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Garrett T

- Research Program Mentor

PhD candidate at Stanford University


machine learning (especially reinforcement learning and meta-learning); robotics, Computer Science, reinforcement learning, AI/ML, deep learning, math


My academic interests are in machine learning, where we attempt to create algorithms that use data to improve predictions and decisions. I particularly focus on learning for sequential decision-making, which has applications in robotics, recommender systems, healthcare, and other areas. The goals of my research are to make more effective use of data and to make the learning process safer, and I primarily attempt to achieve these goals by employing predictive models. As a consequence, I am also interested in supervised learning topics such as uncertainty estimation and distribution shift, as well as transfer learning and meta-learning. Outside of research, I like to play soccer and volleyball to stay active. I also enjoy cooking and investing. In my spare time, I play some games on the Nintendo Switch (e.g. Super Smash Bros, Pokemon, Breath of the Wild).

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Exploring practical algorithmic choices in deep reinforcement learning

Despite recent successes in deep reinforcement learning, many techniques commonly used in the field (e.g. target networks, clipping, maximum entropy) are poorly understood. The project would experimentally probe the necessity of these tricks, and potentially explore other improvements.

Coding skills

Python, PyTorch, C++

Languages I know

elementary Spanish

Teaching experience

As Head Project TA for CS 229 (Machine Learning) at Stanford, I mentored many group projects over the course of a quarter. I have worked as a TA for years both as an undergrad and as a grad student. I also did 1-on-1 tutoring in high school.


Work experience

Microsoft Research (2021 - 2021)
Research Intern


University of California Berkeley (UC Berkeley)
BA Bachelor of Arts
Computer Science, Mathematics
Stanford University
PhD Doctor of Philosophy candidate
Machine learning

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