Computer Science · Machine Learning Enthusiast
Machine Learning · Systems · Arizona State University
01 / About
I'm a Computer Science student at Arizona State University with a 4.0 GPA, focused on building machine learning systems from first principles. I care deeply about understanding architectures beyond surface-level implementation — from attention mechanisms to optimization dynamics. My goal is to design intelligent, scalable systems that create meaningful real-world impact.
Currently pursuing a B.S. in Computer Science at Arizona State University. Open to internships, research roles, and collaborative projects.
Current Focus
02 / Projects
A selection of projects spanning ML, systems, and web. Add more in lib/data.ts.
Implemented a multi-layer decoder-only transformer in PyTorch from first principles, including embeddings, multi-head self-attention, feedforward blocks, and layer normalization. Built a full training pipeline with batching, optimization, evaluation, and autoregressive text generation. Conducting experiments on training dynamics and generalization behavior.
Developed an interactive web application for real-time object detection on images and videos using YOLOv8 and OpenCV. Includes adjustable confidence thresholds, model size selection, and visual comparison tools for experimentation and performance analysis.
Built an LSTM-based time-series model predicting next-day stock direction using nine engineered technical indicators (RSI, MACD, Bollinger Bands). Implemented a custom loss function optimizing for trading profitability and applied time-series cross-validation, achieving 55% directional accuracy and 1.28% MAE.
Built a full-stack web application featuring a real-time 3D globe interface with location-based intelligence panels. Users can explore cities and countries to access structured news aggregation, live weather data, and publicly available webcam feeds. Developed with a modular React frontend and Node.js/Express backend including API integration, caching, and rate limiting.
AI-powered personal life management web app built with Next.js 16, TypeScript, and Tailwind CSS. Features four modules: a smart scheduler with calendar view and AI-generated time-block plans, a spend tracker with budget alerts and AI roast reports, a Health OS tracking workouts, nutrition, sleep, and mental wellness, and a CS Learning Tracker with resource management and AI study plans. Powered by five specialized Llama 3.3 agents (via Groq) for domain-specific insights across each module. Includes a badge/achievement system, shareable badge cards, and is deployed as a PWA installable on mobile.
03 / Achievements
Academic recognition, competitions, and certifications.
Modeled probability of default on a loan portfolio and applied dynamic programming techniques to categorize FICO scores for predictive modeling.
Dec 2025
Maintained a 4.0 (4.2 internal) GPA during first semester (Fall 2025) in Computer Science.
Dec 2025
Completed certifications in Foundation Models & LLMs, Introduction to GenAI, and Prompt Engineering.
Nov 2025
Completed project-based certification focused on structured problem-solving, process optimization, and analytical decision-making.
Dec 2024
Completed certification covering risk assessment principles, financial modeling fundamentals, and quantitative evaluation techniques.
Dec 2024
School Rank 1 · Zonal Rank 20 (Maharashtra & Goa) · International Rank 20.
2017
Achieved top performance in national-level computer science competition.
2014-15
04 / Skills
Languages
Machine Learning
Tools & Systems
05 / Contact
I'm open to internships, research collaborations, and interesting side projects. The best way to reach me is by email — I try to respond within a day.
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