I am currently a Machine Learning Engineer at Machine Medicine. Previously, I have worked as a Research Specialist at NU Earth, as an Applied Scientist at Alchera Labs, and as a Researcher at CIERA.

My research interests lie broadly in Machine Learning, Deep Learning, and Reinforcement Learning. More specifically, my primary research interest is in the science of deep learning, i.e., understanding the underlying behavior and function of neural networks through empirical experiments and foundational theory, and using this knowledge to develop more intelligent systems. Additionally, I am also interested in integrating machine learning algorithms into the scientific development process across various disciplines such that it would help expedite the pace of scientific research.

I completed my M.S. in Computer Science from Northwestern University and my B.Tech. in Computer Engineering from K.J Somaiya College of Engineering.

In my free time, I love to try out new dishes and restaurants, play tennis, read manga/manhwa, and travel/explore new places (Check out my travel map).

My CV can be found here. Please drop me an email if you have any questions related to my research or if you are interested in a research collaboration.

Education

Northwestern University
M.S. in Computer Science
Sep 2019 - Mar 2021

CGPA: 4.0/4.0
Coursework:

• Fall’19: CS349-Machine Learning, DS421-Statistics, CS496-Data Science Seminar, CS348-Intro to AI
  
• Winter’20: CS496-Advanced Deep Learning, EE435-Deep Learning Foundations
  
• Spring’20: CS397-Statistical Language Modeling, CS336-Algorithms
  
• Fall’20: MSIA490 - Social Network Analytics

Labs/Reading Groups: Research in Automated Listening Methods Lab (REALM), Modern Artificial General Intelligence and Computer Systems Lab (MAGICS), AI Journal Club

K.J Somaiya College of Engineering
B.Tech. in Computer Engineering
Aug 2015 - May 2019

CGPA: 8.99/10
Relevant coursework: Artificial Intelligence, Machine Learning (Topper), Neural Nets, Image Analysis (Topper), Fundamentals of Programming (10/10, AP), Data Structures, Algorithms, Computer Architecture (10/10), Operating Systems (Topper)
Activities: Computer Society of India

Experience

Machine Medicine
Machine Learning Engineer
Sep 2024 - Present

Responsible for research, development, and productionization of machine learning algorithms for neurological disorders.

Aalto University
Academic Visitor
May 2024 - Present

Studying the memorization properties of deep neural networks.

NU Earth
Research Specialist
Nov 2022 - Apr 2024

• Developed machine learning approaches for detecting small seismic events in noisy urban environments.
• Developed an algorithm for the problem of Electrical Impedance Tomography, aimed at optimizing sensitivity volume by efficiently selecting a small subset of rows from a large matrix.
• Developed Earthtunes, a mobile app which allows users to listen to normally inaudible sounds within the Earth.
• Developed an analytical framework to analyze seismic events on Mars.
  • Git repository: Marsquakes
• Developed Pysmo, a modular Python framework for seismology.
  • Git repository: pysmo

Alchera Labs
Applied Scientist
Jul 2021 - Oct 2022

• Developed FireScout, an early detection system for wildfires which can detect wildfire smoke with 91.6% accuracy.
  • Paper: Image-based Early Detection System for Wildfires
• Researched the emergence and importance of class-selective neurons during the early epochs of training and demonstrated through a set of experiments that class selectivity is essential for successful training.
  • Paper: On the special role of class-selective neurons in early training
  • Git repository: Class Selective Neurons

CIERA
Researcher
Jun 2020 - Jun 2021

I was a part of Prof. Vicky Kalogera’s Research Group and was responsible for developing Machine Learning algorithms and applying ML across different projects.

Earthquake Detective:
Advisor: Prof. Suzan Van Der Lee
We compiled the first-ever ML benchmark dataset on potentially triggered seismic events and developed a ML algorithm which can detect these low-amplitude signals with high accuracy.
Git repository: Earthquake Detective
Website: Earthquake Detective crowd-sourcing platform
Paper: Applying Machine Learning to Crowd-sourced Data from Earthquake Detective

Northwestern University
Graduate Research Assistant
Jan 2020 - Jun 2020

Advisor: Dr. Prem Seetharaman
We developed OtoWorld, an interactive environment for training reinforcement learning agents for the task of audio separation. The environment is designed to facilitate reinforcement learning research in computer audition.
Git repository: OtoWorld
Paper: OtoWorld: Towards Learning to Separate by Learning to Move

K.J Somaiya College of Engineering
Research Intern
Jan 2018 - Apr 2018

Advisor: Prof. Grishma Sharma
Researched different methodologies of k-shot learning for facial recognition system. We developed a facial recognition system which can be trained on a small number of samples (k samples) to perform fast and accurate recognition of faces.
Paper: k-Shot Learning for Face Recognition

Accelo Innovation
Machine Learning Intern
Aug 2017 - Oct 2017

Responsible for developing lane detection, object detection, and depth mapping modules for Accelo’s assistive driving system.

Computer Society of India
Student Representative
Mar 2016 - Jul 2017

• Created technical content for workshops and coding questions for competitions
• Taught in Machine Learning and Crytography workshops
• Managed over 20+ events and seminars

Travel Map

A travel map showcasing all the countries I have been to!

Total countries visited: