Jiawei Huang

I am currently a Ph.D. candidate at University of Southern California (USC), where I am fortunate to be advised by Prof. Fengzhu Sun and Prof. Remo Rohs. My research interest lies in applying machine learning into biological problems like cancer and drug discovery. Besides, I am also interested in recommendation systems, automative driving and large language modeling in my free time.

Before USC, I received my bachelor's degree of Automation from Tsinghua University (THU) in 2018. I love tennis, badminton and photography.

Email / Linkedin / Github

Education

Ph.D. Sep. 2019 - Present University of Southern California (USC), CA, U.S. Ph.D. student in Boinfomatics
M.S. Sep. 2021 - 2022 University of Southern California (USC), CA, U.S. M.S. student in Computer Science
B.S. Sep. 2014 - June 2018 Tsinghua University (THU), Beijing, China. B.S. in Automation

Intern Experience

May 2024 -- Aug. 2024, Instagram Reels Core Modeling, Menlo Park, CA
Machine Learning Engineer Intern
May 2022 -- June 2022, Amazon Fresh Team, Irvine, CA
Software Development Engineer Intern
Apr. 2019 -- June 2019, ByteDance, Beijing, China
Software Development Engineer Intern

Publications

DeepDeconUQ Estimates Malignant Cell Fraction Prediction Intervals in Bulk RNA-seq Tissue.
Jiawei Huang, Yuxuan Du, Kevin R. Kelly, Jinchi Lv, Yingying Fan, Jiang F. Zhong, and Fengzhu Sun.
PLOS COMPUTATIONAL BIOLOGY, 2025
DeepDecon accurately estimates cancer cell fractions in bulk RNA-seq data.
Jiawei Huang, Yuxuan Du, Andres Stucky, Kevin R. Kelly, Jiang F. Zhong, and Fengzhu Sun.
Patterns, 2024
Structure-based prediction of protein-nucleic acid binding using graph neural networks
Jared Sagendorf, Raktim Mitra, Jiawei Huang, Xiaojiang S. Chen, and Remo Rohs
Biophysical Reviews, 2024

Awards

Student Travel Award, ICIBM 2023
USC Viterbi Graduate Fellowship, 2021
USC Dornsife Graduate Fellowship, 2019
Tsinghua University Outstanding Graduate, 2017