Introduction to Global Studies | 9 | | 79-276 | Beyond the Border | 9 | | 79-300 | Controversial Topics in the History of American Public Policy | 9 | | 79-304 | History of Eugenics and Scientific Racism | 9 | | 79-315 | The Politics of Water in Global Perspective | 9 | | 79-320 | Women, Politics, and Protest | 9 | | 79-321 | Documenting Human Rights | 9 | | 79-330 | Medicine and Society: Health, Healers, and Hospitals | 9 | | 79-331 | Body Politics: Women and Health in America | 9 | | 79-370 | Technology in the United States | 9 | | 79-380 | Hostile Environments: The Politics of Pollution in Global Perspective | 9 | | 79-383 | The History of Capitalism | 9 | | 79-391 | Nations and Nationalisms in South Asia | 9 | | 79-392 | Europe and the Islamic World | 9 | | 80-135 | Introduction to Political Philosophy | 9 | | 80-136 | Social Structure, Public Policy & Ethics | 9 | | 80-244 | Environmental Ethics | 9 | | 80-245 | Medical Ethics | 9 | | 80-324 | Philosophy of Economics | 9 | | 80-334 | Social and Political Philosophy | 9 | | 80-335 | Social and Political Philosophy | 9 | | 80-348 | Health, Human Rights, and International Development | 9 | | 84-104 | Decision Processes in American Political Institutions | 9 | | 84-110 | The Economics of Politics and Technology | 9 | | 84-275 | Comparative Politics | 9 | | 84-306 | Latin American Politics | 9 | | 84-309 | American Political Divides and Great Debates | 9 | | 84-322 | Nonviolent Conflict and Revolution | 9 | | 84-324 | The Future of Democracy | 9 | | 84-325 | Contemporary American Foreign Policy | 9 | | 84-352 | Representation and Voting Rights | 9 | | 84-362 | Diplomacy and Statecraft | 9 | | 84-365 | The Politics of Fake News and Misinformation | 9 | | 84-380 | US Grand Strategy | 9 | | 84-386 | The Privatization of Force | 9 | | 84-387 | Remote Systems and the Cyber Domain in Conflict | 9 | | 84-389 | Terrorism and Insurgency | 9 | | 84-390 | Social Media, Technology, and Conflict | 9 | | 84-393 | The US Congress: Legislative Progress or Paralysis? | 9 | | 84-402 | Judicial Politics and Behavior | 9 | | 84-405 | The Future of Warfare | 9 | | 88-234 | Negotiation: International Focus | 9 | | 88-255 | Strategic Decision Making | 9 | | 88-281 | Topics in Law: 1st Amendment | 9 | | 88-284 | Topics of Law: The Bill of Rights | 9 |
Category 3 (all SCS majors): Cultural Analysis - this requirement seeks to recognize cultures that have shaped and continue to shape the human experience; courses in this category are usually either broad in place, time, or cultural diversity. | | || | | | | --- | --- | --- | | 48-240 | History of World Architecture, I | 9 | | 48-241 | Modern Architecture: History & Theory | 9 | | 57-173 | Survey of Western Music History | 9 | | 60-105 | Cultural History of the Visual Arts | 9 | | 60-106 | Cultural History of the Visual Arts - the Modern Period | 9 | | 62-371 | Photography, The First 100 Years, 1839-1939 | 9 | | 70-342 | Managing Across Cultures | 9 | | 70-348 | Cross-Cultural Business Communications | 9 | | 76-221 | Books You Should Have Read By Now | 9 | | 76-230 | Literature & Culture in the 19th Century | 9 | | 76-239 | Introduction to Film Studies | 9 | | 76-241 | Introduction to Gender Studies | 9 | | 76-339 | Topics in Film and Media | 9 | | 76-357 | (Im)Migration, Multilingualism, and Identities | 9 | | 76-386 | Language & Culture | 9 | | 79-104 | Global Histories | 9 | | 79-145 | Genocide and Weapons of Mass Destruction | 9 | | 79-201 | Introduction to Anthropology | 9 | | 79-202 | Flesh and Spirit: Early Modern Europe, 1400-1750 | 9 | | 79-211 | Modern Southeast Asia: Colonialism, Capitalism, and Cultural Exchange | 9 | | 79-223 | Mexico: From the Aztec Empire to the Drug War | 9 | | 79-226 | African History: Earliest Times to 1780 | 9 | | 79-229 | The Origins of the Palestinian-Israeli Conflict, 1880-1948 | 9 | | 79-230 | The Arab-Israeli Conflict and Peace Process Through 1948 to Present | 9 | | 79-234 | Technology and Society | 9 | | 79-240 | Development of American Culture | 9 | | 79-242 | African American History: Reconstruction to the Present | 9 | | 79-245 | Capitalism and Individualism in American Culture | 9 | | 79-248 | U.S. Constitution & the Presidency | 9 | | 79-261 | The Last Emperors: Chinese History and Society, 1600-1900 | 9 | | 79-262 | Modern China: From the Birth of Mao ... to Now | 9 | | 79-265 | Russian History: Game of Thrones | 9 | | 79-281 | Introduction to Religion | 9 | | 79-288 | Bananas, Baseball, and Borders: Latin America and the United States | 9 | | 79-293 | Inward Odyssey | 9 | | 79-316 | Photography, the First 100 Years, 1839-1939 | 9 | | 79-329 | LGBTQ+ History | 9 | | 79-345 | Roots of Rock & Roll | 9 | | 79-350 | Early Christianity | 9 | | 79-378 | Gender in South Asia | 9 | | 79-393 | Institutions of the Roman Church | 9 | | 79-395 | The Arts in Pittsburgh | 9 | | 79-396 | Music, Art, and Society in 19th and 20th Century Europe and the U.S. | 9 | | 79-465 | The Arts in Qatar | 9 | | 80-100 | Introduction to Philosophy | 9 | | 80-250 | Ancient Philosophy | 9 | | 80-251 | Modern Philosophy | 9 | | 80-253 | Continental Philosophy | 9 | | 80-254 | The History of Analytic Philosophy and Its Influence | 9 | | 80-255 | Pragmatism: Clear Ideas for a Better Life | 9 | | 80-261 | Experience, Reason, and Truth | 9 | | 80-276 | Philosophy of Religion | 9 | | 82-119 | Arabic Calligraphy Culture & Skills | 9 | | 82-137 | Chinese Calligraphy: Culture and Skills | 9 | | 82-139 | Chinese Learning Through Arts, Cultural Practices and Community Engagement | 9 | | 82-267 | Beyond the Mafia and Michelangelo | 9 | | 82-273 | Introduction to Japanese Language and Culture | 9 | | 82-278 | Japanese Film and Literature: The Art of Storytelling | 9 | | 82-279 | Anime - Visual Interplay between Japan and the World | 9 | | 82-280 | Billingual & Bicultural Experiences in the US | 9 | | 82-282 | Interpreting Global Texts & Cultures | 9 | | 82-283 | Language Diversity & Cultural Identity | 9 | | 82-286 | Of Minorities and Migrants: Exploring Germany from the Margins Germany Today | 9 | | 82-293 | Russian Cinema: From the Bolshevik Revolution to Putin's Russia | 9 | | 82-294 | 19th Century Russian Masterpieces | 9 | | 82-303 | French & Francophone Cultures | 9 | | 82-304 | French & Francophone Sociolinguistics | 9 | | 82-313 | Topics in Modern Arabic Language, Literature & Culture | 9 | | 82-314 | Literature of the Arabic-speaking World | 9 | | 82-323 | Germany, Austria and Switzerland in the 20th Century | 9 | | 82-327 | The Emergence of the German Speaking World | 9 | | 82-333 | Chinese Language and Culture | 9 | | 82-342 | Cultures of Spain | 9 | | 82-343 | Cultures of Latin America | 9 | | 82-344 | U.S. Latine Cultures | 9 | | 82-345 | Using Spanish in Social Contexts | 9 | | 82-436 | Introduction to Classical Chinese | 9 |
C. Humanities and Arts Electives (minimum 27 units)\ Complete 3 non-technical undergraduate courses of at least 9 units each from any of the departments in the Dietrich College of Humanities & Social Sciences or the College of Fine Arts. Some of the courses taught in these units are considered technical courses and may not be used to satisfy this requirement (see Deletions below). Additionally, a select set of courses from the Tepper School of Business and from Environmental and Public Policy (CIT) can also count for this requirement (see Additions below). Students may combine 2 mini humanities/arts courses totaling at least 9 units together to form a single course of 9 units or more with advisor approval in consultation with the SCS Associate Dean for Undergraduate Programs. Students are encouraged, but not required, to take courses from different departments to gain additional breadth and to create new opportunities for engagement with the university community.
