• Bachelor of Technology in Computer Science at Vellore Institute of Technology, Chennai, India (2024)
• Master of Applied Computer Science at Concordia Univeristy, Montreal, Canada (Expected 2026)
• Have a deep interest in Software Development (React/TypeScript & Java/.NET), ML model development and fine-tuning
Development Practices: Agile (Scrum), CI/CD, OOD, Data Structures, Design Patterns, Unit Testing, Software Testing
Expertise: NLP, Computer Vision, Deep Learning, AI, Generative AI, MLOps, LLMs, Fine-Tuning
LeetCode: 163 problems solved (102 medium and hard problems)
• Research Intern under a professor at University of Technology Sydney (Machine Learning and Natural Language Processing)
• Teaching Assistant at Concordia Univeristy for the course of COMP 249 (Object Oriented Programming II)
• TubeLytics - A Full stack web application using the Play Framework and Java for backend scraping live data from the Youtube API and making an analysis on the same. Full test coverage with Jacoco by performing JUnit testing and using Mockito for mocking API calls.
• Full stack finance system using React and TypeScript Frontend with .NET in the backend connect to SQL server. External API calls with axios, JWT based authentication. Docker for containerization and Gitlabs for CI/CD pipelining.
• Ptorts - A social media style web application for PETS. MERN stack with Firebase for storing videos and images.
• Automatic Speech Recognition in Indic Languages with enhanced Spell Checker using Masked Language Modelling - Finetuning of the whisper model from OpenAI for low resource Indian Languages and improving on the accuracy by error rectification through a masked language model.
• Argumentation Analysis On Twitter and YouTube Comments Based On Social Events Using Ensemble Learning Of Language Models - Manually extracted about 3000 comments from Twitter and Youtube and annotated using a team led by me. Then the tweets and comments were classified for nine different attributes for predictions and trained using 3 different models from hugging face and then ensembled for the final predictions.
• Hacknight Hackathon - Finalist in a Hackathon on the creation of a Full stack website making use of Polygon Matic Tokens (Cryptocurrency) using MERN stack and Firebase
• Scored 100% in class 10 Mathematics and achieved a certificate of recognition for being a part of the top 0.01% of the students.
