I joined Harvey Mudd College’s Computer Science department in Fall 2022. This past spring, I taught Internet & Society (CS 181AQ) through the Inside Out Prison Exchange Program, as well as Computer Systems (CS 105). I am broadly interested in systems and networking, and my research focuses on lowering the energy consumption of computer systems, from the internet to machine learning applications. Before joining HMC, I finished my Ph.D. at UCLA, where I was advised by Harry Xu and Ravi Netravali. Prior to UCLA, I was a software engineer at Microsoft for three years, and before that, I received a B.A. in Computer Science from Pomona College in 2014.

Teaching

Current Courses:

• Computer Systems (CS 105) - Spring 2025, Fall 2024
• Internet & Society (CS 181AQ), through the Inside Out program - Spring 2025

Past Courses

• Network Algorithmics (CS 181AG) - Fall 2024, Fall 2022
• Principles of Computer Science (CS 60) - Spring 2024, Fall 2023
• Machine Learning System Design (CS 181AI) - Spring 2023

Research

TinyML

My students and I are working on running machine learning on extremely low power devices (in the mW range).
• In December, Sean Nian (SJSU ’24) presented the results of his project from last summer with Ket Hollingsworth (HMC ’25) and Alan Gutierrez (HMC ’26) at INTERACT at SEC (Symposium of Edge Computing) in Rome. Their work analyzed the network overhead of running TinyML in a distributed setting.
• Diya Gangwar (HMC ’26) and Angelina Tsai (HMC ’26) did an independent study where they ran a small ML model on a solar-powered ESP32

Sustainable Computing

We are also studying how to lower the carbon footprint of commonly used websites.
• Last summer, Grace Everts (HMC ’26) did a study to better understand user tolerance for aesthetic changes that lower the carbon footprints of websites. Her work is in submission, and a visual representation of her study was accepted to Issue 9 of the Branch magazine: A Just and Sustainable Internet for All

Publications

• Ket Hollingsworth, Sean Nian, Alan Gutierrez, and Arthi Padmanabhan. An Analysis of Network Overhead in Distributed TinyML. In the Proceedings of the 1st Workshop on Communication and Networking for TinyML based Consumer Applications (INTERACT at SEC 2024).
• Sifat Ut Taki, Arthi Padmanabhan, and Spyridon Mastorakis. FusedInf: Efficient Swapping of DNN Models for On-Demand Serverless Inference Services on the Edge. In the Proceedings of the 9th IEEE/ACM Symposium on Edge Computing (SEC 2024).
• Shan Yu, Zhenting Zhu, Yu Chen, Hanchen Xu, Pengzhan Zhao, Yang Wang, Arthi Padmanabhan, Hugo Latapie, and Harry Xu. VQPy: An Object-Oriented Approach to Modern Video Analytics. In the Proceedings of the 7th Annual Conference on Machine Learning and Systems (MLSys 2023).
• Arthi Padmanabhan*, Neil Agarwal*, Anand Iyer, Ganesh Ananthanarayanan, Yuanchao Shu, Nikolaos Karianakis, Harry Xu, and Ravi Netravali. Gemel: Model Merging for Memory-Efficient Real-Time Video Analytics at the Edge. In the Proceedings of the 20th USENIX Conference on Networked Systems Design and Implementation (NSDI 2023).
• Arthi Padmanabhan, Anand Iyer, Ganesh Ananthanarayanan, Yuanchao Shu, Nikolaos Karianakis, Harry Xu, and Ravi Netravali. Towards Memory-Efficient Inference in Edge Video Analytics. In the Proceedings of the 3rd ACM Workshop on Hot Topics in Video Analytics and Intelligent (HotEdgeVideo 2021). [ PDF ]
• Yuanqi Li*, Arthi Padmanabhan*, Pengzhan Zhou, Yufei Wang, Harry Xu, and Ravi Netravali. Reducto: On-Camera Frame Filtering for Resource-Efficient Real-Time Video Analytics. In the Proceedings of the Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication (SIGCOMM 2020). [ PDF ]
• Arthi Padmanabhan, Lan Wang, and Lixia Zhang. Automated tunneling over IP Land: run NDN anywhere (poster). In the Proceedings of the 5th ACM Conference on Information-Centric Networking (ICN 2018). [ PDF ]