From research to production.

Senior AI/ML Professional with over 5+ years in Data Science, AI, Machine Learning and MLOps across healthcare, automotive and financial services. Currently a Graduate Research Assistant at the University of Maryland, College Park, focused on 7B–70B parameter LLMs and diffusion models for biomedical applications.

Previously, as Senior AI/ML Engineer at Aya Healthcare, I architected production multi-agent LLM platforms processing 2.3M+ patient profiles with 95% clinical accuracy and built scalable RAG infrastructure serving 2,000+ concurrent providers across 15+ hospital networks.

At Bridgestone Group (Azuga Inc.), I led cloud operations, data architecture and MLOps - designing infrastructure that processes 24 billion sensor records (120 PB) with < 60s latency using Apache Spark on 24-node clusters.

Highlights include the Accident Risk Survival Model using Cox regression (C-index 0.78) on 7.8M crash records projecting $122.9M+ savings, NLP sentiment systems, a real-time streaming warehouse with 99.8% data accuracy, and a Generative AI "Chat with Data" initiative powered by LangChain & AutoGen.

My GitHub portfolio (JayDS22) showcases 30+ production-ready projects including the AgentForge Multi-Agent RAG Platform (98.5% success rate, LangGraph orchestration), a Real-Time Recommendation Engine (sub-100ms latency on PySpark + Delta Lake), and a Transportation Demand Forecasting System (MAPE 2.8% with LSTM).

Additional work spans Driver Behavior Analytics using Bayesian hierarchical modeling, a Real-Time Experimentation Platform built on Thompson sampling bandits, and a Marketplace Optimization Engine (Hungarian algorithm + linear programming) at 97.2% matching efficiency.

As an Analytics Engineer at Simplilearn, I built enterprise data pipelines and advised Data Science clients at Purdue and UMass.

Published research includes "Predictive Maintenance in Automotive using Machine Learning" (accepted, IEEE Journal, Feb 2025) and "Optimizing Supply Chain using Data Science and AI" (IJAET, 2023). Earlier work at Dhirtek Business Research applied statistical modeling to liquid biopsy market growth.

I focus on building reliable, production-ready AI - from HIPAA-compliant healthcare systems to real-time fraud detection processing 500K+ daily transactions at 94.2% accuracy. The aim is always the same: scalable systems that deliver measurable business impact under real-world constraints.