 |
Yi Ding |
I am an Assistant Professor of the Elmore Family School of Electrical and Computer Engineering at Purdue University, where I lead the STYLE (SusTainable computing sYstems and LEarning) Lab. Previously, I was an NSF Computing Innovation Fellow and Postdoctoral Associate at MIT CSAIL mentored by Michael Carbin. During my postdoc, I also held a visiting position at Meta Infra Data Center to improve maintenance efficiency of millions of servers in hyperscale datacenters. I received my Ph.D. in Computer Science from The University of Chicago advised by Henry Hoffmann.
My research interests are in the broad areas of computer systems, computer architecture, and machine learning, with a focus on sustainable computing, and causal inference for distributed systems.
Hiring: I am looking for self-motivated Ph.D students who are devoted to research excellence or high-quality system building in energy-efficient datacenters, sustainable cloud computing, and learning-based techniques for computer systems optimization. If you are interested in working with me, please apply for Purdue ECE PhD program and mention my name in your application.
What is New?
2024-07: Two HotCarbon'24 papers have been accepted! One focuses on uncertainty-aware datacenter decarbonization, and the other is about sustainable LLMs.
2024-06: Two DUIRI undergrad research internship proposals have been accepted! One focuses on LCA for sustainable AI computing, and the other examines energy use and carbon emissions in training autonomous vehicles. Purdue Engineering undergrads are encouraged to apply here and here!
2024-06: Applications for the NSF Workshop on Sustainable Computing are open. Submit your applications here!
2024-04-18: Inez Hua and I will oragnize an NSF Sustainability in Computing Workshop focusing on AI computing, water, and biodiversity. Thank NSF for the support!
2023-08-14: Joined Purdue ECE as an Assistant Professor.
2022-08-16: Gave a talk at Meta Infrastructure Data Science Faculty Workshop at KDD'22, DC.
2022-06-16: CAFQA accepted to ASPLOS'23. I introduced Bayesian optimization to search the Clifford ansatz efficiently for quantum accuracy.
2022-04-08: Minimax designs for long-term causal effects accepted to Biometrika, a top theoretical statistics journal.
2022-01-14: NURD for online datacenter straggler prediction accepted to MLSys'22.
2021-08-17: Won Meta Research Award on Statistics for Improving Insights, Models, and Decisions.
2021-07-29: Programming with Neural Surrogates of Programs accepted to Onward!'21.
2021-05-20: GIL for generalizable and interpretable configuration extrapolation accepted to ESEC/FSE'21.
2021-03-18: CIFellows Project Spotlight on CCC Blog and CRA Bulletin!
2021-01-04: Start my postdoc at PSG, MIT CSAIL!
2020-11-09: Attended EECS Rising Stars Workshop at UC Berkeley.
2020-11-03: Successfully defended my Ph.D. thesis!
2020-07-21: Selected as a 2020 Computing Innovation Fellow by CRA/CCC!