Hey, I'm Kuber Khandare.
I'm a Computer Science & Artificial Intelligence undergraduate who enjoys building intelligent systems, data-driven products, and scalable backend infrastructure.
My interests lie at the intersection of Machine Learning, Generative AI, Distributed Systems, and Full-Stack Engineering. I love working on projects involving LLMs, RAG pipelines, recommendation systems, anomaly detection, time-series analytics, developer tools, and high-performance backend systems.
Whether it's training models, building AI-powered products, designing concurrent systems, or participating in hackathons, I'm always looking for opportunities to solve challenging problems through technology.
"Building systems that learn, reason, and create value."
An AI-powered market intelligence platform that analyzes financial data, insider trading activity, and corporate signals to identify high-probability investment opportunities.
Highlights
- Built data pipelines processing Nifty 500 market data and corporate disclosures
- Developed pattern recognition and signal generation systems
- Implemented anomaly detection and opportunity ranking models
- Integrated LLMs for explainable financial insights
- Designed real-time dashboards for investment intelligence
A scalable infrastructure monitoring and network intelligence system designed for large-scale telemetry collection and security analysis.
Highlights
- High-performance network scanning using Golang concurrency
- Automated scheduling and monitoring pipelines
- Structured telemetry generation for analytics
- Extensible architecture for anomaly detection workflows
An intelligent platform that helps developers discover open-source projects aligned with their skills and interests.
Highlights
- Repository discovery using GitHub APIs
- Intelligent ranking and recommendation workflows
- Personalized onboarding for contributors
- Project matching based on technology preferences
A lightweight system analytics engine for real-time monitoring, process inspection, and historical metric tracking.
Highlights
- Real-time CPU, memory, and process monitoring
- Persistent metric storage and snapshots
- Historical system analytics
- Built in Rust for performance and reliability
- Machine Learning
- Deep Learning
- Generative AI
- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Natural Language Processing
- Recommendation Systems
- Time-Series Analysis
- Anomaly Detection
- Backend Engineering
- Distributed Systems
- Systems Programming
I enjoy rapid prototyping, hackathons, and turning ambitious ideas into working products.
Some domains I've explored:
- Financial Intelligence Systems
- AI-Powered Analytics Platforms
- Infrastructure Monitoring
- Developer Tooling
- Recommendation Engines
- Distributed Systems
- Blockchain Protocols
- Decentralized Applications
- 💼 LinkedIn: https://linkedin.com/in/kuber-khandare-4b40ab27a
- 🐦 Twitter: https://twitter.com/kuberkhandare
- 🌍 Portfolio: https://kuber-portfolio.vercel.app
"The most exciting software doesn't just execute instructions—it learns, reasons, and adapts."