James Alan Preiss

learning, control, robotics

g-scholar | github | linkedin | arxiv

I am a postdoctoral scholar in the Department of Computing + Mathematical Sciences at Caltech, where I am co-advised by Yisong Yue, Soon-Jo Chung, and Adam Wierman. I completed my Ph.D. with Prof. Gaurav Sukhatme at the USC Robotic Embedded Systems Lab (RESL).

I am interested in robotics, machine learning, control theory, optimization, and their intersections — both theoretical and practical. Recent projects include regret bounds for online controller selection, policy gradient reinforcement learning theory, combining deep dynamics models with traditional control, and developing the framework of suboptimal covering numbers to quantify the "size" of infinite sets of optimal control tasks.

Earlier projects include trajectory optimization hardness analysis, empirical projects in RL, multi-robot motion planning, and co-developing/maintaining the Crazyswarm platform for multi-quadrotor research with Wolfgang Hönig.

Before starting my Ph.D., I developed software for 3d scanning at Geomagic and interactive statistics at the JMP division of SAS Institute. I completed a B.S. in Mathematics and B.A. in Photography at The Evergreen State College in Olympia, WA.

This page last updated January 2023.


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Ph.D. Dissertation

Characterizing and Improving Robot Learning: A Control-Theoretic Perspective.
James A. Preiss.
University of Southern California, 2022. [pdf]



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