2nd Annual Graduate Student Research Conference - NISS Graduate Student Network Event

May 14-15, 2022 12 - 5 pm ET

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

The NISS Graduate Student Network is very excited once again to announce a two-day graduate student research conference! The first conference took place in June of 2021 and was a resounding success! This second conference  will be a two-day event and take place on May 14 and 15, 2022, from noon - 5 pm ET and will feature graduate student presentations, invited speakers and a social networking hour. 

This conference is open to anyone interested.

A special thanks to this year's sponsor Procter and Gamble (P&G), our new NISS Industry Affiliate!

Graduate Student Presentations

Students will present either an oral presentation or a poster presentation at this conference within the following categories:

  • Original Research (their own research work),
  • Literature Research (presentation of a published paper that is not authored by the presenter), or
  • Literature Review (presentation on recent developments in an area -- this would be a chance to present a couple of papers to highlight recent developments in an area of interest.)

Selected oral presentations will involve a 20 minute live presentation including 5 minutes of Q&A.

Submission Deadline was April 15th at 5 pm ET, we are no longer recieving abstracts at this time. You will be able to register for the conference as an attendee! Registration details are provided below.


During the conference, two graduate students will be recognized with the best presentation award based on the content and the quality of their presentation. The award this year will be $250 granted to each presentation winner! The awardees will also receive recognition at the NISS Reception at JSM 2022 in Washington, DC!


Invited Panel Discussions


Panel 1: Statistics and Data Science Alumni Panel (May 14th)
At this meeting, we will hear from alumni pursuing careers in statistics and data science. They will be sharing their experiences in the job market (application process/interviews/job talks) and talk about their current jobs (such as statistical tools they use and their job environment) and answer questions from the audience.


Andreea Luisa Erciulescu, Senior Statistician, Westat

Joe Rodhouse, Survey Statistician, U.S. Energy Information Administration (EIA)

Dhanushi Wijeyakulasuriya, Data Scientist, Microsoft

Nathan Cruze, NASA Langley Research Center

Spiro Stilianoudakis Statistician, Data & Modeling Sciences (DMS) of Corporate Functions R&D (CFRD), The Procter & Gamble Company

Panel 2: Tips for Statistical Communication and Data Storytelling (May 15th)
Without strong communication skills, all the advanced analysis we have performed might be overrun. At this event, our expert panelists will share tips and advice on how to clearly and effectively communicate statistics, particularly in social media, and answer questions from the audience.


Lucy D'Agostino McGowan, Assistant Professor, Department of Mathematics and Statistics, Wake Forest University
Natalie Dean, Assistant Professor, Department of Biostatistics & Bioinformatics, Emory University 
Julia Silge, Data Scientist and Software Engineer, RStudio PBC


Networking Social Hour

There will be a Networking Social Hour at the end of the conference at 5 pm May 15th!



$20 registration for Graduate Students. All other registrations are $50.

Need more information on registering? View the Graduate Student Conference FAQ or reach out to gsn@niss.org

NISS Affiliates - this event is Affiliate Award Fund Eligible.  

Please Note: NISS affiliates can use their Affiliate Award Funds towards registration, please contact your NISS liaison (Check the List of NISS Affiliates) to learn more about these funds.  Students registering from NISS affiliated universities are eligible for reimbursement after the conference.



Hosted by The National Institute of Statistical Sciences and the NISS Graduate Student Network

Sponsored by Procter & Gamble Company

Graduate Student Research Conference 2022


Saturday, May 14th

(Please Note:  All Times ET)

12:00 – 12:20    Welcome

12:00 – 12:10 Jim Rosenberger, (Director, NISS)

12:10 – 12:20 William Brenneman, (Procter & Gamble)

