Research Interests

My current interests include: ML and optimization, Bayesian inference, deep learning, GPs and uncertainty quantification, adaptive experiment design, ML for physics/mechanics, computational biology, AI for education. Please see my CV for more information on my past and ongoing research projects, as these have informed my current interests in no small way.

Publications and Technical Reports

Learning Region of Interest for Bayesian Optimization with Adaptive Level-Set Estimation
Fengxue Zhang, Jialin Song, James Bowden, Alexander Ladd, Yisong Yue, Thomas Desautels, Yuxin Chen
[pdf] [poster]
ICML 2022, Workshop on Adaptive Experimental Design and Active Learning in the Real World (ReALML)

Deep Kernel Bayesian Optimization
James Bowden, Jialin Song, Yuxin Chen, Yisong Yue, Thomas Desautels
[pdf] [talk]
Pre-print 2021

Bridge-Group: An Opt-In Recitation Section to Facilitate the Transition from CS1 to CS2
Emma Gurcan, James Bowden, Adam Blank
[poster]
RESPECT 2022