Mehrab Tanjim is a Research Scientist II at Adobe Research with a decade of experience bridging scalable machine learning and generative AI, and a PhD in Computer Science from UC San Diego. He leads work on automated optimization of LLM-based agents for reasoning, planning, and decision-making, and built a synthetic data generation framework to address data scarcity in model optimization and evaluation. His prior contributions include productionized query understanding and disambiguation techniques that power Adobe’s AEP AI Assistant, and research on debiasing generative models and scalable ML algorithms. Mehrab combines applied research with systems thinking—having implemented FAISS-based video fingerprinting pipelines and sketching-accelerated PCA—and maintains an active interest in trust, bias, and recommender systems.
10 years of coding experience
7 years of employment as a software developer
University of California, San Diego
B.Sc., CSE, B.Sc., CSE at Bangladesh University of Engineering and Technology
Contributions:18 commits, 12 pushes, 1 branch in 11 months
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