
My name is Hang Zhao, a six-year Ph.D. candidate at the Computer Science Department, Stony Brook University. I was interning at Meta as a Machine Learning Engineer working on Large Language Models fine-tuning. Here is my Google Scholar profile. My Resume is attached. My advisor is Prof. Xiaojun Bi. I am doing research at the HCI lab. My research experiences are related to Machine Learning, Deep Learning (Transformer, CNN, LSTM), Reinforcement Learning (DQN), AI medical diagnosis, and Large Language Models.
Publications:
Hang Zhao, Kaiyan Ling, IV Ramakrishnan, M.D. Guy Schwartz, Xiaojun Bi. Modeling Mouse-based Pointing and Steering Tasks for People with Parkinson's Disease, The ACM international joint conference on Pervasive and Ubiquitous Computing (UbiComp/IMWUT 2025) Paper
Hang Zhao, Qile P. Chen, Yijing Barry Zhang, Gang Yang. Advancing Single- and Multi-task Text Classification through Large Language Model Fine-tuning, arXiv preprint arXiv:2412.08587, Paper
Kaiyan Ling, Hang Zhao, Xiangmin Fan, Xiaohui Niu, Wenchao Yin, Yue Liu, Cui Wang, Xiaojun Bi. Modeling Touch Pointing and Detect Parkinson's Disease via a Mobile Game, The ACM international joint conference on Pervasive and Ubiquitous Computing (UbiComp/IMWUT 2024), Paper
Hang Zhao, Sophia Gu, Chun Yu, Xiaojun Bi. Bayesian Hierarchical Pointing Models, The 35th Annual ACM Symposium on User Interface Software and Technology (UIST 2022), Paper
Zhi Li, Maozheng Zhao, Didyendu Das, Hang Zhao, Yan Ma, Wanyu Liu, Michel Beaudouin-Lafon, Fusheng Wang, Iv Ramakrishnan, Xiaojun Bi. Select or Suggest? Reinforcement Learning-based Method for High-Accuracy Target Selection on Touchscreen, CHI Conference on Human Factors in Computing Systems (CHI 2022), Paper
Hang Zhao, Michael Wang, Xiaolei Zhou, Xiangshi Ren, Xiaojun Bi. Variance and Distribution Models for Steering Tasks, The 34th Annual ACM Symposium on User Interface Software and Technology (UIST 2021), Paper
Yu-Jung Ko, Hang Zhao, IV Ramakrishnan, Shumin Zhai, Xiaojun Bi. Modeling One-Dimensional Touch Pointing with Nominal Target Width, The 47th Annual Graphics Interface Conference (Graphics Interface 2021), Paper
Yu-Jung Ko, Hang Zhao, IV Ramakrishnan, Shumin Zhai, Xiaojun Bi. Issues Related to Using Finger-Fitts law to Model One-Dimensional Touch Pointing Tasks, CHI Conference on Human Factors in Computing Systems (China CHI 2021), Best Paper Honorable Mention Award | Paper
Yu-Jung Ko, Hang Zhao, Yoosang Kim, IV Ramakrishnan, Shumin Zhai, Xiaojun Bi. Modeling Two Dimensional Touch Pointing, The 33rd Annual ACM Symposium on User Interface Software and Technology (UIST 2020), Best Paper Honorable Mention Award | Paper
Working Experience:
Research Scientist @ Meta, Jan 2025 - Present
Menlo Park, California, United States · On-site
Software Engineer, Machine Learning Intern @ Meta, May 2024 - Aug 2024
Menlo Park, California, United States · On-site
Teaching Experience:
TA for CSE518 Human-Computer Interaction, Aug 2024 - Dec 2024
TA for CSE518 Human-Computer Interaction, Aug 2022 - Dec 2022
TA for CSE307 Fundamental of Programming Language, Jan 2020 - May 2020
Education:
Stony Brook University Jan 2021 - May 2025
Ph.D. Candidate in Computer Science
Stony Brook University Jan 2019 - Dec 2020
Master of Science in Computer Science
New York Institute of Technology Jan 2017 - Dec 2018
Master of Science in Computer Science
Award:
Stony Brook University GAANN Fellowship Award (2023-2024)
Best Paper Honorable Mention Award at 33rd Annual ACM Symposium on UIST 2021 (Top 5%)
Best Paper Honorable Mention Award at the International Symposium of CHI 2021 (Top 5%)
Kaggle Competition Bronze Medal (Top 6%) On CIBMTR - Equity in post-HCT Survival Predictions (2025)
Kaggle Competition Silver Medal (Top 4%) On OTTO - Multi-Objective Recommender System (2023)
Academic Service:
Reviewer for UIST 2024
Reviewer for CHI 2024
Reviewer for UIST 2022
Certificates:
Large Language Models: Application through Production edX Certificate
Large Language Models: Foundation Models from the Ground Up edX Certificate
Generative AI with Large Language Models Coursera Certificate
Generative AI for Everyone Coursera Certificate
Deep Learning Specialization Coursera Certificate
Machine Learning Specialization Coursera Certificate
Machine Learning Coursera Certificate
Introduction to Machine Learning in Production Coursera Certificate
Natural Language Processing with Classification and Vector Spaces Coursera Certificate
AI for Medical Diagnosis Coursera Certificate
Skills:
Programming Language: Java, Python, C/C++, R, MATLAB, Prolog, SML, Latex.
Database: IBM db2, MySQL, MongoDB.
Bigdata: Hadoop and Spark, MapReduce (Java), HDFS.
Web: HTML, CSS, JavaScript, d3.js, React.js, Node.js, XML.
Library: PyTorch, TensorFlow, Keras, CUDA, Scikit-learn, SciPy, Pystan, Pandas, NumPy, Matplotlib, Seaborn, Open-CV, Flask.
About Me:
A Leetcoder. A Kaggler. A Husband. A Father.