2022–2027 (expected)
PhD in Statistics
University of Georgia · Advisors: Ping Ma and Wenxuan Zhong
Statistics PhD Candidate · University of Georgia
Tao Wang
I am a Statistics PhD candidate at the University of Georgia, advised by Ping Ma and Wenxuan Zhong. My research focuses on efficient LLM adaptation, knowledge distillation, functional data analysis, and forecasting.
Education
2020–2021
MS in Operations Research
Georgia Institute of Technology
2016–2020
BS in Industrial Engineering
University of Pittsburgh and Sichuan University
Publications
Google ScholarKnowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions
Luyang Fang, Xiaowei Yu, Jiazhang Cai, et al., including Tao Wang
Large Language Models for Bioinformatics
Wei Ruan, Yanjun Lyu, Jing Zhang, et al., including Tao Wang
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
Haoran Lu, Luyang Fang, Rui Zhang, et al., including Tao Wang
COVID-19 Hospitalizations Forecasts Using Internet Search Data
Tao Wang, Simin Ma, Soobin Baek, Shihao Yang
Functional Regression for SERS Spectrum Transformation Across Diverse Instruments
Tao Wang, Yanjun Yang, Haoran Lu, Jiaheng Cui, Xianyan Chen, Ping Ma, Wenxuan Zhong, Yiping Zhao
SPOT: An Active Learning Algorithm for Efficient Deep Neural Network Training
Luyang Fang, Cheng Meng, Lin Zhao, Tao Wang, Tianming Liu, Wenxuan Zhong, Ping Ma
Generalizable and Efficient Automated Scoring with a Knowledge-Distilled Multi-Task Mixture-of-Experts
Luyang Fang, Tao Wang, Ping Ma, Xiaoming Zhai
Domain-Adaptive Anomaly Detection and Severity Prediction of Electric Machine Drives at the Point of Common Coupling
Abolfazl Najar, Shushan Wu, He Yang, Tao Wang, et al.
GASDU: Gauss-Southwell Dynamic Update for Efficient LLM Fine-Tuning
Tao Wang, Luyang Fang, Wenxuan Zhong, Ping Ma