Pradyumna Sridhara

Graduate Student Researcher, MS in Computer Science, UC San Diego

I'm a second year Master's student specializing in Machine Learning Systems, with the Computer Science and Engineering Department at the University of California - San Diego (UCSD), advised by Prof. Arun Kumar. Prior to this, I obtained my B.Tech. from PES University (Bengaluru, India), majoring in Computer Science with a minor in Business Administration.

When I'm not in the lab, you can find me out on a trek somewhere, filming nature. Or perhaps, riding my motorcyle with the wind in my hair! Sometimes I just stay at home and cook up a nice Indian meal to binge watch a romcom with.


My research interests lie at the intersection of Machine Learning and Software Systems (i.e. ML Systems). I develop algorithms, build platforms and infrastructure that scales end-to-end Machine Learning pipelines. In doing so, I hope to improve the productivity of Data Scientists and ML Engineers, and at the same time, make machine learning more accescibile to the everyday user by reducing costs and human effort. My expertise lie in software systems, cloud computing, distributed computing, and deep learning.

I'm currently working on Cerebro - a distributed deep learning framework that offers effecient model selection pipelines for scalable Deep Learning on multi-node multi-GPU clusters. A copy of my Master's research thesis can be found here.

Publications and preprints

Learning from Mistakes - A Framework for Neural Architecture Search
Bhanu Garg*, Li Zhang*, Pradyumna Sridhara, Eric Xing, Pengtao Xie
Association for the Advancement of Artificial Intelligence (AAAI ), 2022
project page / arXiv / code / bibtex
Bodhisattva: Rapid Deployment of AI on Containers
Shreyas S. Rao, Pradyumna S, Subramaniam Kalambur, Dinkar Sitaram
IEEE International Conference on Cloud Computing in Emerging Markets
), 2018
project page / arXiv / code / bibtex
xBridge - A Microservices-Based Smart IoT Gateway System
P Sridhara, N Kamath, S Srinivas
Smart Intelligent Computing and Applications
(Springer SCI
), 2018
project page / arXiv / code / bibtex

Work Experience

Rakuten Americas
San Mateo, California
Jun 2021 - Sep 2021 · 4 mos
Big Data and Cloud Engineering Intern
• Designed a BigQuery solution to host and analyze data quality reports of the Rakuten Catalog Platform team. Integrated the BQ data with Google DataStudio to showcase visual trends. This has been pushed to production.
Cisco Systems
Bengaluru, India
Jul 2018 - Jan 2021 · 2 yrs 8 mos
Software Engineer II
• Technical Lead for a MeanStack solution delivering 560K+ historical contract images, invoices and orders to Cisco Partners. It is being used as the de facto tool for all Software-IT use cases. Deployed to production in 2020.
• Worked on optimizing HPA in Kubernetes. Achieved better REST call failure rates in Cisco production environments using Liveness and Readiness Probes.
• Designed and delivered a zero-fault image migration system for 70K+ of Cisco’s highly critical networking firmware images, playing a key role in all Cisco firmware image downloads. Deployed to production in 2019.
Cisco Systems
Bengaluru, India
Jan 2018 - Jun 2018 · 6 mos
Software Engineering Intern
• Worked on BotLite – a chatbot creation framework developed by Cisco. My primary focus was on making the chatbots more human-like by enhancing its natural language understanding capabilities using
Analog Devices
Bengaluru, India
Jun 2017 - Aug 2017 · 3 mos
IoT Applications Intern
• Designed and developed a cross-platform, multi-protocol smart IoT Gateway system that supports cloud platform compatibility across Cloud Service Providers and fast horizontal scalability across radio-frequency protocols.
• The device was used to demo Analog Devices' flagship Structural Health Monitoring system at The IoT Solutions World Congress 2017, Barcelona.
• The work was published at the General Technical Conference, 2018 – Analog Devices’ top technical conference.
• In active use from 2017-2019 at Analog Devices.


Certified Kubernetes Administrator
Cloud Native Computing Foundation, 2020
Credential ID: LF-yj08g82ocj


DSC 102 Systems for Scalable Analytics by Prof. Arun Kumar
University of California San Diego, Winter 22
Teaching Assistant
CSE 21 Mathematics for Algorithms and Systems by Prof. Miles Jones
University of California San Diego, Fall 21
Teaching Assistant


You're very welcome to contact me regarding my research or for job oppurtunities. You can reach me at prsridha [at] ucsd