Xuan Chen | 陈璇

ECE MS Student

Carnegie Mellon University

About

I am a second-year Master student in the Electrical and Computer Engineering Dept. at Carnegie Mellon University. Before CMU, I obtained my bachelor degree from University of Science and Technology Beijing in 2019.

My research interests lie in interpretable artifical intelligence(AI) and reinforcement learning, machine learning(ML) security and privacy, the vibrant research field that focuses on reducing ML systems vulnerabilities and designing verifiable machine learning approaches with provable robustness. My enthusiasm is to develop trustworthy machine learning solutions as well as deploying reliable AI systems, to help end users trust the AI system and make humans empowered by machine learning.

Interests

Deep Learning
Machine Learning Security
Explainable Neural Network
Reinforcement Learning

Education

MSc in Electrical and Computer Engineering, 2020
Carnegie Mellon University
BSc in Electrical Engineering, 2019
University of Science and Technology Beijing

Projects

Explanation for Deep Reinforcement Learning

Behavior-level explanations of the Deep-Q-Network trained agents.

Fast Transfer Learning for GAN Style Transfer

A novel transfer learning method for GAN style transfer which consumes fewer computation resources and training time.

Uncertainty Calibration for Neural Network Output

Trainable and Diffientiable Loss for Classification Neural Network.

Publications

Quickly discover relevant content by filtering publications.

Towards Behavior-Level Explanation for Deep Reinforcement Learning

While Deep Neural Networks (DNNs) are becoming the state-of-the-art for many tasks including reinforcement learning (RL), they are …

**Xuan Chen**, Zifan Wang, Yucai Fan, Bonan Jin, Pitor Mardziel, Carlee Joe-Wong, Anupam Datta

Preprint Project