Deletions
Some courses from the Dietrich College or the College of Fine Arts may not count toward the unconstrained electives in Humanities and Arts in SCS due to the technical (computing and/or mathematical) nature of the courses. In general, any humanities or arts courses that have computer science or mathematics prerequisites do not count toward this requirement.
The following courses do NOT count toward the unconstrained Humanities and Arts electives:
| 51-257 | Introduction to Computing for Creative Practices | 10 |
| 51-327 | Design Center: Introduction to Web Design | 9 |
| 51-328 | Design for Digital Systems | 9 |
| 76-388 | Coding for Humanists | 9 |
| 76-481 | Introduction to Multimedia Design | 12 |
| 76-487 | Information Architecture & Content Strategy | 9 |
| 80-210 | Logic and Proofs | 9 |
| 80-211 | Logic and Mathematical Inquiry | 9 |
| 80-212 | Arguments and Logical Analysis | 9 |
| 80-305 | Game Theory | 9 |
| 80-306 | Decision Theory | 9 |
| 80-310 | Formal Logic | 9 |
| 80-311 | Undecidability and Incompleteness | 9 |
| 80-315 | Logics for Knowledge and Belief | 9 |
| 80-316 | Logic and AI | 9 |
| 80-325 | Foundations of Causation and Machine Learning | 9 |
| 80-411 | Proof Theory | 9 |
| 80-413 | Category Theory | 9 |
| 80-419 | Interactive Theorem Proving | 9 |
| 80-514 | Categorical Logic | 9 |
| 80-521 | Seminar on Formal Epistemology: Belief and Evidence | Var. |
| 85-170 | Foundations of Brain and Behavior | 9 |
| 85-310 | Research Methods in Cognitive Psychology | 9 |
| 85-314 | Cognitive Neuroscience Research Methods | 9 |
| 85-412 | Cognitive Modeling | 9 |
| 85-414 | Cognition in the Age of AI | 9 |
| 85-419 | Introduction to Parallel Distributed Processing | 9 |
| 85-420 | Biologically Intelligent Exploration | 9 |
| 85-426 | Learning in Humans and Machines | 9 |
| 85-472 | Cognitive Neuropsychology | 9 |
| 88-251 | Empirical Research Methods | 9 |
| 88-372 | Social and Emotional Brain | 9 |
Additions
The following courses from the Dietrich College, the College of Fine Arts, and other Colleges/Schools can count toward the unconstrained Humanities and Arts electives:
| 07-135 | Grand Challenge First-Year Seminar: Designing Better Human-AI Futures | 9 |
| 07-402 | SCS Leadership Development Seminar | 9 |
| 11-423 | ConLanging: Lrng Ling & Lang Tech via Constru Artif. Lang | 12 |
| 16-161 | Artificial Intelligence and Humanity | 12 |
| 16-397 | Art, Conflict and Technology | 12 |
| 17-333 | Privacy Policy, Law, and Technology | 9 |
| 17-416 | AI Governance: Identifying & Mitigating Risks in Design & Dev of AI Solutions | Var. |
| 17-562 | Law of Computer Technology | 9 |
| 19-101 | Introduction to Engineering and Public Policy | 12 |
| 19-351 | Applied Methods for Technology-Policy Analysis | 9 |
| 19-403 | Policies of Wireless Systems | 12 |
| 19-411 | Science and Innovation Leadership for the 21st Century: Firms, Nations, and Tech | 9 |
| 21-150 | Mathematics and the Arts | 9 |
| 32-201 | Leadership & Management | 9 |
| 32-402 | Leadership and Ethics | 9 |
| 36-303 | Sampling, Survey and Society | 9 |
| 70-100 | Global Business | 9 |
| 70-101 | Business Strategy Fundamentals | 9 |
| 70-311 | Organizational Behavior | 9 |
| 70-318 | Managing Effective Work Teams | 9 |
| 70-321 | Negotiation and Conflict Resolution | 9 |
| 70-332 | Business, Society and Ethics | 9 |
| 70-340 | Business Communications | 9 |
| 70-341 | Team Dynamics and Leadership | 9 |
| 70-342 | Managing Across Cultures | 9 |
| 70-345 | Business Presentations | 9 |
| 70-348 | Cross-Cultural Business Communications | 9 |
| 70-350 | Acting for Business | 9 |
| 70-352 | Business Acting | 3 |
| 70-364 | Business Law | 6 |
| 70-365 | International Trade and International Law | 9 |
| 70-381 | Marketing I | 9 |
| 70-415 | Introduction to Entrepreneurship | 9 |
| 70-430 | International Management | 9 |
| 70-443 | Digital Marketing and Social Media Strategy | 9 |
| 73-102 | Principles of Microeconomics | 9 |
| 73-103 | Principles of Macroeconomics | 9 |
| 73-104 | Principles of Microeconomics Accelerated | 9 |
| 73-369 | Islamic Economics | 9 |
New Courses
In the event that a new course is taught in DC, CFA or TSB, consult with an advisor before taking the course. Your academic advisor will notify the SCS General Education Committee who will review the request and make adjustments to the academic audit if approved. Courses are reviewed based on the constraints given above.
Honors Research Thesis
Students considering going on to graduate school in Computer Science or related disciplines should take a wide variety of Computer Science and Mathematics courses, as well as consider getting involved in independent research as early as possible. This would be no later than the junior year and can begin even earlier. Students interested in graduate school in computer science or its related areas are strongly encouraged to participate in the SCS Honors Undergraduate Research Thesis program. Additionally, graduate CS courses can be taken with permission of the instructor and in consultation with an academic advisor.
