Metadata
Title
Computer scientists awarded $1M NSF grant to reduce waste through AI
Category
general
UUID
19fe94443dfa40ce8118744d848e712e
Source URL
https://engineering.rice.edu/news/computer-scientists-awarded-1m-nsf-grant-reduc...
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https://engineering.rice.edu/research-faculty/research-focus-areas/future-comput...
Crawl Time
2026-03-23T20:01:45+00:00
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Computer scientists awarded $1M NSF grant to reduce waste through AI

Source: https://engineering.rice.edu/news/computer-scientists-awarded-1m-nsf-grant-reduce-waste-through-ai Parent: https://engineering.rice.edu/research-faculty/research-focus-areas/future-computing

Patrick Kurp - Jul. 1, 2024

POSTED IN: RICE ENGINEERING

News

Computer scientists awarded $1M NSF grant to reduce waste through AI

Small Business Innovation Research grant will allow Costilla Reyes and Hu to further their work on automated machine-learning platform AutoEdge.ai.

Two computer scientists associated with Rice have received a highly competitive, $1-million Small Business Innovation Research (SBIR) grant from the National Science Foundation to further their work on AutoEdge.ai, an automated machine-learning platform for edge devices, which are the interfaces between data centers and the real world.

“Our goal is to support manufacturers in harnessing the power of artificial intelligence to reduce industrial waste. AutoEdge simplifies deployment of quality assurance tools, making advanced technology accessible and easy to integrate into existing processes. We help their efficiency, improve product quality, and minimize waste, contributing to a more sustainable and profitable future,” said Alfredo Costilla Reyes, who was a postdoctoral researcher in computer science (CS) at Rice from 2020 to 2022, and now works full time for his company, AI POW LLC.

His research and business partner is Dr. Xia “Ben” Hu, associate professor of CS at Rice. Their proposal is titled “A Hardware-Aware AutoML Platform for Resource-Constrained Devices.”

“We want to make AI models on edge devices possible for the real-time detection of defects in industrial manufacturing systems. The problem lies in creating a scalable, efficient and easy-to-use solution,” Hu said.

The research uses artificial intelligence, edge computing and user feedback to create user-friendly solutions, including a system that performs real-time defect detection with reduced resource usage.

Costilla Reyes and Hu have also received a Rice Innovation Fellowship, an earlier NSF SBIR grant, and backing from the Technology Development Fund in the Rice Office of Technology Transfer.

Costilla Reyes earned his Ph.D. in electrical engineering at Texas A&M University in 2020. Hu earned his Ph.D. in CS from Arizona State University in 2015 and joined the Rice faculty in 2021.

[ABOUT PATRICK KURP


Patrick Kurp is a science writer for the George R. Brown School of Engineering.](https://profiles.rice.edu/staff/patrick-kurp)