I have a diversity of interests and experience in vision neuroscience, computer vision, AR/VR technologies, and robotics.
I worked on soft robotics, vehicle crash safety, electric vehicle warning systems, and auditory neuroscience as an undergraduate student at Tsinghua University, China.
As a PhD student in Computation and Neural Systems at Caltech, I lead projects including: an AR cognitive assistant for the blind, real-time animal tracking, calcium imaging in mice, and synthetic data generation for improving rare class generalization with deep convolutional neural networks.
Invited Talk: Powering a cognitive assistant for the blind using AR.
Advisor: Dr. Markus Meister
Department of Automotive Engineering
Thesis Advisor: Dr. Qing Zhou
Deep convolutional neural networks, like most other modern computer vision systems, struggle to categorize objects they have seen only rarely during training, and collecting a sufficient number of training examples of rare events is often challenging and expensive, and sometimes outright impossible. We explore in depth an approach to this problem: complementing the few available training images with ad hoc simulated data.Preprint on arXiv
We combine augmented reality technology with computer vision algorithms and spatial sound to create goggles that can help blind people navigate unfamiliar spaces. We had great success with initial testing with blind subjects and hope the technology can one day be offered by places like banks, grocery stores, museums, and more.Peer-reviewed paper on eLife
Video tracking is widely used for studying rodent behaviors. However the majority of tracking methods does not work in real time, and therefore can not be used for closed-loop experiments. With python and OpenCV, I developed a lightweight, fast, and simple blob tracking system that performs real-time mouse position tracking, video display and recording, as well as streaming position via UDP.
We developed a type of liquid metal electrodes and the method of directly printing it on dielectric elastomers for dielectric elastomer actuators (DEA). Such soft electrodes enable dielectric elastomer films to approach its maximum strain and stress at relatively low voltages. And its unique capability of achieving two-dimensional in-plane self-healing by simple actuation allows more tolerance to fault and resilience to abusive environments. This actuator has a wide spectrum of applications ranging from artificial muscle, flexible electronics to smart clothings.Peer-reviewed paper published on Applied Physics Letters