The goal of the SCS Honors Undergraduate Research Thesis Program is to introduce students to the breadth of tasks involved in independent research, including surveys of prior work, problem formulation, experimentation, analysis, technical writing and public speaking. In particular, students write a short paper summarizing prior results and current progress in their desired area of research, present a public poster session in December of their senior year describing their current progress, present their final results with a poster and an oral presentation in the year-end university-wide Undergraduate Research Symposium (Meeting of the Minds) and submit a written thesis at the end of their senior year. Students work closely with faculty research advisors to plan and carry out their research. The 07-599 SCS Honors Undergraduate Research Thesis typically starts in the fall semester of the senior year, and spans the entire senior year. Students receive a total of 36 units of academic credit for the thesis work, 18 units per semester. Students should prepare their research prospectus (i.e. proposal of work) during the spring semester of their junior year, and students in this program are advised to plan their schedules carefully to ensure there is ample time to perform the required research for the thesis during the senior year.
Students interested in research are urged to consult with their undergraduate advisor and the SCS Associate Dean for Undergraduate Programs no later than the end of their sophomore year in order to plan their workload effectively. Although there is no specific QPA requirement to participate, students are expected to have at least a 3.5 QPA in the core SCS topics relevant to their proposed research to be successful in their work. For those students with no background in research, they may consider using 07-300 Research and Innovation in Computer Science (9 units) as an introduction to the research process in their junior year since this course will introduce students to various research projects going on in the School of Computer Science and important skills that are needed to be an effective researcher. This course leads to a subsequent research practicum, 07-400 Research Practicum in Computer Science (12 units), that allows students to complete a small-scale research study or experiment and present a research poster. Students who use this practicum to start their senior thesis can use the 12 units toward the required 36 units. Students should consult with their academic advisor concerning how the units earned toward the senior thesis can be used toward elective requirements for their major.
Interested juniors should submit a project prospectus of 3-4 pages by the end of their junior year, although submissions over the summer prior to the senior year will also be considered for review. A prospectus must include:
- The name of the research advisor (an SCS faculty member)
- A short abstract (two paragraphs, max)
- A description of the problem to be worked on and its significance
- A tactical description of the proposed research plan, including:
- a description of the background reading to be carried out,
- a description of the research contribution,
- a description of the expected results of the research, and
- a reasonably detailed timeline for the thesis work
- A bibliography of related work (all references belong here)
- The signature of the research advisor, signifying endorsement of the project and willingness to supervise and evaluate it (or an email confirmation from the research advisor)
Students who need help finding potential advisors should get in touch with their academic advisor or the Associate Dean for Undergraduate Programs. Applications to the program are due by the start of the senior year, although submission of applications in the junior year is encouraged.
Students completing an outstanding senior thesis based on the judgement of the SCS Undergraduate Review Committee will earn SCS College Honors and can compete for various SCS research awards given out during commencement.
Faculty
UMUT ACAR, Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2012–
ANIL ADA, Associate Teaching Professor, Carnegie Mellon University – Ph.D., McGill University; Carnegie Mellon, 2014–
HENNY ADMONI, Associate Professor, Robotics Institute – Ph.D., Yale University; Carnegie Mellon, 2017–
YUVRAJ AGARWAL, Professor, Institute for Software Research – Ph.D., University of California, San Diego; Carnegie Mellon, 2013–
HAMMAD AHMAD, Assistant Teaching Professor, Software and Societal Systems Department – Ph.D., University of Michigan; Carnegie Mellon, 2024–
JONATHAN ALDRICH, Professor, Institute for Software Research – Ph.D., University Of Washington; Carnegie Mellon, 2003–
VINCENT ALEVEN, Professor, Human-Computer Interaction Institute – Ph.D., University Of Pittsburgh; Carnegie Mellon, 2000–
DANIEL ANDERSON, Assistant Teaching Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2023–
DAVID ANDERSEN, Professor, Computer Science Department – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 2005–
JOHN ANDERSON, R.K. Mellon University Professor – Ph.D., Stanford University; Carnegie Mellon, 1978–
DIMITRIOS APOSTOLOPOULOS, Principal Systems Scientist, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1989–
SWARNALATHA ASHOK, Associate Teaching Professor, Institute for Software Research – MSc(Tech), Birla Institute of Technology and Science; Carnegie Mellon, 2022–
CHRISTOPHER ATKESON, Professor, Robotics Institute – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 2000–
JAMES BAGNELL, Associate Professor, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2004–
ANDREA BAJCSY, Assistant Professor, Robotics Institute – Ph.D., University of California, Berkeley; Carnegie Mellon, 2023–
MARIA FLORINA BALCAN, Professor, Machine Learning Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2014–
STEPHANIE BALZER, Assistant Professor, Computer Science Department – Ph.D., ETH Zurich; Carnegie Mellon, 2016–
ZIV BAR-JOSEPH, Professor, Computational Biology Department – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 2003–
LUJO BAUER, Professor, Institute for Software Research – Ph.D., Princeton University; Carnegie Mellon, 2015–
NATHAN BECKMANN, Associate Professor, Computer Science Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2017–
TAYLOR BERG-KIRKPATRICK, Assistant Professor, Language Technologies Institute – Ph.D., University of California at Berkeley; Carnegie Mellon, 2016–
JEFFREY BIGHAM, Associate Professor, Human-Computer Interaction Institute – Ph.D., University of Washington; Carnegie Mellon, 2013–
YONATAN BISK, Assistant Professor, Language Technologies Institute – Ph.D, University of Illinois, Urbana- Champaign; Carnegie Mellon, 2020–
GUY BLELLOCH, Professor, Computer Science Department – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 1988–
MANUEL BLUM, University Professor Emeritus, Computer Science Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2001–
CHRISTOPHER BOGART, Senior Systems Scientist, Institute for Sofrware research – Ph.D., Oregon State University; Carnegie Mellon, 2017–
