麻豆传媒

Larry Fulton is an Associate Professor of Health Administration at Texas State University, San Marcos. He earned his Doctorate of Philosophy / Masters of Science in Statistics from the University of Texas at Austin, his Master of Health Administration from Baylor, and three other graduate degrees. Dr. Fulton is a Fellow of the American College of Healthcare Executives (FACHE) and maintains the credentials of Chartered Scientist and Chartered Statistician (CStat CSci) as a Fellow in the Royal Statistical Society. He is a Certified Analytics Professional (CAP) of the Institute for Operations Research & Management Science, a Certified Quality Engineer and Certified Six Sigma Black Belt (CQE CSSBB) of the American Society for Quality and a Professional Statistician (PStat) of the American Statistical Association.

Y. Dan Rubinstein is CEO/co-founder of Physera which is using data and technology to innovate in healthcare. Previously, Dan held product leadership roles at Facebook, Google, and Palantir and was an Entrepreneur in Residence (EIR) at Khosla Ventures. Earlier in his career, he was the founding CEO of Reflectivity, a semiconductor display startup, which raised over $58M, grew to over 60 employees, set up manufacturing lines in Taiwan & Japan and was acquired by Texas Instruments. 

He holds a Ph.D. in Statistics from Stanford and a B.Sc. in Electrical Engineering from Princeton and is a published singer-songwriter.

Lauren Ancel Meyers is the Cooley Centennial Professor of Integrative Biology and Statistics & Data Sciences at The University of Texas at Austin and a member of the Santa Fe Institute External Faculty. She was trained as a mathematical biologist at Harvard and Stanford Universities and has been a pioneer in the field of network epidemiology and the application of machine learning to improve outbreak detection, forecasting and control.

Professor Meyers leads an interdisciplinary team of scientists, engineers, and public health experts in uncovering the social and biological drivers of epidemics and building practical tools for the CDC and other global health agencies to track and mitigate emerging viral threats, including COVID-19, pandemic influenza, Ebola, HIV, and Zika. Her research has been published in over 100 peer-reviewed articles in major journals and covered by the popular press, including The Wall Street Journal, New York Times, Washington Post, NPR, CNN and the BBC. Professor Meyers was named as one of the top 100 global innovators under age 35 by the MIT Technology Review in 2004 and received the Joseph Lieberman Award for Significant Contributions to Science in 2017.

Awards & Fellowships

2018- Denton A. Cooley Centennial Professorship, UT
2017 Joseph Lieberman Award for Significant Contributions to Science
2011-2013, 16-18 William H. and Gladys G. Reeder Faculty Fellow, UT
2006-2010, 14-15 Fellow, University of Texas Institute for Molecular and Cellular Biology
2013 Center for Excellence in Education - Excellence and Achievement Award
2010-2011 Donald D. Harrington Faculty Fellowship, UT
2005 College of Natural Sciences Teaching Excellence Award, University of Texas
2004 MIT Technology Review TR100: One of 100 Top Global Innovators Under 35
2000-2002 National Science Foundation Postdoctoral Fellowship in Biological Informatics
2000-2002 Santa Fe Institute Postdoctoral Fellowship
2000 Samuel Karlin Prize for Ph.D Thesis in Mathematical Biology
1999 Steinmetz Fellowship, Santa Fe Institute
1996-1999 National Defense Science & Engineering Graduate Fellowship
1991-1995 U.S. Congressional National Science Scholar

 (he/him) is a research and associate professor who studies and develops methods to accelerate the development of high-performing crops by identifying specific DNA regions associated with agronomically important traits. He uses statistical approaches for quantitative genetic analyses in crops as well.
More information:
Lipka is a researcher and associate professor passionate about the development of sustainable and high-performing crop practices. In pursuit of this passion, he leads the Lipka Lab at the University of Illinois with the research aim of creating statistical approaches to analyze quantitative genetics data. Lipka's research interests include multidisciplinary collaborations that focus on various genomic-related issues, including the contributions of nonadditive effects to phenotypic variation and the identification of genomic variants associated with agronomic and health-related traits. Some of his research endeavors include the investigation of crop productivity based on the activity of meristems to facilitate further genetic studies and the study into the diversity, genomic complexity, population structure, phylogeny, phylogeography, ploidy, and evolutionary dynamics of switchgrass. Lipka also led a study that developed an R package called Genome Association and Prediction Integrated Tool to handle larger datasets for genome-wide association studies and genomic prediction and selection studies. Prior to joining the University of Illinois, Lipka received his Bachelor of Science in Statistics at the University of Flordia and went on to get his Master of Science and Ph.D. at Purdue University. Lipka was also a postdoctoral associate at Cornell University.
Affiliations:
Dr. Lipka is an associate professor in the  in the  (ACES) at the .

Daniel J. Eck is a professor of statistics at the University of Illinois Urbana-Champaign. His research mission is to improve statistical methodologies that are applicable to real-world problems with a focus placed on both the theoretical and computational aspects of this methodology. To better understand relevant real-world problems, Eck works closely with scientists and researchers across a variety of disciplines. Eck's current methodological work has applications in evolutionary biology, baseball, history, education, epidemiology, and genomics studies. Eck teaches advanced statistical modeling, programming, and baseball analytics. He runs a joint internship with the Chicago Cubs in which undergraduate students get hands-on experience with baseball analytics in the real world.
Research interests

sports analytics
history
evolutionary biology
economics

Education
PhD Statistics, University of Minnesota, 2017
 BS Mathematics, Southern Illinois University Carbondale, 2009

Professor Samuel Manda is a lecturer at the Department of Statistics

His research interests include: Methods research concentrates on Bayesian modelling, analysis of survival and longitudinal studies, design and analysis of health surveys, spatial modelling, and developing innovative statistical models and analysis for research evidence combination and assembled complex and big datasets on critical African health issues such as women and child health, HIV and NCDs). 

Application research focuses on health, epidemiology, and health systems in the sub-Saharan Africa. Designing of clinical trials and impact evaluation of programs and interventions. He is currently working on small area estimation methods, causal inference of health outcomes and coverage; and COVID-19 burden estimation, modelling, and prediction in sub-Saharan Africa.