Pradeep Shetty

About Pradeep Shetty

Academically trained data scientist and AI leader with 19+ years in Industrial AI—from energy and manufacturing to APM and digital twins. I design and deploy Generative AI Agentic frameworks, Physics Foundation Models, Equipment Foundation Models, Time Series Foundation Models, Proxy / Surrogate models to solve real operational problems and unlock digital transformation and value-chain optimization.I’m a hands-on builder: I prototype fast, run ablations, and push new architectures, tokenization strategies, and fine-tuning methods. I also design agentic frameworks—multi-agent systems that orchestrate tool use, retrieval, simulators, code execution, and workflows—and build Deep Research Agents that read across P & IDs, SOPs, RCAs, and time-series to produce evidence-backed, auditable recommendations.I build the data + knowledge layer that makes AI useful in industrials: LLM-ready data ecosystems, knowledge graphs and ontologies driven by Industry standards, and document/time-series fusion (P & IDs, SOPs, RCAs, alarms), with governance and evaluation—so models and agents are accurate, explainable, and production-ready.Functional impact includes Operations & Maintenance, operations planning/MRP, supply chain & inventory, APM/prognostics & health management, physics-informed AI, and domain-grounded FM design—delivered via scalable cloud-native productization. I’ve led global data science teams, shaped AI strategy, and translated AI into digital revenue growth—from architecture and system design through end-to-end product delivery.Focus: Turning GenAI, agentic systems, and domain foundation models into measurable, evidence-grounded outcomes—safely, reliably, and at scale.

Experience

1. Ai Advisor Digital Ops Ai Program

   SLB

   Oct 2025 — Present · Houston, TX, US

   AI Advisor and Program manager for Digital Operations at SLB, leading the strategy and execution of AI capabilities for production plant operations across upstream and downstream. I drive a portfolio that includes Generative AI Agents, Proprietary Foundation Models Research, digital twins, physics-informed AI systems, foundation-model-enabled workflows, AI-powered simulators, workflow optimization for asset performance.I focus on turning complex operational problems into deployable AI products — establishing high-level direction, guiding architecture and governance, and ensuring solutions scale with reliability and measurable impact.

Education

• National Institute of Technology Karnataka

  BE

• Indian Institute of Science (IISc)

  MS(eng), Statistical Learning, AI

• Indian Institute of Science (IISc)

  PhD, Machine Learning, AI

Skills

• Matlab
• Simulations
• Machine Learning
• Statistical Inference
• Energy
• Distributed Systems
• Research and Development (R&D)
• Mathematical Modeling
• Image Processing
• Stochastic Modeling
• R&D
• Modeling
• Fortran
• Data Mining
• Software Engineering
• Computer Vision
• Software Development
• Latex
• Algorithms
• Artificial Intelligence
• Time Series Modeling
• Data Analysis
• Smart Grid
• Statistics
• Computer Science
• Optimization
• Analytics
• R
• Statistical Modeling
• Time Series Analysis
• Predictive Analytics
• Embedded Systems
• Big Data
• Energy and Smartgrids
• Control Systems Design
• Signal Processing
• In-Memory Analytics
• Simulink
• Pattern Recognition
• Statistical Signal Processing