Haimin_24_2

Curriculum Vitae

Google Scholar

Research Statement

JHU Profile

GitHub

Contact: haimin@cs.jhu.edu

 

Hello and welcome! I am an incoming Assistant Professor at JHU CS. I obtained a Ph.D. in Electrical and Computer Engineering from Princeton University, where I was advised by Jaime Fernández Fisac, and worked closely with Naomi Ehrich Leonard, Bartolomeo Stellato, and Andrea Bajcsy. My research aims at enabling safe human-centered robotic systems that can be built, deployed, and verified. Towards this goal I work on new algorithms and theorems centered around dynamic game theory, integrating insights from robust optimal control, machine learning, and numerical optimization. I ground my work in real-world robotic and cyber-physical systems such as miniature autonomous vehicles, quadrupedal robots, AI-assisted race cars, and quadrotors. My work has been recognized with several honors such as the RSS Pioneer, HRI Pioneer, and CPS Rising Star.

🚀 I am hiring PhD students and summer interns. Please feel free to contact me if you are interested in working with me!

Full bio

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Research Statement

Autonomous robots are becoming more versatile and widespread in our daily lives. From autonomous vehicles to companion robots for senior care, these human-centric systems must demonstrate a high degree of reliability in order to build trust and, ultimately, deliver social value. How safe is safe enough for robots to be wholeheartedly trusted by society? Is it sufficient if an autonomous vehicle can avoid hitting a fallen cyclist 99.9% of the time? What if this rate can only be achieved by the vehicle always stopping and waiting for the human to move out of the way?

My vision is to enable human-centered robotic systems that can be built, deployed, and verified with safety assurances under minimal performance loss. Towards this goal, my research focuses on interactive motion planning in the joint space of physical and information states (e.g., beliefs), actively ensuring safety and improving efficiency as robots autonomously navigate uncertain environments and interact with people. The key thrusts of my research include:

Scalable game-theoretic decision-making

Planning while accounting for strategic interactions among many agents is hard, especially with uncertainties induced by learning components and indecisions! My solver draws insights from mixed-integer optimization, machine learning, and bifurcation theory, and runs in real-time for teamed robots on the ground and in the air.

Safe and performant human-robot interaction

Robots will be everywhere. How can we trust them to be safe and performant around people? My work showed that by planning and safeguarding in the joint space of physical and information states (generally, we call them doxo-physical states), we can ensure safety and maintain efficiency for human-robot interaction.

Verifiable neural safety analysis

Computing a safety-assured controller is a fundamental open problem for robots with high-dimensional, nonlinear dynamics. I pioneered algorithms that learn robust neural controllers with theoretical guarantees on their training-time convergence and deployment-time safety.

Please explore my complete list of publications here. Here is my research statement:

Research Statement – Haimin HuDownload

Education

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Aug. 2020 – Aug. 2025, Electrical and Computer Engineering, Princeton University

Master of Arts,
Doctor of Philosophy.

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Aug. 2018 – May 2020, Electrical Engineering, University of Pennsylvania

Master of Science in Engineering.

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Sep. 2014 – July 2018, Electronic and Information Engineering, ShanghaiTech University

Bachelor of Engineering (with high honors).

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Aug. 2017 – June 2018, Electrical Engineering and Computer Sciences, University of California, Berkeley

Exchange Student.

Publications

I regularly publish in the following peer-reviewed journals and conference proceedings:

    • Conferences: RSS, WAFR, CoRL, ICRA, CDC, ACC
    • Journals: IJRR, IEEE RA-L, IEEE TAC, ARCRAS

Please visit here for my publications. Here is my Google Scholar.