I’m an incoming Master’s student in Computer Science and Engineering at UC San Diego, specializing in Distributed Systems. I have hands-on experience working on scalable and resilient systems, including development of Flotilla, a modular federated learning framework, during my time at the Indian Institute of Science. While working on Flotilla, I became especially interested in the challenges of fault tolerance, consistency, and recovery in distributed systems, areas I’m excited to explore further. My broader interests span distributed computing, systems programming, and computer networks.
Used extensively in development of Flotilla and various personal projects
Used heavily across jobs and personal projects
Daily use across work and personal setups (Arch BTW😝)
Daily driver, with custom plugins developed for specific workflows
Integrated into a custom distributed framework using ProtoBuf definitions
Used while building a custom distributed framework and homelab projects
Built a simplified version in Python to understand the internals
Implemented a basic version in Python to understand internal mechanisms
Explored through personal projects focused on distributed systems
Built CNNs, LSTMs, and custom dataloaders for a custom federated learning framework
Used to write custom NeoVim plugins and enhance editor behavior
Used during an internship while working with NoSQL data models
Incoming graduate student at UCSD, specializing in Distributed Systems
GPA: 3.96/4.00Achievements:
Academic scholarship for securing 2nd rank out of 60+ students
Relevant Courses:• Operating Systems• Computer Networks• Cloud Computing• Big Data AnalyticsProjects:
• BitTorrent Client: Built a peer-to-peer file-sharing client using Python’s AsyncIO and BitTorrent protocol with a custom Bencode parser
• GIST: Developed a YouTube video summarizer using NLTK, BART model, SQLite, and Tkinter
Responsibilities include:
Volunteering:
Responsibilities include:
Responsibilities include:
We introduce Flotilla, a flexible and lightweight FL platform designed for real-world edge environments, offering modular strategy support, asynchronous updates, and high fault tolerance. It runs efficiently on edge hardware like Raspberry Pi and Jetson, outperforming or matching top frameworks like Flower, OpenFL, and FedML, while scaling seamlessly to 1000+ clients.
Currently reading: A Wise Man’s Fear and Thinking, Fast and Slow
Just enjoy hitting the ball around and having a good time with friends
Following F1 races, team strategies, and technological advancements
Running PiHole and PFSense, experimenting with network setups
Designing and printing 3D models for personal projects or prototyping
Stargazing and exploring celestial bodies, learning about the universe