Computational Challenges in Healthcare
Katie Siek is an associate professor in Informatics at Indiana University. Her primary research interests are in human computer interaction, health informatics, and ubiquitous computing. More specifically, she is interested in how sociotechnical interventions affect personal health and well being. Her research is supported by the National Institutes of Health, the Robert Wood Johnson Foundation, and the National Science Foundation including a five-year NSF CAREER award. She has been awarded a CRA-W Borg Early Career Award (2012) and a Scottish Informatics and Computer Science Alliance Distinguished Visiting Fellowship (2010 & 2015).
Mona Singh is a Professor of Computer Science and the Lewis Sigler Institute for Integrative Genomics at Princeton University. She received her A.B. and S.M degrees from Harvard University, and her Ph.D. from MIT, all three in computer science. She works broadly in computational molecular biology, as well as its interface with machine learning and algorithms. Much of her work is on developing algorithms to decode genomes at the level of proteins and she is especially interested in developing data-driven methods for predicting and characterizing protein sequences, functions, interactions and networks, both in healthy and disease contexts. She is Editor-in-Chief of the Journal of Computational Biology. Among her awards are the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2001, and the Rheinstein Junior Faculty Award from Princeton’s School of Engineering and Applied Science in 2003. She was named a Fellow of the ACM in 2019, and of the ISCB in 2018.