Dongdong She

Dongdong She is an Assistant Professor at the Department of Computer Science and Engineering (CSE) at the Hong Kong University of Science and Technology (HKUST). He received his Ph.D. in Computer Science from Columbia University, where he worked with Suman Jana and Baishakhi Ray. Prior to his Ph.D., he worked with Zhiyun Qian on Android Security at the University of California, Riverside. He earned his bachelor's degree from Huazhong University of Science and Technology. His research interests include cybersecurity, software engineering, and programming languages, with a focus on applying data-driven approaches such as large language models and machine learning to address security challenges. He is also the recipient of an ACM CCS Best Paper runner-up award and a finalist in the NYU CSAW applied research competition.

Dongdong She is a researcher at the Hong Kong University of Science and Technology, focusing on Security, Machine Learning, Program Analysis, and Fuzzing. His work integrates machine learning techniques with software security to enhance the effectiveness of fuzzing and dynamic analysis. Notable contributions include Neuzz, which combines neural networks with fuzzing for efficient program testing, and NeuDep, which uses neural networks for memory dependence analysis. He has also developed tools like Mc2 and HFuzz to improve the efficiency and precision of fuzzing and symbolic execution. His research emphasizes the intersection of AI and software security, aiming to detect vulnerabilities and improve system robustness.