Dr. Eunsu Kang is a media artist from Korea. She creates interactive audiovisual installations and artworks using Machine Learning methods. Creating interdisciplinary projects, her signature has been seamless integration of art disciplines and innovative techniques. Her work has been invited to numerous places around the world including Japan, China, Switzerland, Sweden, France, Germany, and the US. All her solo shows, consisting of individual or collaborative projects, were invited or awarded. She has won the Korean National Grant for Arts three times. Her researches have been present at conferences such as ACM, ICMC, and ISEA. Kang earned her Ph.D. in Digital Arts and Experimental Media from DXARTS at the University of Washington in Seattle, USA. She received an MA in Media Arts and Technology from the University of California Santa Barbara in USA and an MFA from the Ewha Womans University in Seoul, Korea. She is currently an Associate Professor of New Media Art at the University of Akron. She is also teaching and researching at the Art and Machine Learning departments of Carnegie Mellon University during her sabbatical year 2017-2018. Webpage
Dr. Barnabas Poczos is an assistant professor in the Machine Learning Department at the School of Computer Science, Carnegie Mellon University. His research interests lie in the theoretical questions of statistics and their applications to machine learning. Currently he is developing machine learning methods for advancing automated discovery and efficient data processing in applied sciences including health-sciences, neuroscience, bioinformatics, cosmology, agriculture, robotics, civil engineering, and material sciences. In 2001 he earned his M.Sc. in applied mathematics at Eotvos Lorand University in Budapest, Hungary. In 2007 he obtained his Ph.D. in computer science from the same university. Webpage
Jonathan Dinu is a 2nd year Ph.D. student in Carnegie Mellon's Human Computer Interaction Institute (HCII) where he takes a data driven approach to studying educational systems and is exploring how technology can be used to augment learning environments. To this end, he is working to democratize machine learning through interpretable and interactive algorithms in order to empower teachers and students. Before Carnegie Mellon he created a data science bootcamp called Zipfian Academy (which has since been acquired by Galvanize) and also taught data visualization and creative coding in variety of venues. He got his BA at UC Berkeley where he studied Computer Science and Physics... GO BEARS! Webpage