Shiwei Zeng
Email: szeng4 at stevens dot edu
I am a fifth-year Ph.D. candidate at Stevens Institute of Technology, advised by Professor Jie Shen. My area of research is on Machine Learning Theory and Algorithmic Robustness. I study scenarios when machine learning algorithms are faced with modern challenges such as malicious adversaries, data deficiency, and unreliable human feedbacks; meanwhile, my interest goes well beyond that, including but not limited to data privacy, algorithmic fairness, and algorithmic game theory. Recently, I am concerned about mu
I received a B.Eng. in Electronic Engineering and a B.Eng. in Microelectronics from Hong Kong Polytechnic University and Sun Yat-sen University at the same time in 2015. I came to the U.S. in 2018, where I found my passion in machine learning theory with the great help of my advisor!
I am on the job market right now! My CV and research statement can be accessed through links.
News:
Received the Stevens Excellence Doctoral Award.
Passed my thesis proposal defense!
Publications:
Shiwei Zeng, Jie Shen. Attribute-efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise, ICML 2023. [arxiv] [link]
Shiwei Zeng, Jie Shen. Semi-verified PAC Learning from the Crowd, AISTATS 2023. [arxiv] [link]
Shiwei Zeng, Jie Shen. List-Decodable Sparse Mean Estimation, NeurIPS 2022 [arxiv] [link]
Academic Services:
Conference Reviewer: IJCAI2021, IJCAI2022, ICML2022, ISIT2022, NeurIPS2022, ACML2022, AAAI2023, AISTATS2023, IJCAI2023, ICML2023, NeurIPS2023, AAAI2024, ICLR2024, IJCAI2024, ICML2024.
My Ph.D. Calendar:
May 2023 - Been selected for the Stevens Excellence Doctoral Fellowship for the 2023-24 academic year.
May 2023 - Passed the thesis proposal defense.
Apr 2023 - One paper studying robust learning sparse PTFs got accepted to ICML 2023.
Jan 2023 - One paper studying crowdsourced PAC learning got accepted to AISTATS 2023.
Sep 2022 - One paper studying robust sparse mean estimation got accepted to NeurIPS 2022. October: travel grant received.
May 2022 - One paper studying crowdsourced PAC learning got accepted to ICML 2022. June: travel grant received.
Feb 2022 - Received the Early-career AMS-NSF-Simons-ICM Travel Grant to participate in ICM2022 in Saint Petersburg. (ICM went virtual).
Research Seminar:
The machine learning theory seminar is paused for now.
Misc:
I enjoy dancing as a hobby, for which I was active in Hong Kong and New York City from 2013 to 2020. It teaches me hard-working is the key to any achievement.
Meanwhile, I play ultimate frisbee at Stevens Ultimate to keep myself physically active.