Research

Research Areas

• Creative Generation — poetry, narrative, and expressive AI
• Sanskrit Computational Linguistics — cross-lingual semantics, summarization, linguistic tools
• Multi-Agent Systems — reasoning, debate, simulation, and decision-making frameworks

Motivation & Vision

I aim to explore the full breadth and depth of AI, with a long-term focus on building multi-agent systems capable of robust reasoning, collaboration, and real-world problem-solving.

Key Research Directions

• Multi-agent frameworks for stock analysis and investment decisions
• Multi-agent legal reasoning and courtroom-style argument simulation
• Cross-lingual summarization for Indic and global languages
• Creative systems for poetry and generative expression
• Cognitive memory evaluation frameworks for LLMs
• Multi-agent debate and self-improvement ecosystems
• Reinforcement Learning for improving Small Language Models

Technical Strengths

• LLM finetuning, RLHF/RLAIF, and model compression (QAT)
• Multi-agent orchestration and agent pipeline design
• IR/RAG pipelines and evaluation frameworks
• Sanskrit NLP tooling (morphology, semantics, sandhi systems)
• Dataset creation, benchmarking, and distributed training
• Cloud compute workflows across GCP/AWS

Research Funding

Google GCP Gemma Academic Program Award (November 2025)

Collaboration Interests

I welcome collaborations in the following areas:

• Multi-agent systems
• Sanskrit computational linguistics
• Creative and multimodal generation
• Academic and industry research partnerships
• Open-source projects
• Dataset and benchmark creation
• Joint grant proposals
• Student mentorship and research guidance

If any of these align with your work, I’d be happy to connect.