Junxuan (Helen) Shen

Hi! My name is Junxuan. I am a third-year PhD student in EECS at MIT, and I am fortunate to be advised by Professor Yilun Du. My research interests lie at the intersection of generative modeling, robot learning, and planning. I am particularly interested in developing novel methods that enable robots to robustly generalize to new tasks, environments, and problem structures beyond those encountered during training.

I received a Master of Science degree in EECS from MIT, where I was advised by Professor Thodoris Lykouris and worked on principled algorithms for sequential decision-making under uncertainty, with applications in sequential experiments and queueing systems.

Before joining MIT, I graduated from Caltech in 2024 with a Bachelor of Science degree in computer science and mathematics, where I was fortunate to be mentored by Professors Adam Wierman, Guannan Qu, Nicolas Christianson, and Adam Sheffer, and explored research topics including metrical task systems with ML predictions, control+learning, and extremal combinatorics.