About Me

I am currently a PhD student in Computer Science at Princeton University, advised by Jason Lee.

I have previously studied at the University of California, Berkeley, where I received my degree in Electrical Engineering and Computer Sciences. During my time at Berkeley, I was an undergraduate researcher in Prof. Sergey Levine's lab, where I worked on model-based reinforcement learning together with Roberto Calandra and Rowan McAllister. I have also been involved with Facebook AI Research as a research intern.

I am broadly interested in exploring theoretical machine learning and deep learning, and understanding how insights from these areas could be leveraged to both better understand existing learning algorithms and drive further developments.

You may reach me at kchua (at) princeton (dot) edu.

Publications

• Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models.
  arXiv | website | code
  Kurtland Chua, Roberto Calandra, Rowan McAllister, Sergey Levine.
  NeurIPS 2018 (Spotlight presentation, ~4% of submitted papers).

Talks

• “Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models.” Bay Area Machine Learning Symposium (Baylearn). October 2018.
  video

Teaching

• EECS 126: Probability and Random Processes
  Undergraduate Student Instructor (uGSI)
  Spring 2019 | Fall 2018

Honors and Awards

• National Science Foundation Graduate Research Fellowship (2019).
• Gordon Y.S. Wu Fellowship in Engineering (2019).
• EECS Major Citation (2019).
• UC Berkeley EECS Honors Program (2019). Pursuing a concentration in Mathematics.
• NVIDIA Pioneer Award (2018). Awarded for Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models at NeurIPS 2018.
• Phi Beta Kappa Honors Society (2018). Inducted as a junior.
• Dean’s Honors List for Fall ‘15, Spring ‘16, Fall ‘16, Spring ‘17, Spring ‘18, Fall ‘18.
• Quantedge Award for Academic Excellence (2018). Awarded to students of senior standing with a 4.0 GPA.