12:25 – 13:35   High-dimensional statistical analysis and applications  

Session Chair: Danny Ying, University of California, Los Angeles

12:25 – 12:40 – Ye Tian, Columbia University

12:40 – 12:55 – Arnab Auddy, Columbia University

12:55 – 13:10 – Yingchao Zhou, Iowa State University

13:10 – 13:25 – Yuan Yang, Clemson University

13:25 – 13:35 – Floor discussion

13:40 – 14:40    Statistics and Data Science Alumni Panel

Session Chair: Manqi Cai, University of Pittsburgh

Speakers: Andreea Luisa Erciulescu, Senior Statistician, Westat; Joe Rodhouse, Survey Statistician, U.S. Energy Information Administration (EIA); Dhanushi Wijeyakulasuriya, Data Scientist, Microsoft; Nathan Cruze, NASA Langley Research Center; Spiro Stilianoudakis, Statistician, Data & Modeling Sciences (DMS) of Corporate Functions R&D (CFRD), The Procter & Gamble Company

14:40 – 15:00    Break

15:00 – 16:10    Novel perspectives in Bayesian methodology

Session Chair: Imon Banerjee, Purdue University

15:00 – 15:15 – Yoonji Kim, Ohio State University

15:15 – 15:30 – Brandon Lumsden, Clemson University

15:30 – 15:45 – Hannah Waddel, Emory University

15:45 – 16:00 – Alexander Murph, UNC Chapel Hill

16:00 – 16:10 – Floor discussion

16:15 – 17:05    Contributions in computational and methodological statistics 

Session Chair: Tom Lin, Iowa State University

16:15 – 16:30 – Subrata Pal, Iowa State University

16:30 – 16:45 – Dillon Lloyd, NIEHS

16:45 – 17:00 – Ruochen Huang, Ohio State University

17:00 – 17:05– Floor discussion

17:10 – 18:10    Poster Session and Networking Hour

Event Sponsor: Procter & Gamble

Session Chair: Hannah Waddel

Graduate Student Name Poster Title
Eva Murphy Joint modeling of wind speed and wind direction through a conditional approach
Jian Zou Genomics congruence analysis to select representative cell lines
Xiaohuan Xue A Note on Asymptotics of Estimators on Spheres
Mary Lena Bleile Adaptive Methods for Optimizing Personalized Radiation Schedules
Wei Zong CAMO: A molecular congruence analysis framework for evaluating model organisms (NISS Presentation)
Reetika Sarkar Stable Variable Selection for High-dimensional Genomic Data with Strong Correlations 
Somya Sharma Chatterjee Multi-Resolution Gaussian Processes
Xiaoqing (Ellen) Tan Tree-based Model Averaging for Personalized Causal Inference from Heterogeneous Data Sources
Anisha Das Quantification of the Growth of Glioblastoma Tumor from MRI images
Guoliang Ma Cross-Sectional Analysis of Conditional Stock Returns: Quantile Regression with Machine Learning
Jun Kim Ergodic Paths of LSSVR with the Uncertainty Classification

Sunday, May 15th

12:00 – 12:15    Opening Remarks Day 2

12:00 – 12:15 Esra Kurum (University of California, Riverside) & Hannah Waddel (Emory University)

12:20 – 13:30 – Recent advances in bioinformatics and biomedical data analysis 

Session Chair: Anisha Das, Florida State University

12:20 – 12:35 – Pritam Dey, Duke University

12:35 – 12:50 – Manqi Cai, University of Pittsburgh

12:50 – 13:05 – Yusi Fang, University of Pittsburgh

13:05 – 13:20 – Qingyu Chen, Ohio State University

13:20 – 13:30 – Floor discussion

13:35 – 14:35 – Tips for Statistical Communication and Data Storytelling

Session Chair: Rebecca Kurtz-Garcia (University of California, Riverside) 

Speakers: Lucy D'Agostino McGowan, Assistant Professor, Department of Mathematics and Statistics, Wake Forest University; Natalie Dean, Assistant Professor, Department of Biostatistics & Bioinformatics, Emory University; Julia Silge, Data Scientist and Software Engineer, RStudio PBC

