Summary
Doga Dogan is a research scientist at Adobe Research in Switzerland with a PhD from MIT CSAIL and 11 years of experience at the intersection of HCI, generative AI, and ubiquitous computing. He builds GenAI and agent-driven systems (including work on Adobe LLM Optimizer) and develops metadata-driven methods that let physical materials encode machine-readable signals for more robust AI perception. His background spans industry and academia—Google, MIT, University of Tokyo, TU Delft—and includes tangible interfaces, AR/XR, and novel fabrication techniques. He designs human-centered workflows that combine agentic AI with real-world context to make information access more reliable and pervasive. Notably, his work connects digital and physical contexts through "grounded ubiquitous intelligence," merging creative tools with sensing and material-aware design. Based in Basel, he brings a rare blend of theoretical rigor and hands-on prototyping across software, hardware, and taught curricula.
11 years of coding experience
8 years of employment as a software developer
Information technology, Information technology at BİLSEM (Bilim ve Sanat Merkezi - Science & Arts Center)
Bachelor of Science (B.Sc.), Electrical and Electronics Engineering, Bachelor of Science (B.Sc.), Electrical and Electronics Engineering at Boğaziçi University
Doctor of Philosophy - PhD, Electrical Engineering and Computer Science, Doctor of Philosophy - PhD, Electrical Engineering and Computer Science at Massachusetts Institute of Technology
High School, High School at Istanbul Erkek Lisesi
University of California, Los Angeles
English, German, Turkish, Chinese