Summary
Usman Gohar is an AI evaluation and safety researcher with nine years of experience applying machine learning to real-world problems, currently a PhD student and research assistant at Iowa State University focused on empirical fairness in ML systems. He has blended academic rigor with industry impact through internships and roles at Google, Seagate, Bayer, and OATI, where he built production-ready forecasting pipelines, automated deployments, and designed grower-level ML value models. As a section lead for the AI harms chapter at Mila, he contributed to high-profile safety discourse under Yoshua Bengio’s initiative, signaling both domain depth and policy-minded thinking. His background spans data engineering, feature engineering, and applied research across agriculture, energy, and healthcare signal processing, and he brings practical deployment experience alongside research credentials. Based in Minneapolis, he pairs PhD-level inquiry with hands-on data science execution and a demonstrated knack for turning disparate data sources into actionable models.
9 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Iowa State University
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at University of Minnesota Duluth
Bachelor of Science - BS, Computer Engineering, Bachelor of Science - BS, Computer Engineering at National University of Sciences and Technology (NUST)
English, Urdu, Pashto