Kaushik Rajan

Engineer, Independent Researcher, and Applied Scientist

Connecting theoretical research with practical application through code and content.

Mission & Method

I identify overlooked problems and build specialized applications to solve them. My approach connects insights from applied research directly with software development, creating practical tools for specific, underserved needs.

Core Research Verticals

Agentic AI & Multi-Agent Systems: Researching autonomous agents and tool integration to perform complex, multi-step tasks.
Reinforcement Learning & Adaptive Systems: Using DRL to build applications that learn from and adapt to user behavior.
Game Theory & Strategic Decision-Making: Applying mechanism design to build platforms for negotiation and social coordination.
Multi-modal Learning & Sensor Fusion: Combining inputs from various sources for context-aware applications.
Privacy-Preserving & On-Device AI: Focusing on federated learning and model compression for private and efficient AI.
Interpretable AI & Causal Inference: Employing techniques to ensure applications are not just accurate, but also transparent and trustworthy.

My work connects theoretical exploration with practical application. This is where insights are translated into code, content, and case studies.

Foundational Research

I publish in-depth articles and papers on reinforcement learning, game theory, and other frontier AI topics that form the basis of my work.

Explore Blog View Publications

Practical Applications

I build and deploy focused web and mobile applications that use my research to solve specific, real-world problems.

View Applications

Share Your Thoughts

I welcome feedback on my work, collaboration proposals, or discussions on future research directions.

I am always interested in connecting with fellow researchers and practitioners in AI.