Hello World!
Yang Li (李阳)
Applied Scientist @ AWS AI yangli95 AT cs.unc.edu Google Scholar
About Me
I am currently an Applied Scientist at AWS AI. Feel free to contact me if you are interested in an Intern job at Amazon.
I completed my Ph.D. at the Department of Computer Science at the University of North Carolina at Chapel Hill, advised by Professor Junier Oliva. Thanks to the committee members: Dr. Marc Niethammer, Dr. Mohit Bansal, Dr. Colin Raffel and Dr. Shahriar Nirjon.
During my time at UNC, I'm a member of LUPALAB led by Dr. Junier Oliva. Before joining LUPALAB, I worked with Dr. Dinggang Shen in IDEALAB.
Before coming to UNC, I received my B.Sc. degree in Biomedical Engineering from Beihang University in 2016. I worked closely with Dr. Yan Xu during my undergraduate period.
Research Interests
My research interests include machine learning, generative modeling, reinforcement learning, exchangeable data modeling, meta learning, adversarial learning, natural language processing, etc. Specifically, I focus on models that interact with its environment and user and reason with uncertainty.
Generative Models: capture distributions for tabular data, images, languages, sets, etc
Model-based Reinforcement Learning: leverage generative models for better decision making
Active Feature Acquisition: acquire the most informative features for cost-sensitive problems
Robustness: build robust model against adversarial attacks and out-of-distribution inputs
News
June 2022: I joined AWS AI Lab supervised by Xiaofei Ma
May 2021: Two papers got accepted to ICML2021
May 2021: Work done at Amazon got accepted in ICLR SDG Workshop
Feb 2021: Will join Adobe this summer
Sep 2020: Two papers got accepted to NeurIPS2020
Aug 2020: Completed the summer internship at Amazon
May 2020: Two papers got accepted to ICML2020
Feb 2020: Will join AWS AI Lab for internship this summer
Publications
Machine Learning:
Yang Li, Junier B. Oliva. Distribution Guided Active Feature Acquisition. 2022.
Yang Li, Gang Wu, Stefano Petrangeli, Viswanathan Swaminathan, Haoliang Wang, Ryan Rossi, Zhao Song, Junier B. Oliva. Actively Learned Context Model for Image and Burst Compression. 2021.
Yang Li, Siyuan Shan, Qin Liu, Junier B. Oliva. Towards Robust Active Feature Acquisition. ArXiv, 2021.
Siyuan Shan, Yang Li, Junier B. Oliva. NRTSI: Non-Recurrent Time Series Imputation. ArXiv, 2021.
Yang Li, Junier B. Oliva. Partially Observed Exchangeable Modeling. ICML, 2021.
Yang Li, Junier B. Oliva. Active Feature Acquisition with Generative Surrogate Models. ICML, 2021.
Yang Li, Junier B. Oliva. Dynamic Feature Acquisition with Arbitrary Conditional Flows. ArXiv, 2020.
Yang Li*, Haidong Yi*, Christopher M. Bender, Siyuan Shan, Junier B. Oliva. Exchangeable Neural ODE for Set Modeling. NeurIPS, 2020.
Siyuan Shan, Yang Li, Junier B. Oliva. Meta-Neighborhoods. NeurIPS, 2020.
Yang Li, Shoaib Akbar, Junier B. Oliva. ACFlow: Flow Models for Arbitrary Conditional Likelihoods. ICML. Vienna, Austria, 2020.
Christopher Bender, Yang Li, Yifeng Shi, Mike Reiter, Junier Oliva. Defense Through Diverse Directions. ICML. Vienna, Austria, 2020.
Yang Li, Tianxiang Gao, Junier B. Oliva. A Forest from the Trees: Generation through Neighborhoods. AAAI. New York, US, 2020.
Christopher M. Bender*, Kevin O'Connor*, Yang Li, Juan Jose Garcia, Manzil Zaheer, Junier B. Oliva. Exchangeable Generative Models with Flow Scans. AAAI. New York, US, 2020.
Natural Language Processing:
Yang Li, Ben Athiwaratkun, Cicero Nogueira dos Santos, Bing Xiang. Joint Text and Label Generation for Spoken Language Understanding. ICLR SDG Workshop, 2021.
Medical Image Analysis:
Lei Xiang*, Yang Li*, Weilin Lin, Qian Wang, and Dinggang Shen. Unpaired deep cross-modality synthesis with fast training. MICCAI Workshop. Granada, Spain, 2018.
Yan Xu, Yang Li, Yipei Wang, Mingyuan Liu, Yubo Fan, Maode Lai, Eric Chang. Gland instance segmentation using deep multichannel neural networks. IEEE Transactions on Biomedical Engineering, 64(12), 2901-2912.
Yan Xu, Yang Li, Mingyuan Liu, Yipei Wang, Yubo Fan, Maode Lai, and Eric Chang. Gland instance segmentation by deep multichannel side supervision. MICCAI. Athens, Greece, 2016.
Teaching Experience
UNC-Chapel Hill. Models of Language and Computation, Teaching Assistant, Fall 2018.
UNC-Chapel Hill. Advanced Machine Learning, Teaching Assistant, Spring 2020.
Professional Services
Reviewer: ECML-22, ICML-22, NeurIPS-22, UAI-22, NeurIPS-21, NeurIPS-19