I am a PhD candidate at Prof.Kanso’s Bio-inspired Motion Lab at Univeristy of Southern California. I got my B.S. degree from Shanghai Jiao Tong Univeristy in 2019, where I also worked as an undergraduate research assistant at J.C. Wu Center for Aerodynamics for four years.

My CV can be found at CV.

Research interest

My research takes a multi-disciplinary approach to understand the locomotion of swimming and flying animals. Natural selection has endued these animals fascinating ability in interacting with ambient flow structures, which is not achievable by any man-made vehicles. Both the unsteady flow physics and the sensory control strategy behind these biological behaviors arouse my interests. I utilized methods from computational fluid dynamics (CFD), robo-physical experiment, reduced order modeling, reinforcement learning, and control theory to tackle these problems. For futrue direction, I’m curious about applying these knowledges to designing autonomous robots.

Research projects

Currently, my work are composed of three parts: underwater sensing and navigation, collective behavior, and fluid structure interaction.

In the first part of my work, we are working on underwater navigation based on local flow sensing. This problem is tacled by data-driven methods, e.g. model free reinforcement learning. Several scenarios are considered. In the first scenario, we studied the sensory control strategy of an agnet following a hydrodynamic trail without any visual. The second scenario considered a weak swimmer utilizing the unsteady flow feature to swim against a strong adversial flow. The third scenario asked what information of neighbooring fish can be decoded when fishes are swimming in school.

In these different scenarios, we asked the following quesitons. First, what flow property is the most effective sensory cue, whether it is velocity, pressure or vorticity? Second, which location is optimal for placing the sensors along the body of the swimmer? Third, what is the optimal sensory-control strategy in each task?

In terms of collective behavior of fish, “Vortex phase matching”, which indicates a linear distance-phase relationship is well known in a two swimmer school. Here, we asked how does this understanding scales to larger school? How does different spatial pattern influence the distribution of power saving and school cohesion? More importantly, how does these understanding apply to real fish school, in which the topology are dynamically changing?

By performing vortex sheet and CFD simulation, we also looked at the role of body flexion in the performance of fish’s swimming. We found that passive flexion is able to enhance swimming efficiency but cannot enahnce swimming speed. Moreover, by active flexion according to the flow field generated by passive flexion, the swimmer can enhance swimming speed and efficiency simutaneously in a region of the design space that overlaps with biological observations.

During my undergraduate study, I studied the unsteady aerodynamics mechanism of flapping wings by designing scaled model and carrying out PIV and force measurement experiemnts.

Interacting with fluid “in person”

I’ve also began training toward a private pilot at Santa Monica Flyers.