Prince Modi

Prince Modi

Master’s Student

University of California San Diego

Hi, I’m Prince!

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.

Skills

Proficient
Python

Used extensively in development of Flotilla and various personal projects

Docker

Used heavily across jobs and personal projects

Linux

Daily use across work and personal setups (Arch BTW😝)

NeoVim

Daily driver, with custom plugins developed for specific workflows

Intermediate
gRPC

Integrated into a custom distributed framework using ProtoBuf definitions

MQTT

Used while building a custom distributed framework and homelab projects

Redis

Built a simplified version in Python to understand the internals

Git

Implemented a basic version in Python to understand internal mechanisms

Familiar
Go

Explored through personal projects focused on distributed systems

PyTorch

Built CNNs, LSTMs, and custom dataloaders for a custom federated learning framework

Lua

Used to write custom NeoVim plugins and enhance editor behavior

MongoDB

Used during an internship while working with NoSQL data models

Education

 
 
 
 
 
Master of Science in Computer Science and Engineering

Incoming graduate student at UCSD, specializing in Distributed Systems

 
 
 
 
 
Bachelor of Technology in Computer Engineering

GPA: 3.96/4.00
Achievements: Academic scholarship for securing 2nd rank out of 60+ students
Relevant Courses:
Operating Systems
Computer Networks
Cloud Computing
Big Data Analytics
Projects:
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

Experience

 
 
 
 
 
Research Associate (DREAM: Lab)

Responsibilities include:

  • Built an asynchronous federated learning framework (Flotilla) in Python, optimized for edge hardware deployment
  • Implemented server and client sides using MQTT and gRPC for efficient message passing and coordination in federated learning
  • Designed a custom Redis-based state store with checkpointing to enable recovery from full server failures without data loss or disruption
  • Integrated client selection and aggregation strategies from current research for performance, accuracy, and turnaround optimization
  • Collaborated with PhD students under Prof. Manik Gupta (BITS Pilani) and Prof. Yogesh Simmhan (IISc) to ensure Flotilla’s scalability and reliability
  • Configured and managed an 80+ node edge cluster (Nvidia Jetsons, Raspberry Pis), supporting lab infrastructure and projects including Flotilla

Volunteering:

  • Senior Student Volunteer, Indian Institute of Science – IEEE/ACM CCGrid 2023: Co-organized a 300+ participant conference; coordinated 3 poster sessions and assisted keynote speakers and faculty
  • Student Volunteer, IISc Open Day 2023: Coordinated presentation sessions for DREAM:Lab projects

 
 
 
 
 
Teaching Assistant, Data Engineering at Scale

Responsibilities include:

  • Taught a graduate-level course to a class of 40+ students, comprising topics such as HDFS, Map-Reduce, Apache Spark
  • Facilitated and led a 2-hour lab session per week, prepared and graded assignments, conducted one-on-one office hours, and conducted doubt-clearing sessions

 
 
 
 
 
Software Engineering Intern (Intellza)

Responsibilities include:

  • Developed Intellza, a unified data storage and analytics platform, alongside a cross-functional team
  • Developed and integrated a module to maintain and track schema changes for MongoDB on Intellza using LiquiBase
  • Created Docker images and optimized the existing images as per Docker’s recommendations, reducing the image size to 35% and improving the build times of the project’s CI/CD pipeline by 50%

Hobbies

Reading

Currently reading: A Wise Man’s Fear and Thinking, Fast and Slow

Tennis & Pickleball

Just enjoy hitting the ball around and having a good time with friends

Formula 1

Following F1 races, team strategies, and technological advancements

Home Lab

Running PiHole and PFSense, experimenting with network setups

3D Printing

Designing and printing 3D models for personal projects or prototyping

Astronomy

Stargazing and exploring celestial bodies, learning about the universe