Me
Jennifer Brennan
PhD Student
Allen School of Computer Science & Engineering
University of Washington
Computer Science & Engineering, Gates Center, Office 231

jrb at cs.washington.edu
Google Scholar | Resume

About

I am a fifth (and final!) year PhD student in Computer Science and Engineering at the University of Washington, advised by Kevin Jamieson. My research improves scientific experimentation using tools from experimental design and statistical machine learning. I am currently collaborating with scientists from the University of Pittsburgh to design sample-efficient experiments for the identification of promising antibiotic combinations. I have also worked on the analysis of pilot experiments, models for under-reported counts in the context of global health, and techniques for training memory-hungry deep learning models. During the fall of 2021 I interned at Google Research, working on problems related to causal inference and heterogeneous treatment effect estimation.

I am grateful to have been supported by an NSF Graduate Research Fellowship.


Preprints

Sample-Efficient Identification of High-Dimensional Antibiotic Synergy with the Normalized Diagonal Sampling Design, Jennifer Brennan, Lalit Jain, Sofia Garman, Ann E. Donnelly, Erik S. Wright, Kevin Jamieson. Under Review.

Analysis and Methods to Mitigate Effects of Under-reporting in Count Data, Jennifer Brennan, Marlena Bannick, Nicholas Kassebaum, Lauren Wilner, Azalea Thomson, Aleksandr Aravkin, Peng Zheng. Preprint


Publications

BAM: Bayes with Adaptive Memory, Josue Nassar, Jennifer Brennan, Ben Evans, Kendall Lowrey, ICLR 2022.

Dynamic Tensor Rematerialization, Marisa Kirisame, Steven Lyubomirsky, Altan Haan, Jennifer Brennan, Mike He, Jared Roesch, Tianqi Chen, Zachary Tatlock, ICLR 2021. Paper | Talk | Slides

Estimating the Number and Effect Sizes of Non-null Hypotheses, Jennifer Brennan, Ramya Korlakai Vinayak and Kevin Jamieson, ICML 2020. Paper | Talk | Slides

Reconciliation feasibility in the presence of gene duplication, loss, and coalescence with multiple individuals per species, Jennifer Rogers, Andrew Fishberg, Nora Youngs and Yi-Chieh Wu, BMC Bioinformatics, 2017. 18:292 Paper