RICHARD BORDER, Assistant Professor, Computational Biology Department – Ph.D., University of California, Los Angeles; Carnegie Mellon, 2025–
DAVID BOURNE, Principal Systems Scientist, Robotics Institute – M.S., University Of Pennsylvania; Carnegie Mellon, 1980–
DANIEL BOYARSKI, Professor – M.F.A., Indiana University; Carnegie Mellon, 1982–
TRAVIS BREAUX, Associate Professor, Institute for Software Research – Ph.D., North Carolina State University; Carnegie Mellon, 2010–
STEPHEN BROOKES, Professor Emeritus, Computer Science Department – Ph.D., Oxford University; Carnegie Mellon, 1981–
RALF BROWN, Principal Systems Scientist, Language Technologies Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1993–
FRASER BROWN, Assistant Professor, Institute for Software Research – Ph.D., Stanford University; Carnegie Mellon, 2022–
RANDAL BRYANT, University Professor Emeritus, Computer Science Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 1984–
CARLOS BUSSO, Professor, Language Technologies Institute – Ph.D., University of Southern California; Carnegie Mellon, 2025–
JOSEPH CALANDRINO, Assistant Professor, Software and Societal Systems Department – Ph.D., Princeton University; Carnegie Mellon, 2025–
JAMES CALLAN, Professor and Director, Language Technologies Institute – Ph.D., University Of Massachusetts; Carnegie Mellon, 1999–
JAVIER CAMARA-MORENO, Systems Scientist, Institute for Software Research – Ph.D., University of Malaga; Carnegie Mellon, 2015–
OANA CARJA, Assistant Professor, Computational Biology – Ph.D., Stanford University; Carnegie Mellon, 2019–
KATHLEEN CARLEY, Professor, Institute for Software Research – Ph.D., Harvard University; Carnegie Mellon, 1984–
JACOBO CARRASQUEL, Associate Teaching Professor Emeritus, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1983–
PATRICK CARRINGTON, Associate Professor, Human Computer Interaction Institute – Ph.D., University of Maryland; Carnegie Mellon, 2019–
PAOLO CARVALHO, Assisant Professor, Human-Computer Interaction Institute – Ph.D., Indiana University; Carnegie Mellon, 2024–
JUSTINE CASSELL, Professor, Language Technologies Institute – Ph.D., University of Chicago; Carnegie Mellon, 2010–
ILIANO CERVESATO, Teaching Professor, Computer Science Department – Ph.D., University of Torino; Carnegie Mellon, 2016–
HENRY CHAI, Assistant Teaching Professor, Machine Learning Department – Ph.D., Washington University, Saint Louis; Carnegie Mellon, 2022–
JUSTIN CHAN, Assistant Professor, Software and Societal Systems Department – Ph.D., University of Washington; Carnegie Mellon, 2024–
TIANQI CHEN, Assistant Professor, Machine Learning Department / Computer Science Department – Ph.D, University of Washington; Carnegie Mellon, 2020–
HOWARD CHOSET, Professor, Robotics Institute – Ph.D., California Institute Of Technology; Carnegie Mellon, 1996–
NICOLAS CHRISTIN, Professor, Institute for Software Research – Ph.D., University of Virginia; Carnegie Mellon, 2017–
WILLIAM COHEN, Professor, Machine Learning Department – Ph.D., Rutgers University; Carnegie Mellon, 2003–
PHILLIP COMPEAU, Teaching Professor, Computational Biology Department – Ph.D., University of California, San Diego; Carnegie Mellon, 2015–
VINCENT CONITZER, Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2022–
ALBERT CORBETT, Associate Research Professor Emeritus, Human-Computer Interaction Institute – Ph.D., University Of Oregon; Carnegie Mellon, 1983–
THOMAS CORTINA, Associate Dean for Undergraduate Programs and Teaching Professor, Computer Science Department – Ph.D., Polytechnic University (Brooklyn); Carnegie Mellon, 2004–
KEENAN CRANE, Associate Professor, Robotics Institute – Ph.D., California Institute of Technology; Carnegie Mellon, 2015–
LORRIE CRANOR, Professor, Institute for Software Research – Ph.D., Washington University; Carnegie Mellon, 2003–
KARL CRARY, Associate Professor, Computer Science Department – Ph.D., Cornell University; Carnegie Mellon, 1998–
CHRISTIAN CUBA-SANAMIEGO, Assistant Professor, Computational Biology Department – Ph.D., University of California, Riverside; Carnegie Mellon, 2024–
LAURA DABBISH, Professor, Human Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2007–
ROGER DANNENBERG, Professor Emeritus, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1982–
SAUVIK DAS, Associate Professor, Human Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2022–
PATHAK DEEPAK, Assistant Professor, Robotics Institute – Ph.D., University of California, Berkeley; Carnegie Mellon, 2020–
TIM DETTMERS, Assistant Professor, Machine Learning Department – Ph.D., University of Washington; Carnegie Mellon, 2025–
FERNANDO DE LA TORRE FRADE, Research Professor, Robotics Institute – Ph.D., La Salle School of Engineering; Carnegie Mellon, 2002–
DAN DEBLASIO, Assistant Teaching Professor, Computational Biology Department – Ph.D., University of Arizona; Carnegie Mellon, 2023–
MONA DIAB, Professor, Language Technologies Institute – Ph.D., George Washington University; Carnegie Mellon, 2023–
FERNANDO DIAZ, Associate Professor, Language Technologies Institute – Ph.D., University of Massachusetts Amherst; Carnegie Mellon, 2023–
JOHN DOLAN, Principal Systems Scientist, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1991–
CHRIS DONAHUE, Assistant Professor, Language Technologies Institute – Ph.D., University of California San Diego; Carnegie Mellon, 2023–
ARTUR DUBRAWSKI, Research Professor, Robotics Institute – Ph.D., Institute of Fundamental Technological Research; Carnegie Mellon, 2003–
DAVID ECKHARDT, Teaching Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2003–
WILLIAM EDDY, Professor – Ph.D., Yale University; Carnegie Mellon, 1976–
JEFFREY EPPINGER, Professor Of The Practice, Institute for Software Research – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2001–
MICHAEL ERDMANN, Professor, Robotics Institute – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 1989–
ZACKORY ERICKSON, Assistant Professor, Robotics Institute – Ph.D, Georgia Institute of Technology; Carnegie Mellon, 2021–
MOTAHHARE ESLAMI, Assistant Professor, Human Computer Interaction Institute – Ph.D, University of Illinois, Urbana- Champaign; Carnegie Mellon, 2020–
SCOTT FAHLMAN, Professor Emeritus, Language Technologies Institute – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 1978–
CHRISTOS FALOUTSOS, Professor, Computer Science Department – Ph.D., University Of Toronto; Carnegie Mellon, 1997–
FEI FANG, Associate Professor, Institute for Software Research – Ph.D., University of Southern California; Carnegie Mellon, 2017–
JODI FORLIZZI, Professor, Director; Human-Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2000–
SARAH FOX, Assistant Professor, Human Computer Interaction Institute – Ph.D, University of Washington; Carnegie Mellon, 2020–
KATE FRAGKIADAKI, Associate Professor, Machine Learning Department – Ph.D., University of Pennsylvania ; Carnegie Mellon, 2016–
MATTHEW FREDRIKSON, Associate Professor, Computer Science Department – Ph.D., University of Wisconsin; Carnegie Mellon, 2015–
DANIEL FRIED, Assistant Professor, Language Technologies Institute – Ph.D., University of California at Berkeley; Carnegie Mellon, 2022–
JOHN GALEOTTI, Senior Systems Scientist, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2014–
