Haipeng Chen

Email: hpchen@seas.harvard.edu; haipengkeepon@gmail.com

Haipeng Chen is a CRCS postdoctoral fellow at Harvard University from July 2020, working with Professor Milind Tambe . Previously he did his first postdoc in the Department of Computer Science, Dartmouth College, where he worked with Professor V.S. Subrahmanian. He obtained his PhD from Interdisciplinary Graduate School (IGS), Nanyang Technological University (NTU) in 2018, where he was advised by Professor Bo An. He got the B.S. in Physics from University of Science and Technology of China (USTC) in 2013.

His research focuses on using AI for social impact. For AI techniques, he is interested in prediction and optimization (reinforcement learning; discrete optimization). For social domains, he works on public health, cybersecurity, and transportation. His research has been recognized with the best paper nomination at AAMAS-2021, Innovation Demonstration Award runner-up at IJCAI-2019, Champion of the 2017 Microsoft Malmo Collaborative AI Challenge, and finalist of the Reinforcement Learning Competition track at KDD-2019. He has published multiple papers in top conferences such as AAAI, IJCAI, NeurIPS, AAMAS, UAI, KDD, ICDM, and top journals (e.g., IEEE/ACM Transactions, Transportation Research). He served as co-chair for multiple workshops that are at the intersection of AI and social impact, including ICLR-2021 workshop on Synthetic Data Generation: Quality, Privacy, Bias, IJCAI-2021 workshop on AI for Social Good, and Harvard CRCS workshop on Using AI for Social Good. He also served as TPC member for top AI conferences such as AAAI, IJCAI, AAMAS, NeurIPS, ICLR, and ICML. He has collaborated with non-profit organizations such as The Family Van, Mobile Health Map, Safe Place for Youth. His past work has been covered by media such as The Wall Street Journal, Scientific American, Digital Guardian, ScienceBlog, AAAS, 雷锋网, and 凤凰网.

Contacts

News

  • September, 2021 - Our paper "Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Problems by Reinforcement Learning" is accepted by NeurIPS-21 as a spotlight!
  • September, 2021 - Our paper "PCAM: Predictive Cyber Alert Management" is accepted by ACM Transactions on Internet Technology!
  • August, 2021 - I am co-organizing the 3rd Workshop on Artificial Intelligence for Social Good@IJCAI2021.
  • May, 2021 - I am co-organizing the Synthetic Data Generation: Quality, Privacy, Bias workshop @ICLR2021.
  • May, 2021 - Two papers are accepted by UAI-21!
  • May, 2021 - Our paper, 'Active Screening for Recurrent Diseases: A Reinforcement Learning Approach' is awarded the best paper nomination by AAMAS-21!
  • March, 2021 - Our workshop proposal, 'International Workshop on Artificial Intelligence for Social Good (AI4SG)' is accepted by IJCAI'2021!
  • December, 2020 - Our paper, 'Active Screening for Recurrent Diseases: A Reinforcement Learning Approach' is accepted by AAMAS'2021!
  • December, 2020 - Our workshop proposal, 'Synthetic Data Generation: Quality, Privacy, Bias' is accepted by ICLR'2021 workshops!
  • December, 2020 - Our paper, 'EvaLDA: Efficient Evasion Attacks Towards Latent Dirichlet Allocation' is accepted by AAAI'2021!

Publication

C=Conference, J=Journal, D=Demo, W=Workshop, A=Arxiv, P=Patent



Awards

Professional Service