Niranjana Deshpande
Ph.D. Candidate
![prof_pic.jpg](/assets/img/prof_pic.jpg?0f09f9b186ccf6d4c26d265be8dc6a29)
Rochester, New York, 14623
I’m Niranjana, and I’m a computing and information sciences Ph.D. candidate at Rochester Institute of Technology. I am advised by Dr. Naveen Sharma and fortunate to be mentored by Dr. Mohamed Wiem Mkaouer, Dr. Ernest Fokoue, Dr. Qi Yu and Dr. Daniel Krutz.
I conduct interdisciplinary research at the intersection of software engineering and machine learning. Specifically, (1) I study how evolutionary algorithm performance varies when applied to hard software engineering problems, (2) Leverage statistical ML techniques to derive insights and recommend algorithms at a fine-grained, problem-instance level, and (3) Use these models to design systems that dynamically select algorithms to improve computational resource usage. So far, I’ve studied the benefits of evolutionary algorithms for constructing service-oriented systems and recommending APIs during library migration. Our paper on self-adaptive service-oriented systems using algorithm selection won the best paper award at IEEE ICWS 2021.
Before joining RIT, I was an undergraduate student at the Cummins College of Engineering for Women, where I earned my Bachelor’s in Computer Engineering.
news
Feb 02, 2024 | Website revamp successful! |
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Nov 27, 2023 | Our paper on evaluating multi-objective evolutionary algorithms for API migration was accepted to the Journal of Swarm and Evolutionary Computation! |
Oct 04, 2023 | I’m presenting my research at the Doctoral Symposium at ESEC/FSE in San Francisco this December. |
Apr 15, 2023 | I’ve accepted a data scientist internship in the Product Analytics and Data Science (PANDAS) team at Amazon Web Services in Seattle. |
May 14, 2022 | I’ve successfully defended my thesis proposal, and am looking forward to my internship in Seattle! |
selected publications
- ICWSR-CASS: Using algorithm selection for self-adaptive service-oriented systemsIn 2021 IEEE International Conference on Web Services (ICWS) , 2021