Currently, changing my readme file. Thank you for your patience!

🔬 Researching and building agentic AI systems, LLM inference architectures, and automation-first intelligence pipelines.

My work sits at the intersection of data science, machine learning systems, and autonomous agents, with a strong focus on scalability, evaluation, and real-world deployment.

• Agentic AI & Autonomous Systems

  • Single-agent and multi-agent architectures
  • Tool-using agents (APIs, databases, code execution)
  • Planning, memory, and control loops
  • Agent orchestration and task decomposition

• LLM Inference & Systems

  • Efficient inference (latency, throughput, cost)
  • Model routing and hybrid LLM architectures
  • RAG systems and retrieval strategies
  • Evaluation, benchmarking, and failure analysis

• Applied Data Science

  • Statistical modeling & experimentation
  • Predictive analytics & decision systems
  • Data-centric AI workflows
  • Bridging classical ML with foundation models

• 🤖 AI Agents for complex, real-world workflows
• ⚡ Production-grade LLM inference pipelines
• 🔁 Automation systems with AI-in-the-loop
• 🧠 Hybrid architectures: Classical ML + LLMs
• 📏 Evaluation frameworks for agent behavior

Intelligence is not just model capability — it’s architecture, evaluation, and integration.

I value:

• Reproducibility & clean abstractions
• System-level thinking
• Rigorous evaluation over demos
• Production-aware research

• 🔬 Open to research collaborations in AI agents & LLM systems
• 🧠 Interested in agent evaluation, inference optimization, and applied AI research
• ⭐ If my work helps you, feel free to star or fork a repo