Stanford University
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Mark Musen
Stanford Medicine Professor of Biomedical Informatics Research, Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsModern science requires that experimental data—and descriptions of the methods used to generate and analyze the data—are available online. Our laboratory studies methods for creating comprehensive, machine-actionable descriptions both of data and of experiments that can be processed by other scientists and by computers. We are also working to "clean up" legacy data and metadata to improve adherence to standards and to facilitate open science broadly.
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Mete Muslu
Postdoctoral Scholar, Electrical Engineering
BioA. Mete Muslu received his B.Sc. and M.Sc. degrees in Mechanical Engineering from Ozyegin University, Istanbul, Turkey, in 2018 and 2020, respectively, and his Ph.D. in Mechanical Engineering from the Georgia Institute of Technology, Atlanta, GA, USA, in 2025. His doctoral research focused on developing single- and two-phase cooling solutions for integrated power electronics packages and multi-functional cold plates. His current research interests include understanding device-level multi-physics and developing integrated thermal management solutions spanning from the chip to the package level for high-performance computing and power applications.
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Maggie Mustaklem
Overseas Studies - Oxford, Bing Overseas Studies
BioMaggie Mustaklem is a PhD student at the University of Oxford focusing on AI and creativity. Her doctoral research project, Who and What is Designing Design, centers on algorithmic image search and the images creative professionals use for inspiration. Maggie holds a Master of Arts in History of Design from the Royal College of Art and Victoria & Albert Museum and a Bachelor of Arts in Psychology from the University of Michigan.
In addition to her research, Maggie is the project lead on AI Yesterday, a digital zine and multimedia forum that critically engages with AI histories, challenging dominant narratives about AI’s potential futures. Through experimental, freeform participation, AI Yesterday embraces voices and outputs that academic writing and journalism often exclude.
