Summary
Suleyman Uslu is a faculty member and researcher with nine years of experience at the intersection of Trustworthy and Causal AI, currently conducting AI security research and teaching computer engineering at Purdue. He holds a PhD in Computer Science from Purdue and has a track record of designing graduate curricula—most recently a Spatial Computing course—and advising students on explainability, fairness, and causal inference in high-stakes domains. His background spans systems and applied research, from accelerating graph-theoretic decision-support for watersheds to building national PKI components, reflecting strong engineering rigor alongside theoretical depth. Known for evaluating large language models under operational constraints, he blends hands-on programming in C++, Java, and Python with a research focus on human-AI collaboration and model trustability.
8 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Purdue University
Master of Science (M.Sc.) Computer Science, Master of Science (M.Sc.) Computer Science at University of Iowa
Master of Science - MS Computer Engineering, Master of Science - MS Computer Engineering at Boğaziçi University
Turkish, English