
Aashish Yadavally
Assistant Professor
- Office: L3Harris Engineering Center
- Email: Aashish.Yadavally@ucf.edu
- Phone: 407-823-3957
BIOGRAPHY
Aashish Yadavally is an assistant professor of computer science at the University of Central Florida, where he leads the Software Engineering and Artificial Intelligence Research Lab (SAIL@UCF).
His research lies at the intersection of artificial intelligence and software engineering, with a focus on optimizing software development processes and enhancing software security. His work has appeared in premier venues such as International Conference on Software Engineering, Foundations of Software Engineering, Automated Software Engineering, and Object-Oriented Programming, Systems, Languages and Applications, and has earned multiple accolades, including the Association for Computing Machinery SIGSOFT Distinguished Paper Award at Foundations of Software Engineering 2024 and the IEEE Technical Community on Software Engineering Distinguished Paper Award at the 2022 Software Analysis, Evolution and Reengineering Conference. His long-term vision is to establish and advance scalable, AI-assisted development workflows that support secure and reliable software engineering.
EDUCATION
- Ph.D. in Computer Science, University of Texas at Dallas
- M.S. in Artificial Intelligence, University of Georgia
- B.Tech. in Computer Science, Indian Institute of Information Technology Vadodara
RESEARCH
- Software Engineering
- Software Security
- Machine Learning
- Artificial Intelligence
- Programming Language Processing
PUBLICATIONS
- [ICSE 2025] Aashish Yadavally, Xiaokai Rong, Phat Nguyen, and Tien N. Nguyen. 2025. “Large Language Models for Safe Minimization”. In 47th IEEE/ACM International Conference on Software Engineering.
- [ICSE 2025] Smit Patel, Aashish Yadavally, Hridya Dhulipala, and Tien N. Nguyen. 2025. “Planning a Large Language Model for Static Detection of Runtime Errors”. In 47th IEEE/ACM International Conference on Software Engineering.
- [FSE 2025] Yi Li, Hridya Dhulipala, Aashish Yadavally, Shaohua Wang, and Tien N. Nguyen. 2025. “Blended Analysis for Predictive Execution”. In 32nd ACM International Conference on the Foundations of Software Engineering.
- [FSE 2025] Hridya Dhulipala, Aashish Yadavally, Smit Patel, and Tien N. Nguyen. 2025. “CRISPE: Semantic-Guided Execution Planning and Dynamic Reasoning for Enhancing Code Coverage Prediction”. In 32nd ACM International Conference on the Foundations of Software Engineering.
- [FSE 2024] Aashish Yadavally, Yi Li, and Tien N. Nguyen. 2024. “Predictive Program Slicing via Execution Knowledge-Guided Dynamic Dependence Learning”. In 31st ACM International Conference on the Foundations of Software Engineering.
- [OOPSLA 2024] Aashish Yadavally, Yi Li, Shaohua Wang, and Tien N. Nguyen. 2024. “A Learning-Based Approach to Static Program Slicing”. In Proceedings of the 2024 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications.
- [ESEC/FSE 2023] Yi Li, Aashish Yadavally, Jiaxing Zhang, Shaohua Wang, and Tien N. Nguyen. 2023. “Commit-Level Neural Vulnerability Detection and Assessment”, In 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering.
AWARDS
- ACM SIGSOFT Distinguished Paper Award, FSE 2024
- Distinguished Junior PC Reviewer Award, MSR 2024
- Nomination for ACM SIGSOFT Distinguished Paper Award, ICSE 2023
- IEEE TCSE Distinguished Paper Award, SANER 2022