Jierui Lin

I am currently a machine learning engineer at Apple AIML, where I work on computer vision, machine learning and robotics.

I obtained my Master's degree in Computer Science from UT Austin, advised by Prof. Philipp Krähenbühl and Prof. Yuke Zhu. Prior to that, I obtained my Bachelor's degree in Computer Science and Applied Mathematics from UC Berkeley, where I'm fortunate to work with Prof. Trevor Darrell and Prof. Jitendra Malik.

Email / Google Scholar / Twitter / LinkedIn / Github

Research

	TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation David Berthelot, Arnaud Autef, Jierui Lin, Dian Ang Yap, Shuangfei Zhai, Siyuan Hu, Daniel Zheng, Walter Talbott, Eric Gu arXiv Preprint, 2023 arXiv
	3D Shape Reconstruction from Free-Hand Sketches Jiayun Wang, Jierui Lin, Qian Yu, Runtao Liu, Yubei Chen, Stella X. Yu ECCV Workshop, 2022 arXiv / slides / code
	Fighting Fire with Fire: Avoiding DNN Shortcuts through Priming Chuan Wen, Jianing Qian, Jierui Lin, Jiaye Teng, Dinesh Jayaraman, Yang Gao ICML, 2022 arXiv / website / code
	PointDrive: A Point-based Self-driving Policy Jierui Lin Master's Thesis, 2022 arXiv
	Keyframe-Focused Visual Imitation Learning Chuan Wen, Jierui Lin, Jianing Qian, Yang Gao, Dinesh Jayaraman ICML, 2021 arXiv / website / code
	Fighting Copycat Agents in Behavioral Cloning from Observation Histories Chuan Wen, Jierui Lin, Trevor Darrell, Dinesh Jayaraman, Yang Gao NeurIPS, 2020 arXiv / website / code

Honors & Awards

Highest Honor in Applied Mathematics from UC Berkeley

Honor in Computer Science from UC Berkeley

Service

Reviewer for NeurIPS, ICLR, ICML, CVPR, ICCV, ECCV, ACCV

Teaching Assistant for CS 170 (Algorithms), CS 188 (AI) at UC Berkeley, CS 342 (Neural Networks), CS 343 (AI) at UT Austin

Design and source code from Jon Barron's website.