University Lecturer & Applied AI Researcher
Researching Multi-Agent Architectures and How Agents Behave Under Adversarial Pressure — Memory Poisoning, Retrieval Attacks, and What the Defenses Cost in Accuracy and Compute.
I research memory in LLM agent systems — how persistent memory behaves under adversarial pressure, and what defending it costs in accuracy and compute. I lectured in computer science and data science at Monroe University, 2025–2026.
I hold an M.S. in Data Science from Montclair State University, New Jersey, USA, and worked as an AI researcher in its Data Science Lab, focused on multi-agent AI, RAG, and graph & vector databases.
Memory poisoning, defense composition, and the accuracy and compute cost of defending agent memory.
Hybrid search, agent orchestration, and evaluation design for high-stakes domains.
Mentored undergraduate and graduate students in computer science and data science at Monroe University, 2025–2026.
Applied AI, forecasting, and analytics case studies.
Monroe University, New Rochelle, NY, USA
Sep 2025 — Jul 2026
Teaching undergraduate and graduate courses in computer science, data science, and database systems. Designed Python and SQL lab curricula for 100+ students per semester.
Sentari AI, New York, NY
Jun 2025 — Dec 2025
Translated business requirements into technical specifications for an AI product team; contributed to a 15% improvement in feature-delivery velocity.
Data Science Lab, Montclair State University, New Jersey
Jan 2024 — May 2025
Built a multi-agent RAG chatbot for pharmaceutical inventory and compliance decision-support, reaching 97–99% retrieval accuracy in evaluation.
Montclair State University, New Jersey
Focus: multi-agent retrieval architectures and tool calling.
Institute of Engineering and Management, Kolkata
AUG 2016 — JUL 2020
Focus: algorithms, data structures, software engineering, databases, and networks.