Begin forwarded message:From: "Waterman, Geoffrey Eric" <gwa...@UPENN.EDU>Subject: Penn Bioinformatics Forum, April 11 – Suchi Saria, PhDDate: April 2, 2018 at 5:24:12 PM EDTReply-To: "Waterman, Geoffrey Eric" <gwa...@UPENN.EDU>
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Suchi Saria, PhD
John C. Malone Assistant Professor of Computer Science
Johns Hopkins UniversityTitle and Abstract to be announced
Biography:
Saria’s interests span machine learning, computational statistics, and its applications to domains where one has to draw inferences from observing a complex, real-world system evolve over time. The emphasis of her research is on Bayesian and probabilistic graphical modeling approaches for addressing challenges associated with modeling and prediction in real-world temporal systems. In the last seven years, she has been particularly drawn to computational solutions for problems in health informatics (see her recent article on this topic) as she sees a tremendous opportunity there for high impact work.
Prior to joining Johns Hopkins, she earned her PhD and Masters at Stanford in Computer Science working with Dr. Daphne Koller. She also spent a year at Harvard University collaborating with Dr. Ken Mandl and Dr. Zak Kohane as an NSF Computing Innovation Fellow. While in the valley, she also spent time as an early employee at Aster Data Systems, a big data startup acquired by Teradata. She enjoys consulting and advising data-related startups. She is an investor and an informal advisor to Patient Ping.
Wednesday, April 11
3pm
Austrian Auditorium, CRB
D201 Richards Building
3700 Hamilton Walk
Philadelphia, PA 19104
upibi.org
Begin forwarded message:From: "Waterman, Geoffrey Eric" <gwa...@UPENN.EDU>Subject: Penn Bioinformatics Forum, April 11 – Suchi Saria, PhDDate: April 6, 2018 at 5:43:54 PM EDTReply-To: "Waterman, Geoffrey Eric" <gwa...@UPENN.EDU>
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Individualizing Healthcare with Machine Learning
Biography:
Saria’s interests span machine learning, computational statistics, and its applications to domains where one has to draw inferences from observing a complex, real-world system evolve over time. The emphasis of her research is on Bayesian and probabilistic graphical modeling approaches for addressing challenges associated with modeling and prediction in real-world temporal systems. In the last seven years, she has been particularly drawn to computational solutions for problems in health informatics as she sees a tremendous opportunity there for high impact work.
Prior to joining Johns Hopkins, she earned her PhD and Masters at Stanford in Computer Science working with Dr. Daphne Koller. She also spent a year at Harvard University collaborating with Dr. Ken Mandl and Dr. Zak Kohane as an NSF Computing Innovation Fellow. While in the valley, she also spent time as an early employee at Aster Data Systems, a big data startup acquired by Teradata. She enjoys consulting and advising data-related startups. She is an investor and an informal advisor to Patient Ping.
Wednesday, April 11
3pm
Austrian Auditorium, CRB