Curriculum Vitae

The full version of my CV can be found [here].

Jump to: Education | Work Experience | Publications | Honors & Awards

Education

• Ph.D. in Computer Science, The University of Texas at Dallas, (August 2020 - Present)
• M.S. in Artificial Intelligence, The University of Georgia, July 2020
  (Thesis: An Exploration of Machine Learning Based Day-Ahead Solar Irradiance Forecasting Methodologies)
• B.Tech. in Computer Science, Indian Institute of Information Technology (IIIT), Vadodara, May 2018
  (Capstone Project: Automatic Speech Recognition Using Deep Learning)

Work Experience

• June 2022 – Present: Graduate Research Assistant under Dr. Tien N. Nguyen, The University of Texas at Dallas.
• June 2021 – August 2021: Data Scientist Intern at AI Camp Inc., CA, USA.
• August 2020 – May 2022: Graduate Teaching Assistant at the Department of Computer Science, The University of Texas at Dallas.
• August 2018 – July 2020: Graduate Research Assistant at the Institute for Artificial Intelligence, The University of Georgia.
• January 2018 – May 2018: Undergraduate Research Assistant at the Speech Research Lab, IIIT Hyderabad

Academic Service

• Program Committee - International Conference on Software Engineering (ICSE’24, Artifact Evaluation Track).
• Junior Program Committee - International Conference on Mining Software Repositories (MSR’23, Technical Track).

Publications

• [ICSE 2024]    Yuchen Cai, Aashish Yadavally, Abhishek Mishra, Genesis Montejo, and Tien N. Nguyen. 2024. Programming Assistant for Exception Handling with CodeBERT. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering. April 14–20, 2024. IEEE CS Press, 2024.
• [ESEC/FSE 2023]    Yi Li, Aashish Yadavally, Jiaxing Zhang, Shaohua Wang, and Tien N. Nguyen. 2023. DeMinify: Neural Variable Name Recovery and Type Inference. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. December 3–9, 2023. ACM Press, 2023. (To Appear).
• [ESEC/FSE 2023]    Yi Li, Aashish Yadavally, Jiaxing Zhang, Shaohua Wang, and Tien N. Nguyen. 2023. Commit-Level, Neural Vulnerability Detection and Assessment. In Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering. December 3–9, 2023. ACM Press, 2023. (To Appear).
• [ICSE 2023]    Aashish Yadavally, Wenbo Wang, Shaohua Wang, and Tien N. Nguyen. 2023. (Partial) Program Dependence Learning. In Proceedings of the 45th IEEE/ACM International Conference on Software Engineering. May 14–20, 2023. IEEE CS Press, 2023. Nominated for ACM SIGSOFT Distinguished Paper Award
• [ICSE 2023]    Wenbo Wang, Tien N. Nguyen, Shaohua Wang, Yi Li, Jiyuan Zhang, and Aashish Yadavally. 2023. DeepVD: Towards Class-Separation Features for Neural Network Vulnerability Detection. In Proceedings of the 45th IEEE/ACM International Conference on Software Engineering. Oct 14–20, 2023. IEEE CS Press, 2022.
• [ASE 2022]    Hoan Nguyen, Hung Dang Phan, Samantha Syeda Khairunnesa, Son Nguyen, Aashish Yadavally, Shaohua Wang, Hridesh Rajan, and Tien N. Nguyen. 2022. A Hybrid Approach for Inference between Behavioral Exception API Documentation and Implementations, and Its Applications. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering. Oct 10–14, 2022. IEEE CS Press, 2022. (To Appear).
• [ASE 2022 - NIER]    Anh Nguyen, Aashish Yadavally, and Tien N. Nguyen. 2022. Next Syntactic-Unit Code Completion and Applications. In Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering: New Ideas and Emerging Results Track. Oct 10–14, 2022. IEEE CS Press, 2022. (To Appear).
• [SANER 2022]    Thang Nguyen, Aashish Yadavally, and Tien N Nguyen. 2022. Phrase2Set: Phrase-to-Set Machine Translation and Its Software Engineering Applications. In 29th IEEE International Conference on Software Analysis, Evolution and Reengineering. March 14-17, 2022. IEEE CS Press, 2022.
  IEEE Computer Society TCSE Distinguished Paper Award
• [MS Thesis]    Aashish Yadavally. 2020. An Exploration of Machine Learning Based Day-Ahead Solar Irradiance Forecasting Methodologies. In University of Georgia ProQuest Dissertations Publishing.

Honors & Awards

• Awarded the ACM SIGSOFT Travel Grant for USD 400 to attend ESEC/FSE 2023.
• Awarded the ACM SIGSOFT Travel Grant for USD 500 to attend ICSE 2023.
• Nominated for ACM SIGSOFT Distinguished Paper Award for (Partial) Program Dependence Learning at the 45th IEEE/ACM International Conference on Software Engineering (ICSE 2023).
• IEEE Computer Society TCSE Distinguished Paper Award for Phrase2Set: Phrase-to-Set Machine Translation and Its Software Engineering Applications at the 29th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022).
• First Prize, Project Dazzle, AI Camp Hackathon 2021
• First Prize - Public Voting Category, IIITV Hackathon 2016