Biyonka Liang

Harvard University / Department of Statistics

About Me

I am a Ph.D. Candidate in Statistics at Harvard University advised by Professor Lucas Janson in the Department of Statistics and Professor Iavor Bojinov in the Harvard Business School. My research interests include reinforcement learning, causal inference, and adaptive experimentation. I am gratefully supported by the NSF Graduate Research Fellowship. Prior to joining Harvard, I was a Data Scientist at Meta. I received my Bachelor's in Statistics from UC Berkeley, where I was awarded the 2019 Departmental Citation as the top graduating student in the statistics bachelor's program. During my Ph.D., I was a biostatistics intern at Moderna working on clinical trial planning, a research intern at Zuse Institute Berlin working on combinatorial optimization, and a statistical consultant at MDRC working on heterogenous treatment effect detection.

Working Papers and Publications

A Bayesian Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health

Liang, B., Xu, L., Taneja, A., Tambe, M., Janson, L. (2024)

arXiv

An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

Liang, B., Bojinov, I. (2023)

arXiv

Powerful Partial Conjunction Hypothesis Testing via Conditioning

Liang, B., Zhang, L., Janson, L. (2022)

arXiv

Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology

Wu, S., Sánchez, H., Henry, J., Citron, D., Zhang, Q., Compton, K., Liang, B., et al. (2020)

PLoS Computational Biology, Volume 16(4), e1007446

DOI

Conference Presentations and Talks

"An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits". Talk at the 2023 Conference on Digital Experimentation @ MIT.
"Powerful Partial Conjunction Hypothesis Testing via Conditioning". Poster presentation at the 2023 Joint Statistical Meetings.
"Network Analysis of Mosquito Habitats for Controlling Vector-Borne Pathogens". Poster presentation at the 2018 International Conference for Network Science.
"MICRO: An Eco-epidemiological Agent-based Framework for the Modeling of Mosquito-borne Pathogens". Talk at the 2017 NorCal CompBio Symposium.

Honors and Awards

American Statistical Association Gertrude M. Cox Scholarship, Honorable Mention, 2022
Harvard University Certificate of Distinction and Excellence in Teaching, 2021, 2022
National Science Foundation Graduate Research Fellowship Recipient, 2020
Citadel Data Open, Summer Invitational, First Place, 2019

Teaching

Stat170: Stochastic Processes, Harvard University, 2022
Stat211: Statistical Inference (graduate-level), Harvard University, 2021
Stat140: Probability for Data Science, University of California, Berkeley, 2018-19
Stat134: Concepts of Probability, University of California, Berkeley, 2018

Contact

Email: biyonka@g.harvard.edu
1 Oxford St, Cambridge, MA 02143
CV Google Scholar Github

Misc

Outside of academics, I love to figure skate, ski, and sing. I was fortunate to be a member of the Radcliffe Choral Society from 2020-21. I was a part of the amazing team of faculty, students, and staff who helped found Harvard's Data Adventure Day, an event designed to promote statistics and data science to high school student through hands-on activities and interactions, with a focus on supporting diversity and inclusion in these fields.