Software, Machine Learning,
& Artificial Intelligence
M.S. Computer Science @ ASU (4.0 GPA) — Building high-performance systems, ML pipelines, and full-stack applications.
Who I Am
M.S. Computer Science
Arizona State University
GPA: 4.00
I'm a Software Engineer pursuing my M.S. in Computer Science at Arizona State University with a perfect 4.0 GPA. My work spans across distributed systems, ML pipelines, and full-stack engineering.
From architecting inference servers at BARC handling 100K+ requests, to building event-driven microservices at Tikaj, I bring a systems-thinking approach to every problem. I thrive at the intersection of performance-critical backends and intelligent data systems.
When I'm not engineering systems, I'm exploring quantitative finance, competitive programming on LeetCode, or contributing to open-source projects.
AI & ML
Languages
Cloud & DevOps
Web & Data
Where I've Worked
Bhabha Atomic Research Center (BARC)
Research Project Intern
- Architected ML inference pipelines via Triton Inference Server and Docker to handle 100k+ requests with 99.9% uptime
- Optimized neural models with TensorRT, boosting inference speed by 40% and cutting latency to ~0.2s on 1.2M images
- Built an NLP data pipeline using LLMs and Fairseq, generating 50k+ synthetic samples and improving BLEU score
Tikaj
Full Stack SDE Intern
- Built event-driven systems using RabbitMQ and MongoDB, scaling sequential data processing for 1,000+ sources
- Integrated Redis caching to reduce database reads by 60%, achieving sub-0.2s latency for high-traffic APIs
- Implemented real-time notification pipelines, delivering instant alerts across 1,000+ data watch sources
IIIT Vadodara
Research Intern
- Built a RAG-based code security analyzer using LLMs to detect OWASP Top 10 vulnerabilities across 5+ repos
- Designed a document ingestion pipeline parsing 10,000+ lines of code into vector embeddings
- Achieved 82% precision on injection and authentication-related OWASP issues
Extent
Frontend Developer Intern
- Developed 6 pixel-perfect React and TypeScript dashboards, cutting bug resolution time by 10%
- Built responsive SASS web applications ensuring cross-device compatibility across 3 breakpoints
- Refactored frontend architecture to improve reusability, reducing duplication by 25% across 6 dashboards
What I've Built
TCP Message Queue
A high-performance Rust TCP broker built with Tokio, sustaining 10+ Gbps throughput and 100+ concurrent connections with zero-copy fan-out.
- ▸10+ Gbps throughput, 100+ concurrent connections
- ▸87% memory reduction via zero-copy fan-out
- ▸40% faster parsing with 32-byte binary protocol
Credit Card Fraud Detection
End-to-end ML pipeline on IEEE-CIS dataset (1.1M rows). GNN on transaction-identity edges achieved 84% recall and $68.1M projected savings.
- ▸97.50% accuracy with LightGBM on 1.1M rows
- ▸GNN boosted recall to 84%, FDR down to 12%
- ▸$68.1M projected savings from fraud detection
URL Shortener
High-performance Go/Fiber REST API with Redis caching and rate limiting. Sub-50ms resolution for 5,000+ daily users with real-time analytics.
- ▸Sub-50ms link resolution for 5,000+ daily users
- ▸Configurable TTL-based link expiration
- ▸Real-time click analytics for 10,000+ links