Isaac is a PhD student in the Aeronautics & Astronautics Department. He was also an undergraduate at UW majoring in electrical engineering, specializing in control systems. Previously he was a member of UW’s Formula SAE team where he brought up both hardware and firmware. From there, he interned at Apple on their iPhone hardware org for several months, working primarily on power integrity and test automation.
His research focuses on combining techniques from control theory and machine learning to better human interactions and reasoning and design robot decision-making algorithms that enable safe and trustworthy human-robot interactions.
Outside of school, he enjoys cooking, reading, weightlifting, and hiking.
Isaac is a recipient of the Amazon AI PhD fellowship (2025-2027).
Publications
MISFIT-V: Misaligned Image Synthesis and Fusion using Information from Thermal and Visual
Detecting humans from airborne visual and thermal imagery is a fundamental challenge for Wilderness Search-and-Rescue (WiSAR) teams, who must perform this function accurately in the face of immense pressure. The ability to fuse these two sensor modalities can potentially reduce the cognitive load on human operators and/or improve the effectiveness of computer vision object detection models. However, the fusion task is particularly challenging in the context of WiSAR due to hardware limitations and extreme environmental factors. This work presents Misaligned Image Synthesis and Fusion using Information from Thermal and Visual (MISFIT-V), a novel two-pronged unsupervised deep learning approach that utilizes a Generative Adversarial Network (GAN) and a cross-attention mechanism to capture the most relevant features from each modality. Experimental results show MISFIT-V offers enhanced robustness against misalignment and poor lighting/thermal environmental conditions compared to existing visual-thermal image fusion methods.
@inproceedings{ChauhanRemyEtAl2023,author={Chauhan, A. and Remy, I. and Broyles, D. and Leung, K.},title={{{MISFIT-V}: Misaligned Image Synthesis and Fusion using Information from Thermal and Visual}},year={2023},arxiv={2309.13216},category={afsl},img={ChauhanRemyEtAl2023.png},note={(submitted)},keywords={preprint},owner={karenl7}}
Semantically-Driven Object Search Using Partially Observed 3D Scene Graphs
@inproceedings{RemyGuptaEtAl2024,author={Remy, I. and Gupta, A. and Leung, K.},title={{Semantically-Driven Object Search Using Partially Observed {3D} Scene Graphs}},year={2024},img={RemyGuptaEtAl2024.png},note={(preprint)},keywords={preprint},owner={karenl7}}
Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions
From autonomous driving to package delivery, ensuring safe yet efficient multi-agent interaction is challenging as the interaction dynamics are influenced by hard-to-model factors such as social norms and contextual cues. Understanding these influences can aid in the design and evaluation of socially-aware autonomous agents whose behaviors are aligned with human values. In this work, we seek to codify factors governing safe multi-agent interactions via the lens of responsibility, i.e., an agent’s willingness to deviate from their desired control to accommodate safe interaction with others. Specifically, we propose a data-driven modeling approach based on control barrier functions and differentiable optimization that efficiently learns agents’ responsibility allocation from data. We demonstrate on synthetic and real-world datasets that we can obtain an interpretable and quantitative understanding of how much agents adjust their behavior to ensure the safety of others given their current environment.
@inproceedings{RemyFridovichKeilEtAl2025,author={Remy, I. and Fridovich-Keil, D. and Leung, K.},booktitle={{American Control Conference}},title={{Learning responsibility allocations for multi-agent interactions: A differentiable optimization approach with control barrier functions}},year={2025},arxiv={2410.07409},category={structure},img={RemyFridovichKeilEtAl2024.png},selected={true},keywords={in print},owner={karenl7}}
