Biography

Ahmad Tamim Hamad is a Ph.D. student in Electrical Engineering and Computer Science at the University of Missouri–Columbia, where he is advised by Dr. Jordan Malof. He holds a Master’s degree in Information Technology from the University of Mysore, India, and a Bachelor’s degree in Computer Science from Gharjistan University, Afghanistan.

With over five years of combined experience in software engineering, data science, and deep learning, Tamim has built a strong foundation in both theoretical research and applied system design. His research focuses on deep inverse modeling for scientific and engineering design problems, such as metamaterial design. He studies how deep inverse models, including the neural adjoint method and conditional invertible neural networks, behave when no design can produce the desired target response. To evaluate this, he develops a generative framework, built on autoencoders and normalizing flows, that produces controlled target responses outside the observed data distribution.

Tamim currently serves as a Graduate Research Assistant and Graduate Teaching Assistant at the University of Missouri, and as an AI & Data Engineer at ShotTracker in Kansas City. Across these roles, he has developed and maintained data pipelines, automated ETL workflows, and deployed predictive models on cloud platforms using Snowflake, AWS, and Python/SQL. At ShotTracker, he has also built backend APIs for the Scout project and contributed to prompt engineering. In addition, he has developed full-stack web applications, including a multi-phase management information system for industrial park management built with Laravel and Next.js.

Beyond his academic and professional work, Tamim has shown leadership and community engagement—serving as President of the Afghan Students Association (2022–2023) and as a member of Upsilon Pi Epsilon, the international honor society for computing and information disciplines.

He is deeply passionate about lifelong learning, interdisciplinary collaboration, and creating scalable AI-driven technologies that make a meaningful impact. His long-term goal is to leverage his expertise to advance research and industrial innovation at the intersection of machine learning, data systems, and intelligent automation.