Will present AC-DC at the Draper Scholars Research Symposium 2026.
ROBIN INHO KEE · UNIVERSITY OF MICHIGAN ROBOTICS
Robot teams that reason, communicate, and predict.
I am a Ph.D. student in Robotics at the University of Michigan. I work on practical multi-robot autonomy, with a focus on selective communication, mission-aware reasoning, and prediction-guided execution.
Multi-Robot Autonomy · Communication-Aware Coordination · Learning-Enabled Control
RECENT NEWS
Started serving as a Graduate Student Instructor for AEROSP 740: Online Learning for Single- and Multi-Agent Control at the University of Michigan.
Started my Ph.D. in Robotics at the University of Michigan.
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Presented our work on safe adaptive cruise control at IEEE CCTA 2025 in San Diego.
Served as a conference volunteer at L4DC 2025 at the University of Michigan.
Paper Time Shift Governor-Guided MPC with Collision Cone CBFs for Safe Adaptive Cruise Control in Dynamic Environments accepted to IEEE CCTA 2025.
Paper Learning to Refine Input Constrained Control Barrier Functions via Uncertainty-Aware Online Parameter Adaptation appeared at IEEE ICRA 2025.
Selected as a Draper Scholar through the Draper Scholars Program on Autonomy.
Admitted to the Ph.D. program in Robotics at the University of Michigan.
Paper Constrained Control for Autonomous Spacecraft Rendezvous: Learning-Based Time Shift Governor appeared at AIAA SciTech 2025.
Completed my M.S. in Mechanical Engineering at the University of Michigan.
Paper Disentangled Prototypical Convolutional Network for Few-Shot Learning in In-Vehicle Noise Classification published in IEEE Access.
RESEARCH FOCUS
Selective communication, mission-aware reasoning, and prediction-guided execution.
Selective communication
Prioritize useful information across the team: who should communicate, when, and what should be exchanged.
Mission-aware reasoning
Connect observations and mission context to the information and decisions that matter for the team.
Prediction-guided execution
Compare candidate actions using predicted downstream communication, task, and risk outcomes.
SELECTED WORK
Research foundations already in place.
Adaptive Communication for Scalable Dynamic Average Consensus
Each robot adapts who to communicate with, when, and what state block to exchange.
Project page →
Online Adaptive Input Constrained Control Barrier Functions
Learning-based online adaptation of ICCBF parameters with uncertainty-aware verification.
Project page →Online Adaptive Control Barrier Functions
Query and validate CBF parameters online under epistemic and aleatoric uncertainty.
Project page →ABOUT
Building toward practical autonomy systems.
I am a Ph.D. student in Robotics at the University of Michigan, working on multi-robot autonomy, communication-aware coordination, and learning-enabled control. My research connects selective communication, mission-aware reasoning, prediction-guided action, and real robotic systems.
I am advised by Prof. Vasileios Tzoumas and Prof. Necmiye Ozay at the University of Michigan. Through the Draper Scholars Program, I am also advised by Dr. Begum Cannataro at Charles Stark Draper Laboratory. Before my Ph.D., I worked on learning-enabled safety-critical control at Michigan and on wearable assistive robots at KIST.
Outside research, I enjoy weightlifting and listening to music.