Wang Jian is a Ph.D. candidate in the College of Computing and Data Science (CCDS) at Nanyang Technological University (NTU), Singapore (since Aug 2021). His research lies at the intersection of software engineering and AI, with a focus on automated program repair, code intelligence, AI-generated code security, and the robustness and reliability of large language models for code.

His recent work includes building large-scale, executable benchmarks and systems that make AI-assisted software repair more practical. He is a lead author of Defects4C, a comprehensive benchmark of real-world C/C++ bugs and vulnerabilities used to evaluate and stress-test the repair capabilities of state-of-the-art large language models. He also developed RATCHET, a retrieval-augmented transformer framework that combines test-less fault localization and patch generation to automatically fix buggy code in the wild. Beyond repair, he has conducted large-scale empirical studies on AI-generated code detection, including evaluating commercial and open-source AIGC detectors on millions of machine-generated code samples. His work further explores how execution semantics, fairness constraints, and interpretability techniques can be integrated into neural systems to make them more trustworthy and auditable.

He has published in leading venues across software engineering, reliability, security, and AI, including ASE (2024, 2025), ISSRE (2024), EMNLP Findings (2025), LCTES (2024), and ACM TOSEM (2022, 2023).
Before joining NTU, he spent several years working on large-scale AI infrastructure and high-performance backend systems in industry. From 2017 to 2019, he was a research scientist at Xiaomi AI Lab, where he helped build Xiaomi’s deep learning framework and large-scale vision/algorithm services. From 2011 to 2017, he worked at 58.com, where he helped design and deploy a production-grade user profiling and behavior analytics platform, and led the development of a high-performance asynchronous web framework that continues to handle over 100 million daily requests in production.

He received his bachelor’s degree from Tianjin University in 2011 and an AI / computer vision certification from Tsinghua University in 2019.