About me
As a Ph.D. student at UMN under Dr. Nicola Elia’s supervision focusing on distributed algorithms and multi-agent robotics, I aim to build computationally efficient models and algorithms to help people and robots make optimal decisions in real-time with physical interpretations, bridging the gap between pure statistical models and physics. I, therefore, endeavor to become a research scientist specializing in combining numerical algorithms and optimization.
During the 2018 summer, I interned at Allen Institute for Brain Science with Dr. Anatoly Buchin, participating in the development of precise single neuron and network models with genetic optimization algorithms. After the internship, I joined the UW BioRobotics Lab, working on Behavior Trees embedded Graphical Models based on medical records with Dr. Blake Hannaford. After earning my Masters’s degree, I then worked on Image-based Unsupervised Anomaly Detection and Image Retrieval at TSMC BDSA with Dr. Yi-Chun Chen. I joined Amazon as an Applied Scientist Intern during 2022 summer, working on Reinforcement Learning Based Active Learning with Dr. Jiacong Li and Dr. Cecile Levasseur.
Current Projects
Multi-Agent Robotics Planning and Control
POMDP Reinforcement Learning and States Estimations
News
- August 02 - 20, 2021: Machine Learning Summer School 2021 Taipei
- August 19 - 21, 2019: ADSI SUMMER WORKSHOP: ALGORITHMIC FOUNDATIONS OF LEARNING AND CONTROL
- August 13 - 17, 2019: ADSI SUMMER SCHOOL ON FOUNDATIONS OF DATA SCIENCE
- July 29, 2019 - August 09, 2019: MSRI Mathematics of Machine Learning Summer School
- June 17 - 21, 2019: Applied Mathematics: The Next 50 Years
- July 13 - 18, 2018: 27th Annual Computational Neuroscience Meeting