I am generally interested in unfolding consequences of design choices in machine learning pipelines (e.g. model assumptions, inductive biases, inference, optimization and model explanations) for social-technical decision making systems. I am also broadly interested in issues of AI safety, ethics and regulation. My interests include uncertainty quantification, deep generative models, deep Bayesian models, approximate inference, user modeling in RL, explanable AI and HCI.

Recent Work

More publications can be found at my Google Scholar.

  1. Eura Shin, Siddharth Swaroop, Weiwei Pan, Susan Murphy, Finale Doshi-Velez, Modeling Mobile Health Users as Reinforcement Learning Agents, AAAI Workshop on AI For Behavior Change, 2023.
  2. Zixi Chen, Varshini Subhash, Marton Havasi, Weiwei Pan, Finale Doshi-Velez, What Makes a Good Explanation?: A Harmonized View of Properties of Explanations, Neurips Workshop on Progress and Challenges in Building Trustworthy Embodied AI, 2022.
  3. Ziyan Zhu, Marios Mattheakis, Weiwei Pan, Efthimios Kaxiras, HubbardNet: Efficient Predictions of the Bose-Hubbard Model Spectrum with Deep Neural Networks, Neurips Workshop on Machine Learning and the Physical Sciences, 2022.
  4. Jiayu Yao, Yaniv Yacoby, Beau Coker, Weiwei Pan, Finale Doshi-Velez, An Empirical Analysis of the Advantages of Finite vs. Infinite Width Bayesian Neural Networks, Neurips Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems, 2022.
  5. Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez, Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables, JMLR, 2022.
  6. Jiayu Yao, Sonali Parbhoo, Weiwei Pan, Finale Doshi-Velez, Policy Optimization with Sparse Global Contrastive Explanations, ICML Workshop on Interpretable Machine Learning in Healthcare, 2022
  7. Mark Penrod, Harrison Termotto, Varshini Reddy, Jiayu Yao, Finale Doshi-Velez, Weiwei Pan, Success of Uncertainty-Aware Deep Models Depends on Data Manifold Geometry, ICML Workshop on Responsible Decision Making in Dynamic Environments, 2022
  8. Xin Zheng, Jiayu Yao, Finale Doshi-Velez, Weiwei Pan, From Soft Trees to Hard Trees: Gains and Losses, ICML Workshop on Responsible Decision Making in Dynamic Environments, 2022
  9. Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez, Wide Mean-Field Variational Bayesian Neural Networks Ignore the Data, Artificial Intelligence and Statistics (AIStats), 2022
  10. Anita Mahinpei, Justin Clark, Isaac Lage, Finale Doshi-Velez, Weiwei Pan, The Promises and Pitfalls of Black-box Concept Learning Models, ICML Workshop on Theoretic Foundation, Criticism, and Application Trend of Explainable AI, 2021
  11. Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan Murphy, Finale Doshi-Velez, Power-Constrained Bandit, Machine Learning for Health Care (MLHC), 2021
  12. Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Fiete, Efficient Online Inference for Nonparametric Mixture Models, Uncertainty in Artificial Intelligence (UAI), 2021