Jake Gonzales
Hi! I'm a PhD student in the Department of Electrical and Computer Engineering at the University of Washington where I am advised by Prof. Behçet Açıkmeşe and Prof. Lillian Ratliff. I am also a member of the Autonomous Controls Lab. I am fortunate to be supported by the NSF Graduate Research Fellowship and previously an Amazon PhD Fellowship.
My research focuses on decision-making in multi-agent interactions, using tools from control theory, machine learning, optimization, uncertainty quantification, and game theory. I am interested in developing theory and principled algorithms that enable autonomous agents to interact safely and efficiently in uncertain, real-world environments.
Previously, I did my undergrad in ECE at the University of New Mexico, where I did undergrad research in the Human-Centered Systems and Control Lab and was supervised by Prof. Meeko Oishi. My research was in data-driven control and stochastic optimal control. I'm intersted in theory and algorithms for practical applications, so I have spent time doing internships at Sandia National Labs and MIT Lincoln Labs.
Github
G. Scholar
LinkedIn
CV
jakegonz [at] uw [dot] edu

news
- June 2025 I attended the first ever YC AI Startup School in San Francisco!
- June 2025 I started an internship as an Applied Scientist at Amazon Robotics in Greater Boston.
- May 2025 I passed my qualifying exam!

Safe Probabilistic Planning in Human-Robot Interaction using Conformal Risk Control
Jake Gonzales, Kazuki Mizuta, Karen Leung*, Lillian Ratliff*
*Equal advising
Submitted to IROS 2025
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Hierarchical Decision Framework for Multi-Agent Path Finding
Jake Gonzales, Joey Sullivan, Samuel Burden, Lillian Ratliff, Daniel Calderone
In Preperation
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How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systems
Oswin So, Zachary Serlin, Makai Mann, Jake Gonzales, Kwesi Rutledge, Nicholas Roy, Chuchu Fan
International Conference on Robotics and Automation (ICRA) 2024
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Data-Driven Stochastic Optimal Control Using Kernel Gradients
Adam J. Thorpe, Jake A. Gonzales, Meeko MK Oishi
American Control Conference, 2023
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Advancing Model Credibility for Linked Multi-Physics Surrogate Models within a Coupled Digital Engineering Workflow of Nuclear Deterrence Systems
Sofie W. Schunk, Shane McMurray, Jake A. Gonzales
Model Validation and Uncertainty Quantification, Volume 3, Proceedings of the 41st IMAC, 2023
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Visualization of MBSE Datasets in an Interactive 3D Game Engine
Kelsey Wilson, Ruby Ta, Jake Gonzales, Seethamble S. Mani, Casey Noll, Wesley Krueger, William Gruner, Timothy Wisley
Western States Regional Conference INCOSE, 2022
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EE406 Teaching EngineeringTeaching Assistant
In this course students learn evidence-based learning techniques for teaching STEM related topics such as active and inductive learning. This course teaches prospective engineers how to teach engineering. I taught a lesson, lead discussions, graded homework and final projects, and providing feedback on assignments and projects.
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EE238 Computer Logic DesignTeaching Assistant
A course on digital logic and computer organization with topics including: number systems, Boolean algebra, K-maps, combinational/sequential circuits, VHDL coding, ALUs, memory systems, computer architecture, I/O systems, microprocessor basics. I led lab sessions where students completed coding assignments related to these topics. Graded work, gave lectures, and held office hours.
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ECE101 Intro. to ECETeaching Assistant
Due to the COVID-19 pandemic, I gave lectures for this course online on topcis related to electrical engineering basics and MATLAB design basics.
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Mentor, Prisons Mathematics Project
I'm mentoring an inmate through the Prison Mathematics Project. We send letters back and forth discussing math ranging all sorts of different topcis. I began tutoring him in undergrad level math such as linear algebra and Diff. Eq., and now we are learning more advanced topics such as game theory.
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Research Mentor, UW/Tesla HS
Serving as a mentor for two students from Tesla High School who are doing research on using Bayesian neural networks and other ML methods for mecury pollution prediction in aquatic ecosystems.
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Chess Coach, Learners Chess Academy
I taught chess at elementary and middle schools local to Albuquerque, NM spanning many grades from K-8. I also volunteered for summer chess events.