Chao Ni

Chao Ni is an active Associate Professor at the School of Software Technology, Zhejiang University, specializing in software engineering with a focus on software quality assurance and mining software repositories. His research spans multiple key areas including vulnerability detection, defect prediction, automated program repair, and software security. He has consistently published in top-tier software engineering conferences such as ASE, ICSE, ESEC/FSE, and ISSTA, demonstrating significant contributions to the field. Ni also serves on program committees for major conferences, indicating recognition by his peers in the software engineering community.

Dr. Ni's research interests center around Software Quality Assurance and Mining Software Repositories, with particular emphasis on vulnerability detection, defect prediction, and automated program repair. His work often combines traditional software engineering approaches with machine learning techniques to address challenging problems in software development and maintenance. Recent publications show a strong focus on security aspects of software engineering, including smart contract security, JavaScript breaking changes, and vulnerability detection in C/C++ code.

Analysis of Dr. Ni's recent publications reveals a consistent research trajectory focused on improving software quality through advanced analysis techniques. His work spans multiple subdomains including vulnerability detection (particularly in smart contracts and C/C++ code), defect prediction (especially just-in-time approaches), and automated program repair. A notable trend is his increasing integration of machine learning techniques with traditional software engineering methods, creating hybrid approaches that leverage both semantic features and expert knowledge. His research has practical applications in software security, maintenance, and testing.

Dr. Ni has served on program committees for numerous prestigious conferences including APSEC, ASE, ESEC/FSE, and Mining Software Repositories. His service as a committee member across multiple tracks (Technical Track, Research Papers, Data and Tool Showcase) demonstrates his broad expertise and recognition in the software engineering community. His GitHub profile (jacknichao) shows active engagement with open source projects related to his research, particularly in vulnerability detection tools.