Elio (Keqiang) Yan
@KeqiangY
CS Ph.D. @TAMU. D.E. Shaw Research Doctoral Fellow. AI&LLMs for Science including materials, proteins and others. Ex @MSFTResearch @PKU1898.
Excited and proud mentor moment 💫! A new materials foundation model with two of my undergraduate mentees Montgomery Bohde and Andrii Kryvenko as core authors. For Materials Foundation Models, Invariance V.S. Equivariance? Invariance + Equivariance!
Our 500+ page AI4Science paper is finally published: Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. Foundations and Trends® in Machine Learning, Vol. 18, No. 4, 385–912, 2025 nowpublishers.com/article/Detail…
All AIMEDx webinar recordings are available here: youtube.com/playlist?list=… Thanks to all our speakers and attendees for an incredible season of ideas and inspiration. We are off for a break, wishing everyone a restful summer! #AI4Science #AIMEDx
New paper alert: Toward Greater Autonomy in Materials Discovery Agents: Unifying Planning, Physics, and Scientists. arxiv.org/abs/2506.05616
Excited to share that I received CSE Graduate Research Excellence Award from Texas A&M University (one per year) ! Grateful to all the support along the way from my amazing mentors, collaborators, friends and family, especially Dr. Ji @ShuiwangJi .
Registration is now open for our next AIMEDx Webinar. Excited to host @KeqiangY. Speaker: Keqiang Yan (Texas A&M University) Title: AI for Materials Discovery: Graphs, Language Models, and Agents 📅 March 3, 2025 | 11:00 AM EST Register now: shorturl.at/1BVfP #AI4Science
In our labs @MSFTResearch, as well as great labs around the world, AI is rapidly enabling advances in biomedical research, some of which are very likely to be transformative breakthroughs for human health. It's a time for nations to double-down on research support, not pull back.
Our engineer team at @MSFTResearch AI for Science is hiring a Senior Research Engineer in Berlin, Amsterdam, or Cambridge (UK). We’d love to see candidates with industry experience (or equivalent) who love infrastructure, big data, debugging, profiling, and optimization of…
Fantastic collaboration with @KeqiangY and @ShuiwangJi @HarvardDBMI
"Invariant Tokenization for Language Model Enabled Crystal Materials Generation" is featured as a conference paper at #NeurIPS2024 today. Check out the work by #KempnerInstitute's @marinkazitnik & colleagues: buff.ly/3DiUl4i