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United States, India

Biography

My pursuit of achieving academic excellence is what drives me forward in my endeavours. My research interests are primarily Federated Learning, Edge-Computing, Knowledge Distillation, Distributed Systems, Distributed Optimization and Stochastic Optimization. Broadly, I am interested in Neural Networks, AI & ML.

I worked as Project Associate - I at Distributed Research on Emerging Applications and Machines Lab (DREAM:Lab), CDS, IISc Bangalore, after having done my B.Tech. in Computer Science and Engineering from IIT Dharwad (graduated, 2021). I was previously a member of Learning, Inference and Networks (LIaN) research group at IIT Dharwad during my bachelors.

I am currently a master's student majoring in Computer Science at the Viterbi School of Engineering in University of Southern California, Los Angeles, having started in Fall 22.

Activities

Employment (1)

Indian Institute of Science: Bengaluru, Karanataka, IN

2021-08-11 to 2022-07-31 | Project Associate - I (Computational and Data Sciences)
Employment
Source: Self-asserted source
Sai Anuroop Kesanapalli

Education and qualifications (2)

University of Southern California: Los Angeles, CA, US

2022-08-22 to present | Master of Science (Computer Science)
Education
Source: Self-asserted source
Sai Anuroop Kesanapalli

Indian Institute of Technology Dharwad: Dharwad, Karnataka, IN

2017-07 to 2021-06 | Bachelor of Technology (Computer Science and Engineering)
Education
Source: Self-asserted source
Sai Anuroop Kesanapalli

Works (6)

Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models

ACM SIGMETRICS Performance Evaluation Review
2023-06-26 | Journal article
Contributors: Prashanthi S.K; Sai Anuroop Kesanapalli; Yogesh Simmhan
Source: check_circle
Crossref

Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models

2023-06-19 | Conference paper
Contributors: Prashanthi S.K; Sai Anuroop Kesanapalli; Yogesh Simmhan
Source: check_circle
Crossref

Characterizing the Performance of Accelerated Jetson Edge Devices for Training Deep Learning Models

Proceedings of the ACM on Measurement and Analysis of Computing Systems
2022-12 | Journal article
Contributors: Prashanthi S.K; Sai Anuroop Kesanapalli; Yogesh Simmhan
Source: check_circle
Crossref

Don't Miss the Train: A Case for Systems Research into Training on the Edge

2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
2022-05 | Conference paper
Contributors: Prashanthi S. K; Aakash Khochare; Sai Anuroop Kesanapalli; Rahul Bhope; Yogesh Simmhan
Source: Self-asserted source
Sai Anuroop Kesanapalli

Characterizing the Performance of Deep Learning Workloads on Accelerated Edge Computing Devices

8th IEEE International Conference on High Performance Computing, Data & Analytics Student Research Symposium
2021-12 | Conference poster
Contributors: Prashanthi S.K; Sai Anuroop Kesanapalli; Aakash Khochare; Yogesh Simmhan
Source: Self-asserted source
Sai Anuroop Kesanapalli

Federated Algorithm with Bayesian Approach: Omni-Fedge

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
2021-06-06 | Conference paper
Contributors: Sai Anuroop Kesanapalli; B. N. Bharath
Source: Self-asserted source
Sai Anuroop Kesanapalli