Summary
Mert Kilickaya is an industrial deep learning researcher with 11 years of experience and a PhD in Artificial Intelligence, currently developing models for cancer prognosis at Agendia. He specializes in representation learning, self-supervised and continual learning, and building scalable pipelines that convert weakly supervised real-world data into robust clinical biomarkers, particularly in digital pathology and transcriptomics. His work spans academia and industry—from a PhD at University of Amsterdam and postdoc roles to positions at Qualcomm Lab, Huawei, and Eindhoven University of Technology—and includes 10+ peer-reviewed papers and four US patents. Colleagues describe him as research-driven but product-minded: he not only invents models but also deploys end-to-end systems that adapt over time. An interesting facet is his blend of foundational ML (foundation models, generative AI) with hands-on biomedical signal extraction, making him adept at translating novel algorithms into clinically actionable tools.
11 years of coding experience
13 years of employment as a software developer
Bachelor of Science - BS, Electrical and Electronics Engineering, Bachelor of Science - BS, Electrical and Electronics Engineering at Ankara University
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Hacettepe University
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at University of Amsterdam