About me

My name is Yifan Zhu, and I am a postdoctoral research scholar at the Yale GRAB Lab, advised by Prof. Aaron Dollar. Previously, I obtained a Ph.D. at the Computer Science department at the University of Illinois at Urbana-Champaign, where I was a member of the Intelligent Motion Lab and advised by Prof. Kris Hauser on robotics. You are also welcome to check out my old research page on the lab website.

My research vision is to develop fundamental technologies that enable robots to understand their contacts with the external world from proactive interactions and perform meaningful tasks. My prior research lies at the intersection of physics modeling, optimization, machine learning, hardware design. I aim to develop representations for robots that facilitate tight integration of physics modeling and machine learning for predictive world modeling from visual-tactile perceptions, especially in the low-data regime.

I am currently on the faculty job market for the 2024-25 cycle!

News

June 2023: I successfully defended on 06/20!

April 2023: Our paper ``Few-shot Adaptation for Manipulating Granular Materials Under Domain Shift” is accepted to RSS 2023! We also release a scooping dataset with over 6,000 scoops on a diverse set of materials: website, paper.

Nov 2022: Our robot TRINA has been participating in the AVATAR XPRIZE competition as Team AVATRINA, and we just scored 4-th in the finals, one of the only 4 teams that completed all 10 tasks: media.

Selected Publications

J. Marques*, P. Naughton*, J. C. Peng*, Y. Zhu*, J. S. Nam, Q. Kong, X. Zhang, A. Penmetcha, R. Ji, N. Fu, V. Ravibaskar, R. Yan, N. Malhotra, and K. Hauser, "Immersive Commodity Telepresence with the TRINA Robot Avatar," International Journal of Social Robots, 2024. (* Denotes equal contribution)

Y. Zhu*, P. Thangeda*, M. Ornik and K. Hauser., "Few-shot Adaptation for Manipulating Granular Materials Under Domain Shift," Robotics: Science and Systems (RSS), 2023. (* Denotes equal contribution)

Y. Zhu, A. Smith, and K. Hauser, "Automated Heart and Lung Auscultation in Robotic Physical Examinations," IEEE Robotics and Automation Letters (RA-L), 2022.

Y. Zhu, K. Lu, and K. Hauser. Semi-Empirical Simulation of Learned Force Response Models for Heterogeneous Elastic Objects. IEEE International Conference on Robotics and Automation (ICRA), June 2020 Summary video ICRA 10-minute talk video

Y. Zhu, Z. Pan, and K. Hauser. Contact-Implicit Trajectory Optimization with Learned Deformable Contacts Using Bilevel Optimization. IEEE International Conference on Robotics and Automation (ICRA), May 2021. Supplemental video

Y. Zhu, L. Abdulmajeid, and K. Hauser. Data-driven Approach for Fast Simulation of Robot Locomotion on Granular Media. IEEE International Conference on Robotics and Automation, May, 2019. Summary video ICRA 10-minute talk video

Robots that I work with

UR5

TRINA

Robosimian

Franka Panda