Leo Anthony Celi (MIMIC Project Lead) - Leo Anthony Celi has practiced medicine in three continents, giving him broad perspectives in healthcare delivery. He founded and co-directs Sana, a cross-disciplinary organization based at the Institute for Medical Engineering and Science at MIT, whose objective is to leverage information technology to improve health outcomes in low- and middle-income countries. He also holds a faculty position at Harvard Medical School as an intensive care specialist at the Beth Israel Deaconess Medical Center and is the clinical research director for the Laboratory of Computational Physiology (LCP) at MIT. Over the past decade, LCP and Philips have partnered with Beth Israel Deaconess Medical Center (BIDMC), with support from the National Institute of Biomedical Imaging and Bioinformatics, to build and maintain the Medical Information Mart for Intensive Care (MIMIC) database. This public-access database, which now holds clinical data from over 60,000 stays in BIDMC intensive care units, has been meticulously de-identified and is freely shared online with the research community via PhysioNet. It is an unparalleled research resource; over 2500 researchers from more than 32 countries have free access to the clinical data under data use agreements. Leo is one of the course directors for HST.936 at MIT – global health informatics to improve quality of care, and HST.953 – secondary analysis of electronic health records. Finally, he was featured as a designer in the Smithsonian Museum National Design Triennial “Why Design Now?” held at the Cooper-Hewitt Museum in New York City in 2010 for his work in global health informatics.
Eric Xing - Dr. Eric Xing is a professor in the School of Computer Science at Carnegie Mellon University. His principal research interests lie in the development of machine learning and statistical methodology, and large-scale computational system and architecture, for solving problems involving automated learning, reasoning, and decision-making in high-dimensional, multimodal, and dynamic possible worlds in complex systems. Professor Xing received a Ph.D. in Molecular Biology from Rutgers University, and another Ph.D. in Computer Science from UC Berkeley. Professor Xing is an associate editor of the Journal of the American Statistical Association, Annals of Applied Statistics, the IEEE Transactions on Pattern Analysis and Machine Intelligence, the PLoS Journal of Computational Biology, and an Action Editor of the Machine Learning journal, and the Journal of Machine Learning Research. He is a member of the DARPA Information Science and Technology (ISAT) Advisory Group, a recipient of the NSF Career Award, the Alfred P. Sloan Research Fellowship, the United States Air Force Young Investigator Award, and the IBM Open Collaborative Research Faculty Award.
Jenna Wiens - Jenna Wiens is an Assistant Professor of Computer Science and Engineering (CSE) at the University of Michigan in Ann Arbor. Her primary research interests lie at the intersection of machine learning, data mining, and healthcare. She is particularly interested in time-series analysis, transfer/multitask learning and causal inference. The overarching goal of her research agenda is to develop the computational methods needed to help organize, process, and transform patient data into actionable knowledge. Jenna received her PhD from MIT in 2014. Recently, she received an NSF CAREER Award, and in 2015 was named Forbes 30 under 30 in Science and Healthcare.
Sendhil Mullainathan - Sendhil Mullainathan is the Robert C. Waggoner Professor of Economics at Harvard University. His work runs a wide gamut: the impact of poverty on mental bandwidth; whether CEO pay is excessive; using fictitious resumes to measure discrimination; showing that higher cigarette taxes make smokers happier; modeling how competition affects media bias; and a model of coarse thinking. His latest research focuses on using machine learning to better understand human behavior and health. He enjoys writing, having recently co-authored Scarcity: Why Having too Little Means so Much as well as writing regularly for the New York Times. He is currently co-writing a PhD textbook on machine learning. He also is active in application of research insights. He helped co-found a non-profit to apply behavioral science (ideas42), co-founded a center to promote the use of randomized control trials in development (the Abdul Latif Jameel Poverty Action Lab), serves on the board of the MacArthur Foundation, and has worked in government in various roles. He is a recipient of the MacArthur “genius” Award, has been designated a “Young Global Leader” by the World Economic Forum, labeled a “Top 100 Thinker” by Foreign Policy Magazine, and named to the “Smart List: 50 people who will change the world” by Wired Magazine (UK).
Neil Lawrence - Neil Lawrence is a Professor of Machine Learning and Computational Biology at the University of Sheffield in the United Kingdom. He holds a PhD in Computer science from Cambridge University and had a postdoctoral stay with Microsoft Research Cambridge. He has served as the Chair of the Neural Information Processing Conference, the premier Machine Learning conference in the world, and was the founding editor of the Journal of Machine Learning Research Workshop and Conference Proceedings. He is a fellow of the Royal Society in the working group for machine learning. He is a frequent contributor on various scientific topics regarding machine learning, data and society for The Guardian. He is considered one of the foremost experts on probabilistic modeling of real-world phenomena, specifically using Gaussian Process models. With his group, he is leading efforts to apply machine learning techniques for healthcare purposes in the African continent in collaboration with the World Health Organization.
Niels Peek - Niels Peek is Associate Professor of Health Informatics at the Health e-Research Centre, The University of Manchester, UK. He has a background in Computer Science and Artificial Intelligence. His research focuses on data-driven informatics methods for healthcare quality improvement, data mining for healthcare, predictive models, and clinical computerised decision support. He is director of the Greater Manchester Connected Health City, which is part of the £20M "Health North" investment to establish a learning health system in the North of England. Dr. Peek has co-authored more than 125 peer-reviewed scientific publications. Previously based at the University of Amsterdam, the Netherlands, he led the “CARDSS” initiative, a collaboration between academic partners, professional and patient organisations in cardiac rehabilitation, and industry partners which led to the introduction of computerised decision support in 40 Dutch hospitals and national quality standards for cardiac rehabilitation. He is currently the President of the Society for Artificial Intelligence in Medicine (AIME), and a member of the editorial boards of the Journal of the American Medical Informatics Association and the Journal of Biomedical Informatics. In 2017, he will co-chair the Scientific Programme Committee of MEDINFO-2017, the 16th World Congress on Health and Biomedical Informatics