IIIT Pune • B.Tech CSE • 2027
Hi, I'm Aditya
Full Stack Developer focused on Machine Learning and scalable systems. I build recommendation engines, data-driven platforms, and intelligent applications.
About Me
Engineer first, researcher close second — here's the short version.
I'm a Computer Science undergrad at IIIT Pune who builds at the intersection of software engineering and machine learning — from recommendation systems that outperform baselines to full-stack data platforms serving real-time analytics.
My approach: take a complex, messy problem, architect a clean solution, then ship it. I care about scalable backends, well-designed APIs, and ML systems that actually work in production — not just in a notebook.
Currently diving deeper into retrieval-augmented generation, embedding-based search, and graph-powered code intelligence systems.
I'm drawn to tools that decode complexity — making large systems legible, navigable, and interactive.
Education
B.Tech CSE — IIIT Pune
Focus Areas
ML Systems • Full Stack • Backend Engineering
Currently Exploring
RAG • Embeddings • Code Intelligence
What I Build
I focus on building systems that combine software engineering with machine learning.
Recommendation Systems
Hybrid ML models combining collaborative filtering and content-based approaches.
Data-Driven Platforms
Applications powered by real-time APIs, analytics, and custom scoring systems.
Scalable Backends
Modular backend architectures designed for performance and scalability.
Intelligent Developer Tools
Exploring RAG-based systems and tools for understanding large codebases.
Highlight
Featured Project
Ludex
Machine Learning / Research
A hybrid recommendation system that fuses content-based filtering with collaborative filtering to deliver highly personalized Steam game recommendations at scale.
The content pipeline leverages TF-IDF vectorization across game metadata, while the collaborative component uses implicit ALS (Alternating Least Squares) to model latent user–item interactions — combining the best of both paradigms into a single, unified ranking system.
Evaluated on a dataset of 57,000+ items and 1,200 users, the hybrid approach significantly outperforms standalone baselines, demonstrating that thoughtful fusion of complementary signals yields measurably better recommendations.
+27%
Precision@20 vs CBF
+13%
Precision@20 vs CF
57K+
Items in Dataset
1.2K
Users in Dataset
Sign In Flow
Dashboard
Projects
Selected work showcasing ML research, data platforms, and full-stack engineering.
Ludex
Machine Learning / ResearchHybrid recommendation engine fusing content-based and collaborative filtering to surface personalized Steam game picks — backed by a published research paper.
- • +27% Precision@20 vs pure CBF
- • +13% Precision@20 vs pure CF
- • 57K+ items, 1.2K users dataset
- • Published research paper
PlayNexus
Full Stack / Data PlatformReal-time Steam analytics dashboard with multi-region price comparison, a custom value-scoring algorithm, and vibe-based game discovery — built for data-driven decision making.
- • Real-time Steam API integration
- • Multi-region price comparison
- • Custom value score algorithm
- • Vibe-based game discovery system
SynthRescue
AI / Computer VisionAI-powered disaster analysis system for detecting structural damage and assisting rescue operations using computer vision and AI reasoning. Designed for real-time decision support in emergency scenarios.
- • Real-time image upload and analysis pipeline
- • YOLO-based structural damage detection
- • AI-generated emergency response reports using Gemini
- • Fault-tolerant fallback system for reliability under failure conditions
- • Designed for rapid deployment in disaster response environments
Sheriff of Nottingham App
Backend / MultiplayerDigital adaptation of the Sheriff of Nottingham board game with a lobby-based multiplayer system, real-time game state management, and turn-by-turn logic.
- • Flask backend with WebSocket support
- • Lobby system for multiplayer sessions
- • Turn-based game state handling
Get In Touch
Feel free to reach out for opportunities, collaborations, or just a conversation.