Syed Mohammed Mustafa Akailvi

Instructed working professionals and executives in Generative AI, LLMs, fine-tuning, RAG, and AI governance using Purdue-affiliated curriculum, achieving >90% satisfaction ratings.

Design and implement enterprise AI solutions and deliver executive/professional AI education; architected a GenAI knowledge platform for an MRPL refinery processing 15,000+ pages with RAG, OCR, and multi-agent validation.

Led design and implementation of an enterprise knowledge platform unifying 30+ years of institutional data with Azure AI, enabling natural-language queries and maintaining production use after departure.

Modernized GCP data infrastructure for Keying & Linking, deploying governed pipelines handling 15+ TB/week and improving entity resolution match accuracy from 3.5% to 70%.

Led DOE-funded R&D for AI-enabled forensic analytics in OT, developed GRR real-time anomaly detection and improved intrusion detection true-positive rate from 60% to 97%.

Applied data-driven root-cause analysis and automation in battery pack manufacturing, preventing defects that saved 20,000 cooling tubes and reducing line interruptions by one-third.

Activities and societies: Dissertation research; publications in IEEE; teaching and research assistant roles.

Doctoral candidate (ABD) in Information Science researching methods to reduce LLM hallucination for factual retrieval in industrial control systems.

Activities and societies: Graduate researcher and teaching assistant; MS thesis on nanocomposite materials (ProQuest 2016).

Completed a Master of Science in Systems Engineering focusing on systems and data-driven engineering approaches.

Activities and societies: Team leader for BTech senior project; involvement in engineering design projects.

Earned a Bachelor of Technology in Mechanical Engineering with senior project leadership on a miniature axial flow turbojet engine.