14:40 – 15:10  Break 

15:10 – 16:20 Modern statistical methods for dependent data 

Session Chair: Ksheera Sagar, Purdue University

15:10 – 15:25 – Isaac Quintanilla Salinas, UC Riverside

15:25 – 15:40 – Kunal Das, Iowa State University

15:40 – 15:55 – Adam Tonks, UIUC

15:55 – 16:10 – Rebecca Kurtz-Garcia, UC Riverside

16:10 – 16:20  – Floor discussion

16:30 – 17:00 – Closing Remarks and Awards

16:30 – 16:40 – NISS Director

16:40 – 17:00 Presentation Awards, Sumanta Basu (Cornell University)


About the Panelists: Statistics and Data Science Alumni Panel (May 14th)

Andreea Luisa Erciulescu is a senior statistician at Westat, working at the interface between survey statistics and other areas of statistics, including combining multiple surveys and non-survey sources to answer complex analytic questions. Prior to Westat, she was a research associate with the National Institute of Statistical Sciences (NISS), working at USDA’s National Agricultural Statistics Service. Motivated by real-life problems in agriculture, economy, education, health, recreational sports, she has been developing and implementing innovative and robust statistical models to help improve the reliability of official statistics. Her areas of expertise include Bayesian statistics, hierarchical models, measurement error, official statistics, resampling methods, small area estimation, statistical data integration, and survey statistics. She holds a PhD in statistics from Iowa State University and a bachelor's degree in Mathematics, with double concentration in Mathematics of Information and Technology and Statistics from Colorado State University. Dr. Erciulescu is an Elected Member of the International Statistical Institute, a representative-at-large and the student travel award chair on the Washington Statistical Society Board of Directors, the program chair-elect on the American Statistical Association Survey Research Methods Section Executive Committee, and the U.S. representative on the International Association of Survey Statistics Executive Committee.

Joe Rodhouse is a survey statistician at U.S. Energy Information Administration (EIA). His work experience includes working as a survey methodologist and statistician at USDA and a research associate for NISS, working at the National Agricultural Statistics Services (NASS) in Survey Methodology and Technology Section (SMTS) of the Research and Development Division (RDD).  He holds a Bachelor of Arts in Sociology from Whitman College (2010), and a Master of Science in Survey Methodology from the University of Maryland (2017).  Prior to joining NISS, he spent five years in Boston at one of the leading market research firms in the Information Technology sector, followed by a two-year stint as a graduate research assistant at NASS while completing his graduate studies. His research interests include web surveys, paradata, data collection methods, the psychology of survey response, questionnaire design, statistical modeling, and the total survey error (TSE) framework.

Dhanushi Wijeyakulasuriya is a Data Scientist on the Experimentation Platform Team at Microsoft Corporation where she helps teams run trustworthy online controlled experiments at scale. She holds a PhD in Statistics with a graduate minor in Computational Science from Penn State (2020) and got her BSc. (Hons.) in Industrial Statistics from the University of Colombo (2013). Her doctoral research focused on animal movement modeling. While reading for her PhD she worked for two years as a research assistant at the Statistical Consulting Center at Penn State, Department of Statistics. She also interned at Lubrizol Corporation as a data scientist in 2018. Before moving to the US in 2015 she worked as a Quantitative Analyst at Acuity Knowledge Partners for two years. She is originally from Colombo, Sri Lanka and currently lives in Bellevue, Washington. Dhanushi enjoys singing, baking and gardening in her free time. 

Nathan Cruze, joined NASA Langley Research Center in November 2021 as a statistician in the Systems Engineering and Engineering Methods Branch.  His work at NASA will focus on supporting upcoming community noise studies related to commercial supersonic travel.  Prior to joining NASA, he served as a mathematical statistician in the Research and Development Division at USDA’s National Agricultural Statistics Service (NASS) for more than eight years.  His research at NASS focused on improving economic and crops estimates surveys through modeling.  In 2020 and 2021, he worked with teams at NASS to convert the published Farm Labor, Cash Rents, and Crops County Estimates data products to model-based official statistics; the latter team was recognized with an award from the undersecretary of USDA’s Research, Education, and Economics mission area in October 2021.  He holds bachelor’s degrees in economics and mathematics; master’s degrees in economics and statistics; and a Ph.D. in Interdisciplinary Programs, all from Ohio State University.  Dr. Cruze co-chairs the Federal Committee on Statistical Methodology interest group in Computational Statistics and the Production of Official Statistics.

