My research develops AI systems for decision-making under uncertainty, with applications in pricing, healthcare, transportation, digital platforms, and enterprise AI.
Research & Engineering
Decision Intelligence
Optimization and learning for pricing, resource allocation, recommendations, treatment selection, and routing under uncertainty.
Reinforcement Learning
Contextual bandits, policy optimization, online learning, and adaptive systems for sequential decision-making.
LLM Systems
Prompt optimization, retrieval-augmented generation, alignment, and evaluation infrastructure for large language models.
Production AI
End-to-end ML pipelines, deployment patterns, monitoring, experimentation, and scalable infrastructure.
Industry and Applied Collaborations
My industry and applied research experience includes work with Nvidia, Apple, Citadel, State Street, Headspace, TransUnion, Grainger, CMS, Texas Instruments, Xerox PARC and Encord across finance, healthcare, retail, transportation, and digital platforms.
Selected Evidence
- 50+ peer-reviewed publications across machine learning, optimization, healthcare, transportation, and AI systems.
- 9 issued US patents and 3 pending patents in transportation, recommendation, and inference systems.
- 200+ videos, 1000+ subscribers, 60,000+ views, and 5000+ hours of watch time on YouTube.
- 50+ research-level student projects, with several becoming papers.
Ways We Can Work Together
- Industry advisory on AI strategy, technical due diligence, and architecture review.
- Executive education through custom workshops on AI systems and MLOps.
- Invited talks and technical presentations.
- Research collaboration on decision intelligence, LLM systems, or optimization.