Most recent news

• Plenary talk (on domain adaptation and friends) at Sampling Theory and Applications 2023, Yale University, USA.

• Plenary talk (on domain adaptation and friends) at Journée des Statistiques 2022, Lyon, France.

• Plenary talk (on transfer and multitask) at IBIS (Japan's leading ML venue) 2021, Japan.

• 2021 Sloan Fellow.

• Honored to co-Chair COLT 2021 with Misha Belkin.

• Visiting the Institute of Advanced Studies in Princeton, Jan-May 2020, as part of a
  special year on Optimization, Statistics and Theoretical Machine Learning, led by Sanjeev Arora.

• Plenary talk (on transfer and fairness) at Deep Learning Indaba 2019, Nairobi, Kenya.

• Lecture (on modern analysis of kNN) at Machine Learning Summer School (MLSS) 2018, London, UK.

• Bell Labs first Prize, 2019, for a proposal on Fundamental Limits of Transfer Learning.

• Joint NSF grant (id. 1739809) with N. Feamster and A. Nadarayan, for Security and ML in IoT.

• 2018 Princeton School of Engineering Outstanding Research and Teaching Award for Junior Faculty.
  (E. Lawrence Keyes, Jr./Emerson Electric Co. Faculty Advancement Award)

• Research award for a new collaboration with ODH, Inc on Healthcare Analytics.

• Plenary talk (on measuring transferability) at the 5th ECCV workshop on Transfer Learning in Vision.

• Tutorial at ICML 2018, with Sanjoy Dasgupta, on new perspectives on kNN (Slides, Part 1 and Part 2)

Less recent news

• Princeton Engineering Commendation List for Outstanding Teaching (ORF 524, Fall 16-17).

• Co-organized NIPS 2016 Workshop on Nonparametrics.

• 2016 Seed grant from Siebel Energy Institute, jointly with Prof. Nick Feamster, to work on ML challenges in Internet-Of-Things (smart home/cities). Initial work will consider anomalous activity detection.

• Lecture (on nonparametric and minimax analysis) at Machine Learning Summer School (MLSS) 2016, Cadiz.

• Princeton Engineering Commendation List for Outstanding Teaching (ORF 524, Fall 15-16)