Ashish Garg
Senior Product Leader — AI-Driven Enterprise Solutions
United States
Professional Profile
Ashish Garg is a senior product leader and applied AI practitioner with over 15 years of experience designing, operationalizing, and evaluating AI- and ML-driven systems in large enterprise environments. His work spans large language models (LLMs), natural language processing (NLP), machine learning–based forecasting, and causal analytics, with a strong emphasis on production-grade system design and decision support.
He has led the development of enterprise AI platforms that integrate structured and unstructured data across planning, finance, merchandising, and supply-chain domains. His experience includes architecting retrieval-augmented generation (RAG) pipelines, multi-contextual prompting frameworks, ML forecasting systems, and analytics platforms that support explainable, traceable, and scalable decision-making.
His work bridges advanced AI research and real-world deployment, with a focus on methodological rigor, evaluation quality, reproducibility, and practical impact in complex organizational settings.
Areas of Expertise
Large Language Models and Foundation Models; Natural Language Processing; Retrieval-Augmented Generation and Graph-based Retrieval; Machine Learning Forecasting and Time-Series Modeling; Causal Inference and Decision Frameworks; Explainability, Traceability, and Trustworthy AI; Enterprise Decision-Support Systems.
Education
Doctorate in Business Administration (AI & Machine Learning), in progress — Walsh College, United States.
Master of Science in Data Science (Distinction) — Liverpool John Moores University, United Kingdom.
Postgraduate Diploma in Data Science — International Institute of Information Technology, Bangalore, India.
Bachelor of Technology in Electronics and Telecommunication Engineering — Uttar Pradesh Technical University, India.
Selected Scholarly Contribution
Published book chapter in Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 Chapter 5: Using interpretable machine learning to identify factors contributing to COVID-19 cases in the United States.
Professional Profiles
ORCID: https://orcid.org/0009-0003-4402-9593
LinkedIn: https://www.linkedin.com/in/ashish06/