AI News & Events
Source: https://www.northeastern.edu/ai/news-events/ Parent: https://www.northeastern.edu/ai/
News and events
Tracking AI breakthroughs and innovators
We’re breaking new ground in addressing critical world issues through AI-infused learning and discovery. See how we’re supercharging our impact through AI.
Latest ways we are shaping an enhanced future.
- Northeastern researchers develop AI app to help speech-impaired users communicate more naturally
Northeastern researchers develop AI app to help speech-impaired users communicate more naturally
Mar. 21, 2025 - Researcher’s sustainable fertilizer breakthrough fueled by machine learning and quantum mechanics
Researcher’s sustainable fertilizer breakthrough fueled by machine learning and quantum mechanics
Feb. 12, 2025 - What is Jevons Paradox? And why it may—or may not—predict AI’s future
What is Jevons Paradox? And why it may—or may not—predict AI’s future
Feb. 07, 2025 - Grant will allow Northeastern center to expand AI education
Grant will allow Northeastern center to expand AI education
Dec. 11, 2024
Events and programs
Participate in our AI research community’s events
- Shared Patterns: Form and Labor in Crafts and Generative AI – Sei Jung
Shared Patterns: Form and Labor in Crafts and Generative AI – Sei Jung
Mar. 17, 2026 - Creating Visuals with AI
Creating Visuals with AI
Mar. 18, 2026 - Teaching AI-Powered Research Tools in the First Year and Beyond
Teaching AI-Powered Research Tools in the First Year and Beyond
Mar. 20, 2026 - AI for Text Analysis with Python Using BERT and PyTorch
AI for Text Analysis with Python Using BERT and PyTorch
Mar. 24, 2026 - 2026 Klein Lecture
2026 Klein Lecture
Mar. 24, 2026 - 2026 Hanson Lecture
2026 Hanson Lecture
Mar. 30, 2026 - Using AI Tools To Manage Your Personal & Professional Life
Using AI Tools To Manage Your Personal & Professional Life
Apr. 02, 2026 - NULab Spring Conference 2026
NULab Spring Conference 2026
May 01, 2026
AI co-op case studies
How our students are leveraging AI to effect change
Our talented co-op students are using AI to solve real-world challenges while forging paths toward meaningful careers.
Developing brain-inspired computing hardware
Mauricio Tedeschi worked as a co-op at the Peter Grünberg Institute, where he helped the research center develop and test algorithms for “brain-inspired hardware” for high-performance computing. By mimicking neurons in the human brain, researchers hope to make computer chips more efficient and cost effective. Tedeschi, a computer science and physics major, assisted in the development of code to make these chips handle complicated tasks more efficiently. The research was published in the 2024 IEEE International Conference on Rebooting Computing proceeding.
Co-op students develop AI chatbot for state transit system
Ria Singh and Rudra Sett, students in Northeastern’s AI for Impact Co-op Program, built a generative artificial intelligence chatbot to share information about the MBTA’s paratransit service. The students developed a system that allows call takers to quickly search policies and other MBTA documents. The chatbot also finds answers to queries that the customer service representatives can relay back to the customer. The tool will allow CSRs to more quickly share key transit information with the public.
AI tool connects farmers with environmental grants
Diane Grant and Rachel Kahn—who are both majoring in computer science and political science—created a navigation tool that consolidates information on grants offered by the Massachusetts’ Office of Energy and Environmental Affairs. Their AI-powered tool allows businesses, municipalities, nonprofits, and farmers to search a database of grant information to find appropriate opportunities more easily. Grant and Kahn hope that their tool will also help constituents determine their eligibility, understand grant requirements, and more. Both students are part of the AI for Impact Co-op Program.
Gaining experience in machine learning
Ava Knight completed a co-op with Werusys Industrie Informatik, a German data analytics and machine-learning artificial intelligence company. While working for the company, she developed an application within a data analytics software that used machine learning to analyze time-series energy usage data from a manufacturing plant in order to identify optimal production conditions. Knight appreciated this co-op for granting her extensive app development and problem-solving experience.
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