Sivajeet Chand
Technical University of Munich
Informatics 4 - Chair of Software & Systems Engineering (Prof. Pretschner)
Postal address
Postal:
Boltzmannstr. 3
85748 Garching b. München
About me
In July 2024, I started my PhD at the Chair of Software and Systems Engineering under the supervision of Prof. Dr. Pretschner at the Technical University of Munich. In my research, I am exploring the potential of Generative AI, particularly Large Language Models (LLMs), for code migration and modernization.
I hold a master's degree in Software Engineering and Technology from Chalmers University of Technology, Sweden. Prior to starting at the chair, I was employed as a Data Engineer at Volvo Group. Additionally, I have gained experience as a student engineer at Aptiv and Good Solutions.
Thesis Topics
If any of the following open topics pique your interest, do not hesitate to reach out. Ensure you include your current CV and grade report, along with a short motivation letter stating when you would like to start your thesis.
Ongoing / Assigned
| 1. Evaluating and Improving the Effectiveness of an AI-assisted tutoring system (with RW and JD) 2. Improving the Efficiency of an AI-assisted tutoring system (with RW and JD) 3. Comparative Analysis of Large Language Models for Automated Code Refactoring (with RW) | - Master's Thesis - Master's Thesis - Master's Thesis |
Publications
Sivajeet Chand, Sushant Kumar Pandey, Jennifer Horkoff, Miroslaw Staron, Miroslaw Ochodek, and Darko Durisic. 2023. Comparing Word-Based and AST-Based Models for Design Pattern Recognition. In Proceedings of the 19th International Conference on Predictive Models and Data Analytics in Software Engineering(PROMISE). Page: 44 - 48.
Sushant Kumar Pandey, Sivajeet Chand, Jennifer Horkoff, and Miroslaw Staron. Design Patterns Understanding and Use in the Automotive Industry: An Interview Study. International Conference on Product-Focused Software Process Improvement(PROFES). Page: 301 - 319.
Sivajeet Chand, Chang Li, CM Montes, B Cabrero-Daniel, J Horkoff. Automating Requirements Review in the Automotive Sector: A Tailored AI Approach 2024 IEEE 32nd International Requirements Engineering Conference (RE). Page: 492 - 493.