The MIDAS faculty community has grown significantly in the past years and now consists of more than 750 faculty members across the university. In order to help our faculty affiliates get to know each other, each month, MIDAS hosts an informal faculty gathering of affiliates around a particular domain or theme to explore research questions or discuss possible grant proposals.
The purpose of these connections is to:
- Connect faculty members from across the university
- Pursue funding opportunities
- Facilitate AI-driven research discussions
- Support AI development for research applications
Past Session Themes
- AI and quantum
- AI and math
- AI and clinical decision-making
- AI and humanities
- AI and health and medicine
- AI and energy
Interested in Suggesting a Topic?
Partner with MIDAS to bring together faculty across disciplines to explore collaborative research opportunities in AI and data science. Contact us at [email protected] to get started.
Testimonial
How two MIDAS affiliate faculty members sparked collaboration after meeting at the Faculty Research Pitch.
After meeting for the first time at the Faculty Research Pitch in 2023, Liyue Shen and Hui Deng developed cross-collaboration between both of their labs. “I randomly came across Hui’s great talk to introduce this important problem of inverse design of photonics device structure, and then reached out to her to learn more about this application and propose to solve this problem using generative AI methods my lab has been working on,” said Shen.
Since then, their collaboration expanded with biweekly meetings with students from both labs, including Schmidt AI in Science Fellow Xin Xie. “Xin has helped a lot to generate the simulated data and run preliminary results to get our collaborative project started, and also helped to write about the problems and applications in our proposal submission to ACED in June 2024,” stated Shen.
“We are so happy to see that our first proposal submission led to success at the first trial. It would definitely not have happened without MIDAS to organize the workshop and to support Xin’s fellowship. We very much appreciate this!”
Liyue Shen
Assistant Professor of Electrical Engineering and Computer Science, College of Engineering
Hui Deng
Professor of Physics, College of Literature, Science, and the Arts,
Professor of Electrical Engineering and Computer Science, College of Engineering
Xin Xie
Schmidt AI in Science Fellow, 2022 Cohort