Assistant Professor
School of Computer Science
Carnegie Mellon University
Oct 2024
Together with Drew Bagnell and our student Gokul Swamy, we are teaching a new course in the upcoming spring semester: 17-740: Algorithmic Foundations of Interactive Learning.
Sept 2024
Six papers accepted at NeurIPS 2024 and one paper at WINE 2024:
PhD students
Daniel Ngo (co-advised by Maria Gini)
Logan Stapleton (co-advised by Haiyi Zhu)
Justin Whitehouse (co-advised by Aaditya Ramdas)
Keegan Harris (co-advised by Nina Balcan)
Gokul Swamy (co-advised by Drew Bagnell)
Luke Guerdan (co-advised by Ken Holstein)
Terrance Liu
Jingwu Tang (co-advised by Fei Fang)
Anusha Sinha (co-advised by Hoda Heidari)
Kimberly Truong (co-advised by Hoda Heidari)
Jiahao Zhang
Undergrad &
Master's Students
Ally Du
Xiaoyu Wu (visiting master student from Shanghai Jiaotong U.)
Henry Jin (visiting undergrad from Tsinghua)
Yuanchen Tang (visiting undergrad from Peking U.)
Alumni
Giuseppe Vietri (PhD student), now at Amazon
Hao-Fei Cheng (PhD student), now at Amazon
Shuran Zheng (Post-doc), now on the IIIS faculty at Tsinghua University
Xin Gu (MS), now a PhD student at Penn State
Ken Ziyu Liu (MS), now a PhD student at Stanford
Konwoo Kim (undergrad, winner of the Allen Newell Award), now a PhD student at Stanford
Yuqi Pan (visiting undergrad from Peking U.), now a PhD student at Harvard
Huiying Zhong (visiting undergrad from Peking U.), now a PhD student at MIT
Jiayun Wu (visiting masters student from Tsinghua)
Xinyan Hu (visiting undergrad from Peking U.), now a PhD student at UC Berkeley
Leijie Wang (visiting undergrad from Tsinghua), now a PhD student at Univ. of Washington
Jocelyn Chou (REU student from Rutgers)
Diana Qing (REU student from Berkeley), now an MS student at Stanford
Harry Tian (REU student from Carleton), now a PhD student at Purdue
Grace Tian (REU student from Harvard), now an ML engineer at Hive
Allen Marquez (REU student from Cal State LA), now a software engineer at Northrop Grumman
Conference Program Committee
NeurIPS 2022, 2021, 2020 (area chair)
ICML 2022, 2020 (area chair)
ICLR 2024, 2022, 2021, 2020 (area chair)
AISTATS 2021 (area chair)
COLT 2025, 2024, 2023 (SPC)
EC 2025 (SPC)
ITCS 2022
SODA 2022
ALT 2021
FORC 2020, 2024
FAccT 2019, 2021, 2023 (area chair)
TheWebConf 2020, 2018
Workshop Program Committee
TPDP 2021, 2019
NIPSML4H18
HAI-GEN 2020
Workshop Organizer
Intersectionality in Fair Machine Learning: Where Are We and Where Should We Go from Here? MOSAIC 2020: An Annual Conference on Intersectionality. Nov. 1, 2020.
Recent Developments in Research on Fairness. The Simons Institute for the Theory of Computing, Berkeley, CA. July 8-10, 2019.
Other
I co-organize differentialprivacy.org.
During my undergraduate, I was involved in
the Bard Prison
Initiative as a math tutor at
the Eastern New York Correctional
Facility. Check out this amazing four-part
documentary film
series, College Behind Bars, about this
initiative.
Feb 2022
Of Moments and Matching: Trade-offs and Treatments in Imitation Learning
Simons Institute Workshop on Adversarial Approaches in Machine Learning
YouTube
Mar 2021
A Geometric View on Private Gradient-Based Optimization
Federated Learning One World Seminar (FLOW)
Google TechTalks
FLOW Video
Google Video
Mar 2021
Feb 2021
Involving Stakeholders in Building Fair ML Systems
Foundations of Algorithmic Fairness Workshop
IDEAL Quarterly Theory Workshop: Algorithms and their Social
Impact
Trustworthy ML Initiative (TrustML) Seminar
YouTube
Panopto
Mar 2021
Feb 2021
Leveraging Heuristics in Private Synthetic Data Generation
CMU Crypto/Applied crypto seminar
PPAI workshop 2021
Boston-area Data Privacy Seminar
PPAI Video
CMU Cryto Video
Oct 2019
Tutorial: Differential Privacy Techniques Beyond Differential
Privacy
FOCS
2019 workshop
A TCS Quiver
Slides