Sandeep Polisetty

Sandeep Polisetty

PhD student exploring efficient systems for machine learning

Sandeep Polisetty

I am a final year PhD student in the College of Information and Computer Sciences at the University of Massachusetts Amherst, advised by Prof. Hui Guan and Prof. Marco Serafini. I am currently working on building efficient systems for Scalable multi-GPU Graph Neural Network training.

Previously, I also explored efficient graph analytics frameworks advised by Prof. Marco Serafini. During my masters, I worked on scalable distributed transactions advised by Prof. Arun Venkataramani. Prior to coming to USA, I pursued my undergraduate degree at the Indian Institute of Technology, Kharagpur.

Alongside research, I also worked on large industrial software during my internships. I recently finished an internship with Intel as an AI Frameworks Engineer working on a pytorch extension to support intel hardware. Previously at Reservoir Labs (acquired by Qualcomm), I was a Research Engineer working on the popular deep learning TVM compiler. Before that, I was a Software Engineer Intern with the AWS distributed systems team.

I aspire to build infrastructure that is fueling the AI revolution. Efficient and easy to adopt frameworks are especially important with rising hardware costs. To support these goals, I have worked at various levels across the framework such as efficient kernel design, parallelization strategies, compiler abstractions and hardware aware models to optimize performance. I am currently seeking internship opportunities for Spring 2025 and full time opportunities for 2025 Fall. Please contact me for further details.

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