DAVID GARLAN, Professor, Institute for Software Research – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1990–
CHARLES GARROD, Associate Teaching Professor, Institute for Software Research – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2012–
HARTMUT GEYER, Professor, Robotics Institute – Ph.D., Friedrich-Schiller University; Carnegie Mellon, 2010–
PHIL GIBBONS, Professor, Computer Science Department – Ph.D., University of California at Berkeley; Carnegie Mellon, 2015–
IOANNIS GKIOULEKAS, Associate Professor, Robotics Institute – Ph.D., Harvard; Carnegie Mellon, 2017–
CLARK GLYMOUR, University Professor – Ph.D., Indiana University; Carnegie Mellon, 1985–
MAYANK GOEL, Associate Professor, Institute for Software Research – Ph.D., University of Washington; Carnegie Mellon, 2016–
SETH GOLDSTEIN, Associate Professor, Computer Science Department – Ph.D., University Of California; Carnegie Mellon, 1997–
GEOFFREY GORDON, Professor, Machine Learning Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2001–
MATTHEW GORMLEY, Associate Teaching Professor, Machine Learning Department – Ph.D., John Hopkins University; Carnegie Mellon, 2015–
ALBERT GU, Assistant Professor, Machine Learning Department – Ph.D., Stanford University; Carnegie Mellon, 2023–
MARCAIS GUILLAUME, Senior Systems Scientist, Computational Biology Department – Ph.D., University of Maryland; Carnegie Mellon, 2020–
ABHINAV GUPTA, Professor, Robotics Institute – Ph.D., University of Maryland; Carnegie Mellon, 2011–
HANA HABIB, Assistant Teaching Professor, Software and Societal Systems Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2024–
ZAKIA HAMMAL, Assistant Research Professor, Robotics Institute – Ph.D, University of Grenoble, France; Carnegie Mellon, 2021–
JESSICA HAMMER, Associate Professor, Human-Computer Interaction Institute – Ph.D., Columbia University; Carnegie Mellon, 2014–
MOR HARCHOL-BALTER, Professor, Computer Science Department – Ph.D., University Of California at Berkeley; Carnegie Mellon, 1999–
ROBERT HARPER, Professor, Computer Science Department – Ph.D., Cornell University; Carnegie Mellon, 1988–
ERIK HARPSTEAD, Senior Systems Scientist, Human-Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2017–
CHRISTINA HARRINGTON, Assistant Professor, Human Computer Interaction Institute – Ph.D, Georgia Institute of Technology; Carnegie Mellon, 2021–
CHRISTOPHER HARRISON, Associate Professor, Human-Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2014–
ALEXANDER HAUPTMANN, Research Professor, Language Technologies Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1994–
MARTIAL HEBERT, Dean of the School of Computer Science and Professor, Robotics Institute – Ph.D., Paris-Xl; Carnegie Mellon, 1984–
HODA HEIDARI, Assistant Professor, Machine Learning Department – Ph.D., University of Pittsburgh; Carnegie Mellon, 2020–
DAVID HELD, Associate Professor, Robotics Institute – Ph.D., Stanford University; Carnegie Mellon, 2017–
VINCENT HELLENDOORN, Assistant Professor, Software and Societal Systems Department – Ph.D., University of California Davis; Carnegie Mellon, 2020–
AUSTIN HENLEY, Associate Teaching Professor, Software and Societal Systems Department – Ph.D., The University of Memphis; Carnegie Mellon, 2024–
JAMES HERBSLEB, Director, Professor, Institute for Software Research – Ph.D., University Of Nebraska; Carnegie Mellon, 2002–
MARIJN HEULE, Associate Professor, Computer Science Department – Ph.D., Delft University of Technology (Netherlands); Carnegie Mellon, 2019–
LEE HILLMAN, Executive Director of MHCI, Human-Computer Interaction Institute – M.S., Carnegie Mellon University; Carnegie Mellon, 2017–
MICHAEL HILTON, Teaching Professor, Institute for Software Research – Ph.D., Oregon State University; Carnegie Mellon, 2017–
JESSICA HODGINS, Professor, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2001–
JAN HOFFMANN, Associate Professor, Computer Science Department – Ph.D., Ludwig-Maximilians-Universität and TU Munich; Carnegie Mellon, 2015–
RALPH HOLLIS, Research Professor Emeritus, Robotics Institute – Ph.D, University of Colorado; Carnegie Mellon, 1993–
JASON HONG, Associate Professor, Human-Computer Interaction Institute – Ph.D., University Of California at Berkeley; Carnegie Mellon, 2004–
DANIEL HUBER, Senior Systems Scientist, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2002–
SCOTT HUDSON, Professor, Human-Computer Interaction Institute – Ph.D., University Of Colorado; Carnegie Mellon, 1997–
JEFF ICHNOWSKI, Assistant Professor, Robotics Institute – Ph.D., University of North Carolina at Chapel Hill; Carnegie Mellon, 2023–
DAPHNE IPPOLITO, Assistant Professor, Language Technologies Institute – Ph.D., University of Pennsylvania; Carnegie Mellon, 2023–
FARNAM JAHANIAN, President, Carnegie Mellon University, and Professor, Computer Science Department – Ph.D., University of Texas at Austin; Carnegie Mellon, 2014–
AAYUSH JAIN, Assistant Professor, Computer Science Department – Ph.D, University of California, Los Angeles; Carnegie Mellon, 2021–
LASZLO JENI, Assistant Research Professor, Robotics Institute – Ph.D., University of Tokyo; Carnegie Mellon, 2018–
MATTHEW JOHNSON-ROBERSON, Professor, Director, Robotics Institute – Ph.D., University of Sydney; Carnegie Mellon, 2022–
MICHAEL KAESS, Associate Professor – Ph.D., Georgia Institute of Technology; Carnegie Mellon, 2013–
TAKEO KANADE, University Professor, Robotics Institute – Ph.D., Kyoto University; Carnegie Mellon, 1980–
EUNSUK KANG, Assistant Professor, Institute for Software Research – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2017–
JOSHUA KANGAS, Assistant Teaching Professor, Computational Biology Department – PhD, Carnegie Mellon University; Carnegie Mellon, 2018–
GEORGE KANTOR, Research Professor, Robotics Institute – Ph.D., University of Maryland; Carnegie Mellon, 2002–
IRENE KAPLOW, Assistant Professor, Computational Biology Department – Ph.D., Stanford University; Carnegie Mellon, 2024–
CHRISTIAN KASTNER, Associate Professor, Institute for Software Research – Ph.D., University of Magdeburg; Carnegie Mellon, 2012–
GEOFF KAUFMAN, Associate Professor, Human Computer Interaction Institute – Ph.D., Ohio State University; Carnegie Mellon, 2015–
DILSUN KAYNUR, Associate Teaching Professor, Computer Science Department – Ph.D., University of Edinburgh; Carnegie Mellon, 2012–
ALONZO KELLY, Professor Emeritus, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1998–
SEUNGJUN KIM, Systems Scientist, Human-Computer Interaction Institute – Ph.D., Gwangju Institute of Science and Technology; Carnegie Mellon, 2011–
CARL KINGSFORD, Professor, Computational Biology Department – Ph.D., Princeton University; Carnegie Mellon, 2012–
KRIS KITANI, Associate Research Professor, Robotics Institute – Ph.D., University of Tokyo; Carnegie Mellon, 2016–
ANIKET KITTUR, Professor, Human-Computer Interaction Institute – Ph.D., University of California At Los Angeles; Carnegie Mellon, 2009–
DANIEL KLUG, Systems Scientist, Institute for Software Research – Ph.D., University of Basel; Carnegie Mellon, 2021–
KENNETH KOEDINGER, Professor, Human-Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1991–
