Zian Wang
Department of Computer Science, Stony Brook University
Contact : ziawang@cs.stonybrook.edu

About Me

I am a new first year Ph.D. student studying at the Stony Brook University, Department of Computer Science. I obtained my Master’s degree in Information Science from the School of Computing and Information at the University of Pittsburgh in January 2023 and hold dual Bachelor’s degrees in Computer Science and Computing and Information Science from my undergraduate studies.

My primary research focus is on Natural Language Processing (NLP) and Bayesian modeling. I believe NLP holds the key that can make machines not only utilize quintillions of bytes of data generated by humans daily but also grasp our accumulated knowledge and experience to address pressing real-world challenges. I myself have finished a paper on using Transfer Learning to apply BERT models to downstream tasks, and it has been accepted by SPML 2023. Among my projects, I have conducted sentiment analysis of Tweets from the COVID-19 pandemic and identified biased terms within police union contracts.

During my Master’s studies, I conducted research about NLP applications in the PICSO lab with Dr. Yuru Lin at UPitt. One of our recent endeavors is a paper proposing a predictive model for food insecurity across African nations, currently under review for BFNDMA 2023. Additionally, I finished a review project on Bayesian Optimization under the guidance of Dr. Joseph Yurko.

Beyond my core research areas, I am also interested in most of the general directions in machine learning, including Deep Learning, Data Mining, Trustworthy ML, Algorithms, Optimization, and Human Computer Interaction. As a perpetual learner, I continue to navigate the vast and intriguing landscape of machine learning with enthusiasm. I am on the lookout for potential fits in research groups of our department, any opportunities or suggestions would be greatly appreciated.

Here is my CV and my transcript

Papers and reports

2023:
HungerGist: An Interpretable Predictive Model for Food Insecurity
Yongsu Ahn, Muheng Yan, Zian Wang, and Yu-Ru Lin
The 5th international workshop on Big food, nutrition and environment data management and analysis(BFNDMA 2023).

2022:
A New Computationally Efficient Method to Tune BERT Networks – Transfer Learning
Zian Wang
Accepted by the 2023 International Conference on Signal Processing and Machine Learning (CONF-SPML 2023).

2021:
Police Union Contract Misconduct Complaint Detection
Zian Wang, Sonal Gupta, Shuo Zheng
A final report paper for the Data Mining course, topic is given by Dr. Lin Yuru.

Thanks

I am deeply grateful to Dr. Lin and Dr. Yurko for their invaluable guidance during my Master’s studies and throughout my Ph.D. application process. Both professors provided immense support in lab projects, courses, and in my overall academic journey. I extend my heartfelt appreciation to them!