I previously received my B.S. in Mechanical Engineering from Purdue University and Shanghai Jiao Tong University, where I was fortunate to be advised by Karthik Ramani on Human-Computer Interaction. Recently, I'm looking for Ph.D. positions. Please let me know if you are interested in my research.
I support diversity, equity, and inclusion. If you would like to have a chat with me regrading research, career plans or anything, feel free to reach out! I would be happy to support people from underrepresented groups in the STEM research community, and hope my expertise can help you.
[Sep 2021] Started at Stanford as a Msc student in Mechanical Engineering.
[Aug 2022] "See, Hear, Feel: Smart Sensory Fusion for Robotic Manipulation" is accepted by CoRL'22.
[Jan 2023] "Sonicverse: A Multisensory Simulation Platform for Embodied Household Agents that See and Hear" is accepted by ICRA'23.
[Feb 2023] "The ObjectFolder Benchmark: Multisensory Object-Centric Learning with Neural and Real Objects" is accepted by CVPR'23.
I'm broadly interested in artificial intelligence and robotics, including but not limited to perception, planning, control, hardware design, and human-centered AI.
The goal of my research is to build agents that can achieve human-level of learning and adapt to novel and challenging scenarios by leveraging multisensory information including vision, audio, touch, etc.
We introduce the OBJECTFOLDER BENCHMARK, a
benchmark suite of 10 tasks for multisensory object-centric
learning, and the OBJECTFOLDER REAL dataset, in-
cluding the multisensory measurements for 100 real-world
We introduce SONICVERSE, a multisensory
simulation platform with integrated audio-visual simulation
for training household agents that can both see and hear.
We demonstrate SONICVERSE’s realism via sim-to-real
Using our VRFromX system,
users can select region(s) of interest (ROI) in scanned point cloud or
sketch in mid-air using a brush tool to retrieve virtual models and
then attach behavioral properties to them.
Course Assistant in AA274A: Principle of Robot Autonomy, Stanford University, 2022