Health Research and Policy

Events

DATE: January 18, 2013
TIME: 3:00 pm
LOCATION: Rm 200
Sequoia Hall
TITLE: Writing Scientific Papers
SPEAKER:

Kristin Sainani, PhD
Clinical Assistant Professor of Health Research & Policy

Abstract: Writing is critical to success in biostatistics. Yet statisticians often receive little formal training in the principles of effective writing. As a result, statistical writing is often needlessly difficult and boring to read. This talk will teach you how to make your papers more
lively, engaging, and informative. The talk will review general principles of good writing, examples of good and bad writing, and tips for making the writing process itself more fun and efficient.

Bio: Kristin Sainani, MS '99, PhD '02, is a freelance writer and clinical assistant professor in the department of health research and policy.

To read more: Faculty member's online science-writing class helps researchers from around the world hone their writing and presentation skills

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DATE: April 5, 2013
TIME: 3:00 pm
LOCATION: Rm 200
Sequoia Hall
TITLE: Prize4Life: predicting disease progression in ALS
SPEAKER:

Lester Mackey, PhD
Postdoctoral Research Fellow, Natural Sciences Cluster

Abstract: ALS (amyotrophic lateral sclerosis), or Lou Gehrig's disease, is a fatal neurodegenerative disease with no known cure and few known causes. In July of 2012, Prize4Life launched a challenge to most accurately predict the rate of progression of ALS in patients. The ALS Prediction Prize4Life Challenge ran on the InnoCentive prize platform and featured a subset of the PRO-ACT (Pooled Resource Open-Access ALS Clinical Trials) database, the largest compilation of ALS clinical trial data ever assembled. The complete PRO-ACT database contains the clinical records of over 8,500 ALS patients. In October of 2012, Lilly Fang and I were awarded first prize in the challenge, an honor shared with Liuxia Wang and Guang Li of Sentrana, Inc.

Bio: I'm a Simons Math+X postdoctoral fellow, working with Emmanuel Candes at Stanford University. I received my Ph.D. in Computer Science (2012) and my M.A. in Statistics (2011) from UC Berkeley and my B.S.E. in Computer Science (2007) from Princeton University. My Ph.D. advisor was Mike Jordan, and my undergraduate research advisors were Maria Klawe and David Walker. My current research interests include Statistical Machine Learning and Algorithms and Data Structures. Lately, I've been developing and analyzing algorithms for ranking, admixtures, matrix factorization, and collaborative filtering, but I'm quite generally interested in problems that bridge theory and applications and that involve drawing inferences from large, structured datasets.

To read more: Contest Winners Offer Solutions for Tracking ALS

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