ANNE KOHLBRENNER, Assistant Teaching Professor, Computer Science Department – Ph.D., Princeton University; Carnegie Mellon, 2023–
J. ZICO KOLTER, Professor, Computer Science Department – Ph.D., Stanford University; Carnegie Mellon, 2012–
DAVID KOSBIE, Teaching Professor, Computer Science Department – M.S., Carnegie Mellon University; Carnegie Mellon, 2009–
IOANNIS KOUTIS, Adjunct Assistant Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2008–
ROBERT KRAUT, Herbert A. Simon Professor Emeritus, Human-Computer Interaction Institute – Ph.D., Yale University; Carnegie Mellon, 1993–
OLIVER KROEMER, Associate Professor, Robotics Institute – Ph.D., Technische Universität Darmstadt; Carnegie Mellon, 2017–
CLAIRE LE GOUES, Professor, Institute for Software Research – Ph.D., University of Virginia; Carnegie Mellon, 2013–
AVIRAL KUMAR, Assistant Professor, Computer Science Department – Ph.D., University of California, Berkeley; Carnegie Mellon, 2024–
WILLIAM KUSZMAUL, Assistant Professor, Computer Science Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2024–
CHRISTIAN LEBIERE, Research Psychologist, Psychology – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1999–
EUN SUN LEE, Associate Teaching Professor, Institute for Software Research – M.S., Carnegie Mellon University; Carnegie Mellon, 2014–
TAI-SING LEE, Professor, Computer Science Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 1996–
TERRY E LEE, Associate Teaching Professor, Software and Societal Systems Department – M.Sc., Carnegie Mellon University; Carnegie Mellon, 2020–
LORRAINE LEVIN, Research Professor, Language Technologies Institute – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 1989–
JAIOYANG LI, Assistant professor, Robotics Institute – Ph.D., University of Southern California; Carnegie Mellon, 2022–
LEI LI, Associate Professor, Language Technologies Institute – Ph.D., University of California Santa Barbara; Carnegie Mellon, 2023–
MINCHEN LI, Assistant Professor, Computer Science Department – Ph.D., University of Pennsylvania; Carnegie Mellon, 2023–
MAXIM LIKACHEV, Professor, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2010–
ZACHARY LIPTON, Associate Professor, Machine Learning Department – Ph.D., University of California San Diego; Carnegie Mellon, 2024–
CHANGLIU LIU, Associate Professor, Robotics Institute – Ph.D., University of California, Berkeley; Carnegie Mellon, 2019–
YANG LIU, Assistant Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2025–
HAO LIU, Assistant Professor – Ph.D., University of California at Berkeley; Carnegie Mellon, 2025–
JOSE LUGO-MARTINEZ, Assistant Professor, Computational Biology Department – Ph.D., Indiana University; Carnegie Mellon, 2022–
JIAN MA, Professor, Computational Biology Department – Ph.D., Pennsylvania State University ; Carnegie Mellon, 2016–
JOHN MACKEY, Teaching Professor, Computer Science Department and Mathematics Department – Ph.D., University of Hawaii; Carnegie Mellon, 2003–
ZACHARY MANCHESTER, Associate Professor, Robotics Institute – Ph.D., Cornell University; Carnegie Mellon, 2020–
MELISA ORTA MARTINEZ, Assistant Professor, Robotics Institute – PH.D., Stanford University; Carnegie Mellon, 2020–
RUBEN MARTINS, Assistant Research Professor, Institute for Software Research – Ph.D, Technical university of Lisbon; Carnegie Mellon, 2018–
NIKOLAS MARTELARO, Assistant Professor, Human Computer Interaction Institute – Ph.D, Stanford University; Carnegie Mellon, 2020–
MATTHEW MASON, Professor Emeritus, Robotics Institute – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 1982–
AULDYN MATTHEWS-MCGEE, Assistant Teaching Professor, Human Computer Interaction Institute – MHCI, Carnegie Mellon University; Carnegie Mellon, 2023–
JAMES MCCANN, Associate Professor, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2017–
BRUCE MCLAREN, Professor, Human-Computer Interaction Institute – Ph.D., University Of Pittsburgh; Carnegie Mellon, 2003–
HEATHER MILLER, Assistant Professor, Institute for Software Research – Ph.D., École Polytechnique Fédérale de Lausanne; Carnegie Mellon, 2018–
EDUARDO MIRANDA, Teaching Professor, Institute for Software Research – M.S./M.Eng., University of Linköping/University of Ottawa; Carnegie Mellon, 2008–
TERUKO MITAMURA, Research Professor, Language Technologies Institute – Ph.D., University Of Pittsburgh; Carnegie Mellon, 1990–
TOM MITCHELL, University Professor, Machine Learning Department – Ph.D., Stanford University; Carnegie Mellon, 1986–
HOSEIN MOHIMANI, Associate Professor, Computational Biology Department – Ph.D., University of California, San Diego; Carnegie Mellon, 2017–
ALAN MONTGOMERY, Associate Professor of Marketing – Ph.D., University Of Chicago; Carnegie Mellon, 1999–
IGOR MORDATCH, Assistant Professor, Robotics Institute – Ph.D., University of Washington; Carnegie Mellon, 2017–
LOUIS-PHILIPPE MORENCY, Associate Professor, Language Technologies Institute – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2015–
DOMINIK MORITZ, Assistant Professor, Robotics Institute – Ph.D, University of Washington; Carnegie Mellon, 2020–
JAMES MORRIS, Professor, Emeritus, Human-Computer Interaction Institute – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 1982–
DAVID MORTENSEN, Assistant Research Professor, Language Technologies Institute – Ph.D, University of California, Berkeley; Carnegie Mellon, 2015–
JACK MOSTOW, Research Professor Emeritus, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1992–
TODD MOWRY, Professor, Computer Science Department – Ph.D., Stanford University; Carnegie Mellon, 1997–
KATHARINA MUELLING, Systems Scientist, Robotics Institute – Ph.D., Max Planck Institute for Intelligent Systems; Carnegie Mellon, 2013–
ROBERT MURPHY, Ray and Stephanie Lane Professor of Computational Biology Emeritus – Ph.D., California Institute of Technology; Carnegie Mellon, 1983–
BRAD MYERS, Professor, Human-Computer Interaction Institute – Ph.D., University Of Toronto; Carnegie Mellon, 1987–
PRIYA NARASIMHAN, Professor – Ph.D., University Of California; Carnegie Mellon, 2001–
SRINIVASA NARASIMHAN, Professor, Interim Director, Robotics Institute – Ph.D., Columbia University; Carnegie Mellon, 2004–
ARAN NAYEBI, Assistant Professor, Machine Learning Department – Ph.D., Stanford University; Carnegie Mellon, 2024–
GRAHAM NEUBIG, Associate Professor, Language Technologies Institute – Ph.D., Kyoto University; Carnegie Mellon, 2016–
MEG NEUMANN, Assistant Teaching Professor, Human-Computer Interaction Institute – M.S., Carnegie Mellon University; Carnegie Mellon, 2025–
CHRISTINE NEUWIRTH, Professor – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2004–
ILLAH NOURBAKHSH, Professor, Robotics Institute – Ph.D., Stanford University; Carnegie Mellon, 1997–
ERIC NYBERG, Professor, Language Technologies Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1989–
RYAN O'DONNELL, Professor, Computer Science Department – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 2006–
KEMAL OFLAZER, Associate Dean of Research, Language Technologies Institute – Ph.D, Carnegie Mellon University; Carnegie Mellon, 2008–
AMY OGAN, Associate Professor, Human-Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2014–
