Alexander C. Li

I'm a first year PhD student in the Machine Learning Department at Carnegie Mellon University. I'm advised by Deepak Pathak, and my work is supported by the National Science Foundation Graduate Research Fellowship.

Previously, I was an electrical engineering and computer science major at UC Berkeley, where I received my BS and MS. I was a researcher in the Berkeley Artificial Intelligence Research Lab and was advised by Pieter Abbeel, Lerrel Pinto, and Carlos Florensa.

In high school, I also spent time at the Hansen Experimental Physics Laboratory, working with Yang Liu on computer vision algorithms for solar physics.

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I'm interested in developing robust, multi-task algorithms for reinforcement learning and unsupervised learning.

We present Generalized Hindsight: an approximate inverse reinforcement learning technique for relabeling behaviors with the right tasks. Given a behavior generated under one task, Generalized Hindsight finds a different task that the behavior is better suited for. Relabeling a trajectory with this different task and training with an off-policy RL algorithm improves sample-efficiency and asymptotic performance on a suite of multi-task navigation and manipulation tasks.

We develop a new hierarchical RL algorithm that can efficiently adapt pre-trained skills on related tasks, and directly learn effective emergent skills by simultaneously training the entire hierarchy.

We attempt to use powerful autoregressive models for image-to-image translation and outlier detection, with poor results. We analyze the failure modes and find that (a) differentiating through these models creates an ill-conditioned optimization problem and (b) their density estimates are incredibly sensitive to distributional shifts.

We develop a novel algorithm for estimating sunspot rotation speed that is more robust to feature evolution than traditional methods based on time-slices. We use this technique to gain more accurate estimates of magnetic energy buildup in rotating sunspots.

• National Science Foundation Graduate Research Fellowship (2020)
• 1st place at Citadel San Francisco Invitational Data Open (2019)
• Mark D. Weiser Excellence in Computing Scholarship (2019)
• Accel Scholar (2018)
• Quantedge Award for Academic Excellence: awarded to ~120 seniors at UC Berkeley for a 4.0 GPA (2018)
• Cal Alumni Association Leadership Award (2017)
• Dean's Honor List: Fall 2016, Spring 2017, Fall 2017, Spring 2018, Spring 2019
• Robert J. Kraft Award for Freshmen (2016)
• Regents’ and Chancellor’s Scholar: awarded to top <2% of entering students at Berkeley (2016)

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