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• For PhD applicants, please apply to the CS PhD program at Northwestern by December 1st and list my name on your application.
• For postdocs/research interns, please fill out this form: application form.
• Owing to the high volume of inquiries, I may not be able to respond individually.
• I collaborate with Manling Li at Northwestern, who is an amazing researcher and mentor. You can also consider applying for her lab.

Research Mission
My research “North Star” is to create embodied AI systems that augment human physical and cognitive capabilities. My work spans robot hardware, robot learning, human-robot interaction, brain-computer interfaces, cognitive science, the societal impact of AI and automation, and AI for art and design. Examples:

• Can we build search-and-rescue robots that save lives in natural disasters?
• Can we create robotic “experts” in art and sports, including painting, dancing, climbing, or playing soccer?
• Can we design robots that care for us when we are ill, when we grow old, or when we are far from our loved ones?

When reaching out, a great way to start our conversation is by sharing your vision for “building a robotic system that can do X,” where X is something you are genuinely passionate about. If we work together, I will do my best to support you with the resources and guidance needed to bring your vision to life.

Past and Ongoing Research

My research is structured around three pillars: human tasks, human data, and human interfaces. I have co-led the development of a comprehensive robotic benchmark, BEHAVIOR (see also BVS and EAI), to simulate the 1,000 most essential household tasks, identified through large-scale survey studies, in virtual, interactive, and ecologically realistic environments. To achieve human-level AI in solving these tasks, we design systems and learning algorithms that enable AI and robots to learn from large-scale, diverse human data collected through novel interfaces, see BRS, DexCap, MimicPlay, TRANSIC, SEED, Atari-HEAD, and CoM. To augment human capabilities and enable seamless interaction, we have developed intelligent brain-robot interfaces to assist older adults, individuals with disabilities, and those receiving hospital care with activities of daily living, see NOIR-EEG and NOIR-EEGv2. In addition to these, we aim to enhance the generalization capabilities of learning-based robotic systems for everyday tasks by leveraging foundation models, see VoxPoser, ReKep UAD, and Digital Cousins. Meanwhile, we are developing specialized robotic systems that match human capabilities in domains such as painting, dancing, cooking, and sports, through the integration of learned world models and motion planning algorithms.

My past work has received several paper awards or nominations from robotics conferences and workshops, including two CoRL best paper nominations (2022, 2023), ICRA best paper (2024), best paper nomination (2025), and multiple awards/oral/spotlight at CoRL, RSS, ICRA, CVPR, NeurIPS, AAAI, and their workshops. I also publish in major machine learning conferences and cognitive science journals such as Neural Computation and PLoS Computational Biology.

Mentoring Philosophy

I attended a liberal arts college, where small class sizes and a strong focus on teaching fostered critical thinking, creativity, and intellectual curiosity. Close student-faculty interactions created an environment for personalized learning, ensuring individualized attention and support. This approach encouraged exploration across disciplines, nurturing individuals who are prepared not only for specific jobs but also for lifelong learning and civic engagement. I was fortunate to be advised by Professor Dana Ballard and Mary Hayhoe during my PhD, where I learned that research freedom is the greatest gift a mentor can give, allowing students the freedom to pursue their intellectual curiosity. They taught me the importance of being patient, supportive, and a good listener. As a postdoc with Professor Fei-Fei Li and Jiajun Wu, I developed practical skills for applying these ideas in a larger, fast-paced lab. Supporting many students while fostering their growth is challenging, but I have learned how to be a leader and a mentor, and how to conduct high-quality, impactful research. I gained skills in seeking research resources, creating long-term research plans for my students and the lab, coordinating research teams, and managing a large research lab.

I have closely advised 38 students (for over six months each, with weekly 1:1 meetings), including 23 graduate and 15 undergraduate students. I have helped 13 students gain admission to top PhD programs like Stanford and MIT, with 3 more applying this year. I build teams from various academic departments and backgrounds. The students I advise come from a variety of academic disciplines, including computer science, electrical engineering, mechanical engineering, neuroscience, psychology, civil engineering, and economics. My mentoring style closely follows the principles I value: engaging closely with students, encouraging exploration and learning, and remaining patient and supportive throughout their journeys.

About Northwestern and Chicago

• Northwestern University is a top university in the United States, consistently ranking in the top 10 in the US and top 30 worldwide.
• Northwestern has very strong robotics research programs. See our Center for Robotics and Biosystems.
• Our research should strive for real-world applications and impact. For career development, Chicago offers abundant opportunities to apply your research to solve real-world problems.
• Located in Evanston, part of Chicago's northern suburbs (~30-minute commute), it offers a safe and nice living environment. The school is extremely beautiful, with two private beaches for faculty and students. For those who like the convenience of a big city but want less of the hustle and noise and danger, Northwestern is definitely one of the best choices.
• Chicago has some of the world’s best art museums, Broadway shows, ballet companies, comedy clubs, sports teams, and restaurants. It is fun to explore these while you are in grad school!