Your Committee

Saleema Amershi is a Researcher in the Adaptive Systems and Interaction Group at Microsoft Research working on technologies for making people better at building and using ML systems. Throughout her work, she distills guiding principles applicable in a broader context to help provide a foundation for future human-driven machine learning systems.

Richard Banks is Principal Design Manager at the Human Experience and Design Group at Microsoft Research, Cambridge, UK. His work explores the boundaries of technology, creativity, and society through a human-centered lens. Much of Richard’s current focus is on new issues and opportunities raised by artificial intelligence for both people, as well as the design profession.

Gagan Bansal is a Ph.D. student at the Paul G. Allen School of Computer Science at the University of Washington, Seattle. He conducts interdisciplinary research on AI and HCI. He currently works on developing UI to explain ML models to users via a user-system dialog, and interfaces to evaluate the effect of explanations on human-AI team performance. He is advised by Dan Weld.

Rebecca Fiebrink is a lecturer at Goldsmiths, University of London. Her research combines techniques from HCI, ML, and signal processing to allow people to apply ML effectively to new problems. She is involved in projects developing rich interactive technologies for digital humanities scholarship, and using digital music creation to engage youth in learning computer programming and computational thinking. She is the author of the Wekinator software for interactive ML.

Soroush Ghorashi is a Research Engineer at Microsoft Research working in the Machine Teaching Group, where he works to streamline the process of knowledge transfer from the human teachers to the learning machines. He received his M.Sc and Ph.D. from the Oregon State University specializing in HCI focused on improving collaboration quality within software teams by building novel development environment and collaboration techniques.

Christopher Meek is a Principal Researcher at Microsoft Research at the Machine Teaching Group, where he is enabling people to effectively use machine learning to solve problems. He received his Ph.D. from Carnegie Mellon University, and worked on topics related to machine learning, many of which have lead to product innovations and product features. He has a long-standing interest in learning causal, and graphical models. He is an affiliate professor at the University of Washington.

Gonzalo Ramos is a Senior Researcher at Microsoft Research working at the Machine Teaching Group, where he works in lowering the barrier of entry for people to harness the power of ML. He received his M.Sc and Ph.D. from the University of Toronto’s Computer Science Department, specializing in Scientific Visualization and HCI, respectively. Gonzalo also worked as a Senior Design Technologist and UX Scientist at Amazon, and as a Scientist at Microsoft.

Alison Smith-Renner leads the Machine Learning Visualization Lab for Decisive Analytics Corporation. Her focus is on enhancing users’ understanding and analysis of data without requiring expertise in ML or data science. She is currently a Computer Science Ph.D. Candidate at the University of Maryland, College Park with a focus on human-centered design for interactive machine learning under the direction of Leah Findlater and Jordan Boyd-Graber.

Jina Suh is a graduate student at the Paul G. Allen School of Computer Science at the University of Washington advised by Dan Weld and James Fogarty. She is a Principal Research Software Developer at Microsoft Research in the Affective Computing Group. Jina researches how humans interact with ML systems focusing on model intelligibility and bias. She was part of the Machine Teaching Group at Microsoft Research and continues to contribute in this area.