Weihao Qu, Ph.D.

• Assistant Professor

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Department: Computer Science and Software Engineering

Office: James and Marlene Howard Hall 227

Phone: 732-263-5396

Email: wqu@monmouth.edu

View Weihao Qu

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Dr. Qu received his Ph.D. in Computer Science at Boston University in 2022 under the supervision of Marco Gaboardi, and M.S. in Computer Science at University at Buffalo.  Before he joined Monmouth University as an Assistant Professor in the Computer Science and Software Engineering in 2023, he worked as a research scientist at Meta on security program analysis. Dr. Qu is interested in programming language research including semantics, type systems, proof systems, program analysis. He is also interested in security and deep learning.  

Education

Ph.D Computer Science, Boston University

MS, Computer Science, University of Buffalo

Research Interests

Program Language, Formal Verification, Logics, Deep Learning, Differential Privacy, Program Logic and Analysis, Security and Penetration Testing, Artificial Intelligence, Data Analysis, Deep Learning, Transformers

Scholarly Articles

• Ph.D. Dissertation: “Program-based Analysis for Quantitative Properties.” Weihao Qu, Boston University

• Weihao Qu, Ling Zheng, Haowen Pan, Dongyang Wang, “Time-Aware Transformer-based Prediction Model for AECOPD,” MEDINFO 2025
• Francisco Erramuspe Alvarez, Shobharani Polasa, Weihao Qu, Jay Wang, Ling Zheng, “Multimodal Injury Risk Prediction in Tennis,” The 5th IEEE International Conference on Human Machine Systems 2025 (IEEE ICHMS ’25)

• Jiawen Liu, Weihao Qu, Marco Gaboardi, Deepak Garg, Jonathan Ullman, “Program Analysis for Adaptive Data Analysis,” Programming Language Design and Implementation (PLDI 2024)
• Evan Gardner, Gurmeet Singh, Weihao Qu, “Penetration Testing Operating Systems: Exploiting Vulnerabilities,” 2024 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI), Beijing, China, 2024.
• Alley Stoughton, Carol Chen, Marco Gaboardi, Weihao Qu, “Formalizing Algorithmic Bounds in the Query Model in EasyCrypt,” The International Conference on Interactive Theorem Proving (ITP 2022) 
• Weihao Qu, Marco Gaboardi, Deepak Garg, “Relational Cost Analysis in a Functional-Imperative Setting,” Journal of Functional Programming 31 (JFP 2021) 
• Weihao Qu, Marco Gaboardi, Deepak Garg, “Relational Cost Analysis for Functional-Imperative Programs,” ACM SIGPLAN International Conference on Functional Programming (ICFP 2019) 
• Ezgi Cicek, Weihao Qu, Gilles Barthe, Marco Gaboardi, Deepak Garg, “Bidirectional Type Checking for Relational Properties,” Programming Language Design and Implementation (PLDI 2019) 

• Weihao Qu, Feng Lin, Wenyao Xu, “A Real-Time Low-Complexity Fall Detection System on the Smartphone,” IEEE First International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE 2016) 
• Weihao Qu, Feng Lin, Aosen Wang, Wenyao Xu, “Evaluation of a Low-Complexity Fall Detection Algorithm on Wearable Sensor Towards Falls and Fall-Alike Activities,” IEEE Signal Processing in Medicine and Biology Symposium (SPMB 2015)

Forthcoming

• Cybersecurity-education platform cybergla (http://www.cybergla.com) with Gurmeet Singh and Daniel Crawford
• AECOPD regression models using transformer and LNN with Dongyang Wang and George Khalil

Additional Information

In February, 2025 Dr. Qu was awarded a $174,999 grant from the National Science Foundation. NSF 2451348 – CRII:SHF: Precise Formal Verification of General Relational Quantitative Properties with Multiple Arrays

“Making Software Safer“, Monmouth Magazine, Fall/Winter 2025