How to Write a Successful Grant Proposal

Thursday, November 4, 2021 12:30 - 2 pm ET

[Please Note: This session has already occurred.  Go to the News Story to read about what happened.] 


Research grants are important for career advancement.  Grants also allow researchers to protect their time while providing resources necessary for statisticians in academia to pursue an independent area of research. But the process can be challenging to figure out where to apply for a grant and how to write a strong proposal.  Which organizations offer funding for statistical research?  How can you increase your chances of getting funded?  What are the elements that are commonly found in successful grant applications? If you asked reviewers for their advice, what would they point out as being essential?

The NISS Academic Affiliates Committee is very excited about being able to bring together four accomplished senior statisticians who have extensive experience in both writing and reviewing grant proposals. 

The speakers for this session are Huixia (Judy) Wang who is the National Science Foundation DMS Statistics Program Director and at George Washington University, Steven Kern from the Gates Foundation, Joshua M. Tebbs Professor and Department Chair at the University of South Carolina, who has served at the BMRD study section of National Institutes for Health (NIH) and received several external grants, and Ali Shojaie from the University of Washington who has been successful in securing multiple sole-PI and collaborative grants, and has served on a number of proposal review panels for NSF and NIH.

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Agenda

The program for this session will be organized as follows:

12:30-12:35         Opening remarks: Moderator: Sumanta Basu (Cornell)

12:35-12:50        Huixia (Judy) Wang (NSF) 

12:50-1:05         Steven Kern (Gates Foundation)

1:05-1:20         Joshua M. Tebbs (NIH)

1:20-1:35         Ali Shojaie (University of Washington)

1:35-2:00         Q&A - questions from attendees

Moderated by Sumanta Basu (Cornell)

About the Speakers

Joshua M. Tebbs is Professor and Chair in the Department of Statistics at University of South Carolina. He obtained his BS in Mathematics and MS in Statistics from University of Iowa and his PhD in Statistics from North Carolina State University. His primary research interests are in the development of statistical methods for categorical data, especially aggregated or group tested data and their application in infectious disease screening, as well as in general biostatistical methods and problems involving ordering or shape restrictions. He is an elected member of the International Statistical Institute, a fellow of the American Statistical Association, and his research program is funded by the National Institutes of Health (NIH). He is currently Editor-in-Chief at American Statistician, Associate Editor at Statistics in Medicine, and a former member of the Biostatistical Methods and Research Design (BMRD) Study Section of the NIH.  

Ali Shojaie is Professor and Associate Chair of Biostatistics, Adjunct Professor of Statistics and founding director of the Summer Institute for Statistics in Big Data (SISBID) at the University of Washington. Originally trained in Industrial and Systems Engineering, he obtained his PhD in Statistics from the University of Michigan, while completing Masters degrees in Applied Mathematics and Human Genetics. Dr. Shojaie’s research lies in the intersection of statistical machine learning, statistical network analysis and applications in biology and social sciences.    

Additional short speaker bio-sketches coming soon!

 

Moderator:

Sumanta Basu, Ph.D., (Assistant Professor, Shayegani Bruno Family Faculty Fellow, Department of Statistics and Data Science, Department of Computational Biology, Cornell University).

Event Type

Host

National Institute of Statistical Sciences

Cost

Registration is free.

Location

Online Webinar
Moderator: Sumanta Basu (Cornell)  Speakers: Huixia Wang (NSF), Steve Kern (Gates Foundation), Joshua Tebbs (NIH), Ali Shojaie (University of Washington)