Pradeep Reddy R.

About Pradeep Reddy R.

AI / ML Architect | Clinical Data Automation | LLMs in Regulated Systems | 15+ Years in Healthcare AIAI architect and data scientist with 15+ years of experience building machine learning systems and automation platforms in healthcare, life sciences, and enterprise analytics.My work focuses on applying AI in regulated environments—where accuracy, traceability, and validation are as critical as model performance. I specialize in designing end-to-end systems that connect data engineering, machine learning, and operational deployment into scalable production workflows.Across industry and academia, I have led initiatives spanning clinical data automation, neuroimaging biomarkers, predictive modeling, and enterprise ML infrastructure.## Areas of Expertise• AI and LLM applications in regulated environments (GxP, clinical data workflows)• Machine Learning, Deep Learning, and statistical modeling• Clinical data systems and healthcare analytics• Medical imaging and computer vision• Large-scale data pipelines and predictive modeling• MLOps, ML platform architecture, and production deployment• Open-source scientific software and reproducible research## Selected Career Highlights• Designed automation pipelines for enterprise clinical data operations, significantly reducing manual effort and accelerating study setup timelines• Led development of neuroimaging biomarkers for early detection of Alzheimer’s and Parkinson’s disease• Built predictive models for consumer behavior and market analytics supporting multi-million-dollar strategic decisions• Led cross-functional teams delivering scalable production ML systems across research and enterprise environments• Published 21+ peer-reviewed articles and delivered 45+ invited talks• Coordinated international multi-site collaborations advancing open science and reproducible research## Technical StackPython • PyTorch • TensorFlow • SQL • ML pipelines • Data engineering • AWS / GCP • Scientific computingInterested in building responsible AI systems that translate complex data into real-world clinical and business impact.

Experience

1. Director, Data Science & Operations

   Eisai US

   Sep 2025 — Present

   Enterprise AI Architect – Clinical Data Science and Automation- Designed and implemented AI-driven automation pipelines for clinical data workflows in regulated environments, reducing manual effort by ~80% and accelerating study build timelines- Developed automated pipelines for change-impact analysis and related processes supporting Computer Systems Validation (CSV) and regulatory compliance- Lead architecture and solution design for AI systems including data pipelines, model deployment, monitoring, and governance- Build internal AI capabilities for secure processing of sensitive clinical documents, enabling scalable automation while maintaining regulatory and data privacy requirements- Establish platform standards and frameworks enabling responsible adoption of AI across clinical data operations (e.g, CDISC, SDTM etc)

Education

• Sri Venkateswara University

  B.S, Mathematics, Physics, Computer Science

  2000 — 2003

• Simon Fraser University

  Ph. D, Biomedical Engineering

  2008 — 2014

• Indian Institute of Technology, Madras

  M.S, Physics

  2003 — 2005

Skills

• Machine Learning
• Pattern Recognition
• Image Processing
• Medical Imaging
• Biomedical Engineering
• Matlab
• Latex
• R
• Signal Processing
• Programming
• Feature Selection
• C++
• Python
• C
• Java
• Statistical Modeling
• Data Analysis
• Microsoft Office
• Mathematical Modeling
• Computer Vision
• Statistics
• Data Mining
• Computer Science
• Medical Image Analysis
• Image Analysis
• Sql
• Numerical Analysis
• Statistical Learning
• Alzheimer's Disease
• Differential Diagnosis
• Feature Extraction
• Digital Signal Processing
• Magnetic Resonance Imaging
• Data Visualization
• Linux
• Scientific Computing
• 3d Visualization
• Digital Image Processing
• High Performance Computing
• Image Segmentation