Weiwei Pan


Data Science Graduate Program Advisor, Harvard University

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I’m the Data Science Graduate Program Advisor at the Institute of Applied Computational Sciences at Harvard University. I’m also a machine learning researcher in the Data to Actionable Knowledge (DtAK) lab. I am interested in building models with guaranteed properties that align with task-specific desiderata, such as interpretability, risk-awareness, satisfaction of domain-specific constraints.

In a former life, I did research in pure math (specifically algebraic topology) and was an Assistant Professor of Mathematics at Saint Mary’s College of California.

Recent Work

  1. Zixi Chen, Varshini Subhash, Marton Havasi, Weiwei Pan, Finale Doshi-Velez, A Unifying View of Properties of Machine Learning Explanations, Neurips Workshop on Progress and Challenges in Building Trustworthy Embodied AI, 2022.
  2. 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.
  3. 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.
  4. Yaniv Yacoby, Weiwei Pan, Finale Doshi-Velez, Mitigating the Effects of Non-Identifiability on Inference for Bayesian Neural Networks with Latent Variables, JMLR, 2022.
  5. 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
  6. 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
  7. 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
  8. 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
  9. Jiayu Yao, Emma Brunskill, Weiwei Pan, Susan Murphy, Finale Doshi-Velez, Power-Constrained Bandit, Machine Learning for Health Care (MLHC), 2021
  10. Rylan Schaeffer, Blake Bordelon, Mikail Khona, Weiwei Pan, Ila Fiete, Efficient Online Inference for Nonparametric Mixture Models, Uncertainty in Artificial Intelligence (UAI), 2021

Recent Courses

I teach undergraduate and graduate courses in data science and machine learning. I also supervise undergraduate and graduate research. Students interested in research opportunities should reach out directly to me.

AC297r Computational Science and Engineering Capstone Project, Fall
AM207 Advanced Scientific Computing: Stochastic Optimization Methods, Fall 2019-2021
DSC6232 Machine Learning and Computational Statistics at the University of Rwanda, Summer 2019-2021
Workshop Data Science Workshop at the University of Rwanda, Summer 2019
AC298r Diversity, Inclusion and Leadership in Tech, Fall
AC299r Directed Graduate Research, Spring
AM91r Directed Undergraduate Research, Spring

Outreach & Community Building

Since 2018, I’ve been organizing the data science workshop for the annual Women in Data Science Cambridge (WiDS) conference: WiDS Datathon Workshop 2022. Since 2021, I’ve served as the co-director of the Worldwide WiDS Datathon.

I am the organizer of IACS’s Data Science Pedagogy Winter Workshop for educators of underrepresented college students in data science. I am also the faculty advisor of the IACS Graduate Advisory Committee and the facilitator of the IACS Diversity, Inclusion, Leadership Reading Group.

I’m the faculty mentor of the IACS PhD Working Group, a working group for IACS students who are interested in receiving support and mentorship through their PhD application process. Sign up for the 2022 PhD Working Group. Recently, I have also begun serving as a mentor in the Career Development program at DataPoint Armenia.


Fall 2022 Capstone Office Hours

Fall 2022 Open Office Hours

Note for Advisees: During the Fall semester, please prioritize using my open office hours to address your questions. My responses to emails will be slow. If you want to reach out via email with advising questions, please preface the email subject with “[ADVISING]”; I may very well miss advising emails without this preface in the subject.

weiweipan (at) g (dot) harvard (dot) edu

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