Yigitcan Kaya

I am a postdoctoral fellow at UCSB SecLab, working with Giovanni Vigna and Chris Kruegel as of October 2023. My postdoc is very generously fully funded by the Intelligence Community (IC) Postdoctoral Research Fellowship to conduct research on ML-based antifragile cyber defenses. I received my PhD in Computer Science from the University of Maryland College Park advised by Prof. Tudor Dumitras. My research interests span the areas of machine learning (ML) for security and adversarial machine learning, with an emphasis on bridging between these two fields. In the past, I identified a common pathology of deep neural networks and coined the term overthinking, developed realistic threat models against ML systems, such as inconspicuous poisoning attacks, and studied the feasibility of practical defenses to make ML models more private. My work has garnered press interest by popular outlets such as VentureBeat and MIT Tech Review. Nowadays, I'm applying my expertise to make ML models more robust, secure and reliable in security applications, such as malware detection.

As an undergraduate intern at the Maryland Cybersecurity Center in 2016, I was supervised by senior PhD students. Since then, I, myself, had the pleasure to supervise many interns and junior students on research projects, which has led to multiple publications at top venues and 6 new PhD students in leading programs.

I usually just go by Can, pronounced very similar to 'John'.


Publications --- Google Scholar



Industry Experience


yigitcan at ucsb dot edu

2114 Harold Frank Hall,
Department of Computer Science,
University of California, Santa Barbara.
CA 93106