DAVID O'HALLARON, Professor Emeritus, Computer Science Department – Ph.D., University of Virginia; Carnegie Mellon, 1989–
JEAN OH, Associate Research Professor, Robotics Institute – Ph.D, Carnegie Mellon University; Carnegie Mellon, 2019–
IRVING OPPENHEIM, Professor – Ph.D., University of Cambridge; Carnegie Mellon, 1973–
MATTHEW O'TOOLE, Associate Professor, Robotics Institute and Computer Science Department – Ph.D., University of Toronto; Carnegie Mellon, 2018–
RICCARDO PACCAGNELLA, Assistant Professor, Software and Societal Systems Department – Ph.D., University of Illinois Urbana-Champaign; Carnegie Mellon, 2023–
ROHAN PADHYE, Assistant Professor, Software and Societal Systems Department – Ph.D., University of California, Berkeley; Carnegie Mellon, 2020–
PATRICK PARK, Assistant Professor, Institute for Software Research – Ph.D, Cornell University; Carnegie Mellon, 2021–
BRYAN PARNO, Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2017–
JIGNESH PATEL, Professor, Computer Science Department – Ph.D., University of Wisconsin Madison; Carnegie Mellon, 2023–
DEEPAK PATHAK, Assistant Professor, Robotics Institute – Ph.D, University of California, Berkeley; Carnegie Mellon, 2020–
SCOTT PAVETTI, Assistant Teaching Professor, Software and Societal Systems Department – MSE, Carnegie Mellon University; Carnegie Mellon, 2020–
ANDREW PAVLO, Associate Professor, Computer Science Department – Ph.D., Brown University; Carnegie Mellon, 2013–
RICHARD PENG, Associate Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2023–
ADAM PERER, Associate Professor, Human Computer Interaction Institute – Ph.D., University of Maryland; Carnegie Mellon, 2018–
JUERGEN PFEFFER, Assistant Research Professor, Institute for Software Research – Ph.D., Vienna University of Technology; Carnegie Mellon, 2012–
ANDREAS PFENNING, Associate Professor, Computational Biology Department – Ph.D., Duke University; Carnegie Mellon, 2015–
FRANK PFENNING, Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1986–
BABU PILLAI, Associate Teaching Professor, Computer Science Department – Ph.D., University of Michigan; Carnegie Mellon, 2025–
BARNABAS POCZOS, Associate Professor, Machine Learning Department – Ph.D., Eötvös Loránd University; Carnegie Mellon, 2012–
NANCY POLLARD, Professor, Robotics Institute – Ph.D., Massachusetts Institute Of Technology; Carnegie Mellon, 2002–
ADITI RAGHUNATHAN, Assistant Professor, Computer Science Department – Ph.D., Stanford University; Carnegie Mellon, 2022–
BRIAN RAILING, Associate Teaching Professor, Computer Science Department – Ph.D., Georgia Institute of Technology; Carnegie Mellon, 2016–
BHIKSHA RAJ RAMAKRISHNAN, Professor, Language Technologies Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2008–
DEVA RAMANAN, Professor, Robotics Institute – Ph.D., University of California at Berkeley; Carnegie Mellon, 2015–
PRADEEP RAVIKUMAR, Professor, Machine Learning Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2016–
RAJ REDDY, University Professor, Institute for Software Research – Ph.D., Stanford University; Carnegie Mellon, 1969–
ANDREJ RISTESKI, Associate Professor, Machine Learning Department – Ph.D., Princeton University; Carnegie Mellon, 2019–
KELLY RIVERS, Associate Teaching Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2017–
CAMERON RIVIERE, Research Professor, Robotics Institute – Ph.D., Johns Hopkins University; Carnegie Mellon, 1995–
DAVID ROOT, Associate Teaching Professor, Institute for Software Research – M.P.M., Carnegie Mellon University; Carnegie Mellon, 2002–
CAROLYN ROSE, Professor, Language Technologies Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2003–
RONALD ROSENFELD, Professor and Department Head, Machine Learning Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1995–
STEPHANIE ROSENTHAL, Associate Teaching Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2019–
ALEXANDER RUDNICKY, Professor Emeritus, Language Technologies Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1980–
MATTHEW RUFFALO, Systems Scientist, Computational Biology Department – Ph.D., Case Western Reserve University; Carnegie Mellon, 2016–
FERAS SAAD, Assistant Professor, Computer Science Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2023–
NORMAN SADEH-KONIECPOL, Professor, Institute for Software Research – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1991–
MAJD SAKR, Teaching Professor, Computer Science Department – Ph.D., University of Pittsburgh; Carnegie Mellon, 2006–
RUSLAN SALAKHUTDINOV, Professor, Machine Learning Department – Ph.D., University of Toronto; Carnegie Mellon, 2016–
TUOMAS SANDHOLM, Professor, Computer Science Department – Ph.D., University of Massachusetts; Carnegie Mellon, 2001–
MAARTEN SAP, Assistant Professor, Language Technologies Institute – Ph.D., University of Washington; Carnegie Mellon, 2022–
MAHADEV SATYANARAYANAN, Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1983–
JULIE SAUNDERS, Assistant Teaching Professor, Human-Computer Interaction Institute – MDes, Carnegie Mellon University; Carnegie Mellon, 2025–
SARAH SCHEFFLER, Assistant Professor, Software and Societal Systems Department – Ph.D., Boston University; Carnegie Mellon, 2024–
RICHARD SCHEINES, Dean, Dietrich College and Professor, Philosophy – Ph.D., University of Pittsburgh; Carnegie Mellon, 1988–
SEBASTIAN SCHERER, Associate Research Professor, Robotics Institute – Ph.D, Carnegie Mellon University; Carnegie Mellon, 2010–
BRADLEY SCHMERL, Principal Systems Scientist, Computer Science Department – Ph.D., Flinders University of South Australia; Carnegie Mellon, 2000–
JEFF SCHNEIDER, Research Professor, Robotics Institute – Ph.D., University of Rochester; Carnegie Mellon, 1995–
RUSSELL SCHWARTZ, Professor of Biological Sciences and Department Head, Computational Biology Department – Ph.D, Massachusetts Institute of Technology; Carnegie Mellon, 2002–
DANA SCOTT, Professor Emeritus, Computer Science Department – Ph.D., Princeton University; Carnegie Mellon, 1981–
TEDDY SEIDENFELD, Herbert A. Simon Professor – Ph.D., Columbia University; Carnegie Mellon, 1985–
SRINIVASAN SESHAN, Professor and Department Head, Computer Science Department – Ph.D., University of California; Carnegie Mellon, 2000–
NIHAR SHAH, Associate Professor, Machine Learning Department – Ph.D., University of California at Berkeley; Carnegie Mellon, 2017–
MICHAEL SHAMOS, Teaching Professor, Language Technologies Institute and Institute for Software Research – Ph.D., Yale University; Carnegie Mellon, 1975–
MARY SHAW, University Professor, Institute for Software Research – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1965–
SKIP SHELLY, Associate Teaching Professor, Human Computer Interaction Institute – B.F.A., Carnegie Mellon University; Carnegie Mellon, 2017–
HONG SHEN, Assistant Professor, Human Computer Interaction Institute – Ph.D., University of Illinois, Urbana-Champaign; Carnegie Mellon, 2018–
JUSTINE SHERRY, Associate Professor, Computer Science Department – Ph.D., University of California at Berkeley; Carnegie Mellon, 2017–
GUANYA SHI, Assistant Professor, Robotics Institute – Ph.D., California Institute of Technology; Carnegie Mellon, 2023–
