Are you an undergraduate student eager to learn more about the next steps in your academic journey? Join us for a captivating and informative Graduate Student Panel where accomplished graduate students from advanced degrees in Statistics, Biostatistics, and Data Science will share their experiences, advice, and insights to help you navigate the transition from undergrad to graduate studies.

Graduate Student Panelists

Jason B Cho, Cornell University

Jeremy Flood, North Carolina A&T

Jess Kunke, U Washington

Noé Vidales, UC Riverside

Hannah Waddel, Emory University

Moderator

Georgia Smits, Cornell University

Event Highlights

Diverse Perspectives | Our panel consists of graduate students from MS and PhD degrees in Statistics, Biostatistics, and Data Science. This ensures a well-rounded discussion that caters to a wide range of interests.

Personal Journeys | Each graduate student panelist will take you on a journey through their personal experiences, detailing how they chose their graduate programs, managed the application process, and overcame challenges along the way.

Research and Projects | Discover the exciting research projects and initiatives that our panelists are currently engaged in. Learn how their studies contribute to their fields and make a positive impact on society.

Balancing Academics and Life | Balancing academic pursuits with personal life is a critical skill in graduate school. Panelists will share their strategies for managing coursework, research, and maintaining a healthy work-life balance.

Q&A Session | Have burning questions about graduate school? The event will conclude with an engaging Q&A session, where you can direct your inquiries to the panelists and gain valuable insights. This is your chance to ask specific questions, seek advice, and build connections.

Whether you're intrigued by the prospect of advanced research, curious about specialized fields of study, or simply want to understand what life as a graduate student is like, this panel has something for everyone. Don't miss this fantastic opportunity to gain invaluable insights and set yourself up for success in your academic journey!

This event is free and open to all undergraduate students. Prepare to be inspired, informed, and motivated to take your academic ambitions to the next level. We look forward to seeing you at the Graduate Student Panel!

About the Panelists

Jason B Cho is a fourth-year Ph.D. student in Statistics at the Department of Statistics and Data Science at Cornell University under Professor David S. Matteson. His resarch interest is in Bayesian Time-series Analysis. In their most recent work, they present a novel method for estimating time-varying volatility model called Adaptive Stochastic Volatility (ASV). You may find the preprint in this link. Before joining the Ph.D. program, he completed a Master's degree in animal science, specializing in Precision Agriculture under professor Quirine M. Ketterings, Joe Guinness and Jan van Aardt. Jason's research focused on the spatio-temporal analysis of yield monitor data, high-resolution geo-referenced yield estimates, and development of statistical tools to help farmers make better nutrient management decisions.

Jeremy Flood is a fourth-year data science Ph.D. candidate at North Carolina A&T State University. There, he received the Chancellor's Distinguished Fellowship to assist his research in estimating finite population parameters using probabilistic and (potentially biased) convenience samples. Before his graduate studies, Jeremy earned a Bachelor of Arts in experimental psychology and a cognate in statistics from the University of South Carolina (UofSC). In addition to his academic pursuits, Jeremy works as an applied statistician at Liberty Mutual.

Jess Kunke (she/they) is a Ph.D. candidate in the Department of Statistics at the University of Washington in Seattle, advised by Tyler H. McCormick.  Driven by social and environmental applications, her research leverages network information to learn about human and animal populations.  Since 2020, she has been collaborating with the Tribal Exchange Network to develop and teach R workshops for Tribal environmental professionals and to provide one-on-one data science consulting.  Jess loves teaching math and computing to students and professionals both within and outside STEM fields.  She is also passionate about learning from other fields' ways of knowing such as qualitative and feminist methodology to develop research methods that center the communities they impact.  Jess enjoys running, finding slugs and giant leaves, eating good food, reading, crafting, and playing the piano.

Noé Vidales is a PhD candidate at UCR’s Statistics Department. His interests span the gamut from stochastic processes to the rise of populism in Latin America. He, currently, finds himself researching Markov chains and consistent variance estimators for serially correlated data. He tries to live his life by the three Cs: Culture, Curiosity, and Cycling. If you can’t find him, he will most likely be in one of two places: Cafebrería El Péndulo in Roma Norte or grabbing a coffee at Tierra Garat.

Hannah Waddel is a PhD candidate in Biostatistics at Emory University (Atlanta, GA). Her research focuses on phylodynamic infectious disease modeling methods which reconstruct infectious disease outbreaks by incorporating sampled pathogen genetic data. In addition, Hannah is a frequent collaborative biostatistician, with research projects across the schools of medicine and public health.

About the Moderator

Georgia Smits is a Ph.D. candidate in Statistics at Cornell University, where her research focuses on algorithmic fairness, time series modeling, and statistical computing. She has contributed to projects developing generative adversarial network (GAN) frameworks for improved fairness and applying quantile adaptations of time series models to detect financial risks and genetic associations. As a teaching assistant, she has supported courses in Bayesian Data Analysis, Statistical Computing, and Introductory Statistics and Data Science. In addition to her academic work, Georgia has gained industry experience through internships at MIT Lincoln Laboratory and The Johns Hopkins University, where she applied advanced AI and NLP techniques to real-world challenges. Prior to her doctoral studies, she worked as a Structured Products Analyst at Crédit Agricole CIB, facilitating trades across asset classes and supporting the transition from LIBOR to SOFR. She holds a B.S. in Physics with distinction from Yale University and is an active mentor in Cornell’s Directed Reading Program, encouraging undergraduate research in statistics.

About the NISS New Researchers Network

The National Institute of Statistical Sciences (NISS) is a national organization that works on issues related to information and quantitative analysis. The goal of the NISS New Researchers Network is to create connections among undergraduate and graduate students from different academic institutions and early-career professionals within the NISS Affiliates Program. The NISS New Researchers Network fosters collaboration and support among early-career statisticians, graduate students and undergraduate students offering resources and opportunities for professional growth.