Sudipta Saha Shubha

Endowed Fellow, University of Virginia | Research Associate @ Hewlett Packard (HP) Enterprise Labs Systems for Generative AI

Contact: ss7krd@virginia.edu

Welcome to my home page!

Hi, I am Sudipta, a Computer Science PhD student at the University of Virginia (UVA). I am working with Dr. Haiying Shen from UVA and Dr. Anand Iyer from Georgia Tech. I am broadly interested in research opportunities at the intersection of networked systems and machine learning. My research works involve cloud/high-performance/edge computing, computer networks, operating system, GPU/TPU architecture, and deep learning (DL) models. I am currently working on developing cost- and energy-efficient and scalable infrastructures for distributed inference serving of generative AI (e.g., LLM) models. I feel grateful for the opportunity to work closely with Dr. Ganesh Ananthanarayanan from Microsoft Research and Dr. Ayush Goel, Dr. Puneet Sharma, and Dr. K. K. Ramakrishnan from Hewlett Packard Labs.

Before starting my PhD journey, I have completed my B.Sc. in Computer Science and Engineering (CSE) from Bangladesh University of Engineering and Technology (BUET) in September, 2017. After my graduation, I worked as a software engineer at Works Applications, Singapore, and then as a full-time research assistant at the Department of CSE, BUET in collaboration with Samsung Research.

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News:

[May, 2024] Was awarded the John A. Stankovic Graduate Research Award, this award is presented to a UVA CS PhD student with outstanding research productivity in an academic year.
[March, 2024] Conference paper on a cost-efficient, model interference-aware, and scalable deep learning (both CNNs and LLMs) inference serving system got accepted at OSDI 2024 with all-accept reviews in the very first submission attempt!
[September, 2023] Was awarded the University of Virginia Endowed Fellowship, this fellowship is awarded to a graduate student with outstanding research productivity (proposal, publications, and presentations) and awards/honors.
[May, 2023] Conference paper on an efficient end-to-end DNN inference serving system was accepted at SIGCOMM 2023! This was a dream project for me! Really happy it ended so well!
[May, 2023] Will be working on the DeepSpeed project at Microsoft Research during this summer!
[April, 2023] Was awarded NSF travel grant to present paper at IPDPS 2023!
[January, 2023] Conference paper on large-scale distributed COVID-19 spread prediction system was accepted at IPDPS 2023!
[October, 2022] Conference paper was accepted at IEEE BigData 2022!
[September, 2021] Conference paper was published at IEEE CLOUD 2021!
[April, 2021] Conference paper was accepted at IEEE SECON 2021!
[September, 2020] Journal paper was accepted at Elsevier Smart Health 2021!
[Feabruary, 2020] Conference paper was accepted at LREC 2020!
[January, 2020] Conference paper was accepted at ICASSP 2020!
[June, 2019] Was awarded ACL travel grant to present paper at NAACL!
[February, 2019] Conference paper was accepted at NAACL 2019!
[September, 2018] Journal paper was published in Journal of Network and Computer Applications (JNCA), Elsevier (Volume 124, 15 December 2018, Pages 44-62) (Journal Impact Factor: 6.281). Find it here: Paper Link.
[August, 2018] Started working as a Research Assistant at Department of Computer Science and Engineering (CSE) of Bangladesh University of Engineering and Technology (BUET). Our research project is being funded by Samsung Research, South Korea.