Spiro Stilianoudakis is a statistician at The Procter & Gamble Company, working in the Data & Modeling Sciences (DMS) division of Corporate Functions R&D (CFRD). Spiro has dual roles within CFRD. One role is building web-based applications focusing on R-shiny applications and R-plumber APIs. The other role is serving as the primary statistician for a newly formed team known as Home-as-Clinics (HaC). The primary aim of HaC is to transform clinical studies from “on site” to “in-home”. As such, the focus of HaC is leveraging sensor/wearable technologies to gain insights and develop products through novel innovations. Motivated by these types of problems, some of Spiro’s current research interest is in methods dealing with machine learning, dimensionality reduction, state space models, dynamic linear models, among others. Prior to joining P&G, he obtained a PhD from Virginia Commonwealth University (Feb 2021) in biostatistics where he developed a machine learning pipeline for predicting the genomic coordinates of boundaries that defined Topologically Associating Domains (TADs) and published his method as an R packaged hosted on Bioconductor. Additionally, he holds a Bachelor’s degree in both Secondary Education and Applied Mathematics, as well as a Master’s degree in Mathematics from Marshall University.


About the Panelists: Tips for Statistical Communication and Data Storytelling (May 15th):

Lucy D’Agostino McGowan is an assistant professor in the Mathematics and Statistics Department at Wake Forest University. She received her PhD in Biostatistics from Vanderbilt University and completed her postdoctoral training at Johns Hopkins University Bloomberg School of Public Health. Her research focuses on statistical communication, causal inference, data science pedagogy, and human-data interaction. Dr. D’Agostino McGowan is the 2021 chair of the American Statistical Association’s Committee on Women in Statistics and can be found blogging at livefreeordichotomize.com, on Twitter @LucyStats, and podcasting on the American Journal of Epidemiology partner podcast, Casual Inference. Her personal website is https://www.lucymcgowan.com/.

Dr. Natalie Dean is an Assistant Professor in the Department of Biostatistics and Bioinformatics at Emory’s Rollins School of Public Health. She received her PhD in Biostatistics from Harvard University, and previously worked as a consultant for the WHO’s HIV Department and as faculty at the University of Florida. Her primary research area is infectious disease epidemiology, with a focus on innovative study designs for evaluating vaccines during public health emergencies. During the COVID-19 pandemic, she has been active in public engagement, with authored pieces in the Washington Post, New York Times, and other outlets. You can find her on Twitter and her personal website is https://www.nataliexdean.com/.

Julia Silge is a data scientist and software engineer at RStudio PBC where she works on open source modeling tools. She studied physics and astronomy, finishing her PhD in 2005. She worked in academia (teaching and doing research) and ed tech before moving into data science in 2015 and discovering R. She is an author, an international speaker, and a real-world practitioner focusing on data analysis and machine learning. She has written books with her collaborators about text mining, supervised machine learning for text, and modeling with tidy data principles in R. She loves making beautiful charts, the statistical programming language R, Jane Austen, black coffee, and red wine. You can find her on Twitter and GitHub. Her personal website is https://juliasilge.com/


Organizing Committee:

Esra Kurum (chair, University of California, Riverside)
Manqi Cai (University of Pittsburgh)
Randy Freret (NISS)
Megan Glenn (NISS)
Rebecca Kurtz-Garcia (University of California, Riverside)
Piaomu Liu (Bentley University)
Ksheera Sagar (Purdue University)
Hannah Waddel (Emory University)

Scientific Committee:

Sumanta Basu (chair, Cornell University)
Analisa Flores (University of California, Riverside)
Esra Kurum (University of California, Riverside)
Kevin Lee (Western Michigan University)
Piaomu Liu (Bentley University)

Event Type


NISS Graduate Student Network


Procter & Gamble Co.
National Institute of Statistical Sciences


$20 registration for Graduate Students. All other registrations are $50


Virtual Conference