David Zollikofer is a researcher and engineer bridging theoretical computer science, machine learning, and microeconomics with nine years of hands-on experience. Currently an associated PhD student at ETH Zurich and the ETH AI Center, he focuses on interpretable AI and econometric methods under Prof. Elliott Ash, while co-founding and leading AI research at DDMind. His background spans applied data-science projects—from LC-MS wine authentication and drift-correction algorithms to building corporate IT tooling—reflecting fluency across experiment design, infrastructure, and algorithm development. He has taught algorithms at ETH, completed advanced fellowships at Harvard and Y Combinator’s AI Startup School, and pursues work that tightly couples economic theory with ML practice. Colleagues value his ability to translate abstract theoretical tools into practical, auditable solutions for interdisciplinary problems.
9 years of coding experience
3 years of employment as a software developer
AI Startup School, AI Startup School at Y Combinator
Fellow in Computer Science, Fellow in Computer Science at Harvard University
Master of Science ETH Computer Science, Master of Science ETH Computer Science at ETH Zürich
Contributions:10 commits, 8 pushes, 1 branch in 1 year 6 months
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