ELAINE SHI, Associate Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2020–
HIROKAZU SHIRADO, Associate Professor, Human Computer Interaction Institute – Ph.D., Yale University; Carnegie Mellon, 2019–
DOUGLAS SICKER, Professor, Institute for Software Research – Ph.D., University of Pittsburgh; Carnegie Mellon, 2014–
MEL SIEGEL, Associate Research Professor Emeritus, Robotics Institute – Ph.D., University of Colorado; Carnegie Mellon, 1982–
DANIEL SIEWIOREK, Buhl University Professor Emeritus, Computer Science Department – Ph.D., Stanford University; Carnegie Mellon, 1972–
MAX SIMCHOWITZ, Assistant Professor, Machine Learning Department – Ph.D., University of California, Berkeley; Carnegie Mellon, 2025–
REID SIMMONS, Research Professor, Robotics Institute – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 1988–
AARTI SINGH, Professor, Machine Learning Department – Ph.D., University of Wisconsin At Madison; Carnegie Mellon, 2009–
RITA SINGH, Research Professor, Language Technologies Institute – Ph.D., National Geophysical Research Institute; Carnegie Mellon, 2010–
MICHAEL SKIRPAN, Assistant Teaching Professor, Software and Societal Systems Department – Ph.D., University of Colorado Boulder; Carnegie Mellon, 2023–
DANIEL SLEATOR, Professor, Computer Science Department – Ph.D., Stanford University; Carnegie Mellon, 1985–
STEPHEN SMITH, Research Professor, Robotics Institute – Ph.D., University of Pittsburgh; Carnegie Mellon, 1982–
VIRGINIA SMITH, Associate Professor, Machine Learning Department – Ph.D., University of California at Berkeley; Carnegie Mellon, 2018–
PETER SPIRTES, Professor, Philosophy – Ph.D., University of Pittsburgh; Carnegie Mellon, 1983–
JOHN STAMPER, Associate Professor, Human-Computer Interaction Institute – Ph.D., University of North Carolina At Charlotte; Carnegie Mellon, 2009–
PETER STEENKISTE, Professor, Computer Science Department – Ph.D., Stanford University; Carnegie Mellon, 1987–
MARK STEHLIK, Teaching Professor, Computer Science Department – B.S., Pace University; Carnegie Mellon, 1981–
AARON STEINFELD, Research Professor, Robotics Institute – Ph.D., University of Michigan; Carnegie Mellon, 2001–
GEORGE STETTEN, Adjunct Research Professor, Robotics Institute – Ph.D., University of North Carolina; Carnegie Mellon, 1999–
EMMA STRUBELL, Assistant Professor, Language Technologies Institute – Ph.D, University of Massachusetts, Amherst; Carnegie Mellon, 2020–
JOSHUA SUNSHINE, Associate Professor, Institute for Software Research – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2014–
KLAUS SUTNER, Teaching Professor, Computer Science – Ph.D., University of Munich; Carnegie Mellon, 1995–
KATIA SYCARA, Research Professor, Robotics Institute – Ph.D., Georgia Institute of Technology; Carnegie Mellon, 1987–
WENNIE TABIB, Systems Scientist, Robotics Institute – Ph.D, Carnegie Mellon University; Carnegie Mellon, 2021–
AMEET TALWALKAR, Associate Professor, Machine Learning Department – Ph.D., New York University, Courant Institute; Carnegie Mellon, 2017–
MICHAEL TAYLOR, Assistant Teaching Professor, Computer Science Department – MSR, Carnegie Mellon University; Carnegie Mellon, 2020–
ZEYNEP TEMEL, Associate Professor, Robotics Institute – Ph.D., Sabanci University (Istanbul, Turkey); Carnegie Mellon, 2019–
CHRIS TIMPERLEY, Associate Teaching Professor, Software and Societal Systems – Ph.D., University of York, UK; Carnegie Mellon, 2018–
BEN TITZER, Assistant Research Professor, Software and Societal Systems Department – Ph.D., University of California, Los Angeles; Carnegie Mellon, 2025–
DAVID TOURETZKY, Research Professor, Computer Science Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1984–
MATTHEW TRAVERS, Senior Systems Scientist, Robotics Institute – Ph.D., Northwestern University; Carnegie Mellon, 2013–
BOGDAN VASILESCU, Associate Professor, Institute for Software Research – Ph.D., Eindhoven University of Technology; Carnegie Mellon, 2016–
MARIA MANUELA VELOSO, Professor Emeritus, Machine Learning Department – Ph.D, Carnegie Mellon University; Carnegie Mellon, 1992–
RASHMI VINAYAK, Associate Professor, Computer Science Department – Ph.D., University of California at Berkeley; Carnegie Mellon, 2017–
LAURA VINCHESI, Assistant Teaching Professor, Human Computer Interaction Institute – MFA, Cranbrook Art Academy; Carnegie Mellon, 2023–
PAT VIRTUE, Assistant Teaching Professor, Computer Science Department and Machine Learning Department – Ph.D., University of California at Berkeley; Carnegie Mellon, 2018–
ALEXANDER WAIBEL, Professor, Language Technologies Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 1988–
WEINA WANG, Associate Professor, Computer Science Department – Ph.D., Arizona State University; Carnegie Mellon, 2018–
WENSHEN WANG, Systems Scientist, Robotics Institute – Ph.D., Shanghai Jiao Tong University; Carnegie Mellon, 2023–
LEILA WEHBE, Assistant Professor, Machine Learning Department – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2018–
DAVID WETTERGREEN, Research Professor, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2000–
BRYAN WILDER, Assistant Professor, Machine Learning Department – Ph.D., Harvard University; Carnegie Mellon, 2022–
DAVID WOODRUFF, Professor, Computer Science Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2017–
WEI WU, Senior Systems Scientist, Computational Biology Department – Ph.D., Rutgers University; Carnegie Mellon, 2011–
SHERRY TONGSHUAN WU, Assistant Professor, Human Computer Interaction Institute – Ph.D., Washington University, Saint Louis; Carnegie Mellon, 2022–
STEVEN WU, Associate Professor, Software and Societal Systems Department – Ph.D., University of Pennsylvania; Carnegie Mellon, 2020–
FRANCESKA XHAKAJ, Assistant Teaching Professor, Computer Science Department/ Human Computer Interaction Institute – Ph.D, Carnegie Mellon University; Carnegie Mellon, 2021–
POE ERIC XING, Professor, Machine Learning Department – Ph.D., University Of California At Berkeley; Carnegie Mellon, 2004–
CHENYAN XIONG, Associate Professor, Language Technologies Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2023–
MIN XU, Associate Professor, Computational Biology Department – Ph.D., University of Southern California; Carnegie Mellon, 2016–
YIMING YANG, Professor, Language Technologies Institute – Ph.D., Kyoto University; Carnegie Mellon, 1996–
NESRA YANNIER, Senior Systems Scientist, Human Computer Interaction Institute – Ph.D., Carnegie Melllon University; Carnegie Mellon, 2019–
YUN WILLIAM YU, Associate Professor, Computational Biology Department – Ph.D., Massachusetts Institute of Technology; Carnegie Mellon, 2023–
MARTIN ZHANG, Assistant Professor, Computational Biology Department – Ph.D., Stanford University; Carnegie Mellon, 2023–
JI ZHANG, System Scientist, Robotics Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2019–
HAIYI ZHU, Associate Professor, Human Computer Interaction Institute – Ph.D., Carnegie Mellon University; Carnegie Mellon, 2019–
JUN-YAN ZHU, Assistant Professor, Robotics Institute – Ph.D, University of California, Berkeley; Carnegie Mellon, 2020–
JOHN ZIMMERMAN, Professor, Human-Computer Interaction Institute – M.Des., Carnegie Mellon University; Carnegie Mellon, 2002–