About Me

I am a first-year Master's student with Stanford Vision and Learning Lab (SVL) and Stanford Electrical Engineering (Stanford EE). I am lucky to work with Dr. Jim Fan (now at Nvidia) and Agrim Gupta.

I obtained my bachelor's degree with first-class honors from The University of Edinburgh in Summer 2020. Previously, I have also spent time at ByteDance AI Lab (Beijing).

Research Overview

I am generally interested in embodied AI that enables learning through interaction with environments. I study reinforcement learning and imitation learning. Before I came to Stanford, I worked toward surpassing human-level performance in 3D games with deep reinforcement learning.

Besides dealing with MDPs, my previous work also lies at the intersection of deep learning, physics, engineering, and social science. With these diverse backgrounds, my curiosities naturally extend to neuroscience, epistemology, and cognition science. I believe that the community of embodied AI will evolve together with these fields.


Many Ways to be Lonely: Fine-grained Characterization of Loneliness and its Potential Changes in COVID-19
Yueyi Jiang, Yunfan Jiang, Liu Leqi, Piotr Winkielman
Under review as a conference paper at AAAI ICWSM-2022.

CSTNet: A Dual-Branch Convolutional Neural Network for Imaging of Reactive Flows using Chemical Species Tomography
Yunfan Jiang, Jingjing Si, Rui Zhang, Godwin Enemali, Bin Zhou, Hugh McCann, Chang Liu
Under review as a journal article at IEEE Transactions on Neural Networks and Learning Systems


Graduate Grader
EE 277 Fall 2021 (Instructor: Prof. Benjamin Van Roy), EE 236A Fall 2021

Honors and Awards

Ewart Farvis Project Prize (Top 2)
School of Engineering, The University of Edinburgh, October 2020
Jointly awarded to the best two bachelor theses with the most industrial relevance.

First Rank in Junior Year
School of Engineering, The University of Edinburgh, July 2019