Undergraduate Student Guide for Grad School: Grad Student Panel

Friday, October 13, 2023 at 2:00 pm - 3:00 pm ET

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

Jericho Lawson  (Moderator)

PhD Student in the Statistics Department at the University of California, Riverside

Manqi Cai

PhD student in the Biostatistics Department at University of Pittsburgh

Sithija Manage

PhD Student in the Statistics Department at Cornell University

Hannah Waddel

PhD Student in the Biostatistics Department at Emory University

Lauren Vanasse

MS Student in the Biostatistics Department at Emory University

Yanru (Ru) Ma

MS Student in the Biostatistics Department at Emory University

Jacob Andros 

PhD Student in the Department of Statistics at Texas A&M University in College Station, Texas

Sam Gailliot

PhD Student in the Department of Statistics at Texas A&M University in College Station, Texas

Isha Vaish

MS Student in the Department of Data Science at Harvard 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 Our Graduate Students


Jericho Lawson is currently a 4th year PhD student in the Statistics Department at the University of California, Riverside. His research interests include high-dimensional variable selection, sports statistics, and machine learning. He is currently exploring the application of deep-generated knockoffs for multinomial data. On top of research, he is also committed to instructing undergraduates on general statistics, quality improvement, and statistical computing. In his free time, Jericho enjoys trying new food, exploring new places, and hiking.



Manqi Cai is a 5th-year PhD student in the Biostatistics Department at the University of Pittsburgh. Her research is centered on creating statistical methods for high-dimensional genomics data that consider cell-type heterogeneity. Additionally, Manqi has contributed to collaborative studies on Alzheimer's disease and chronic kidney disease. She is a member of the executive committee for the NISS Graduate Student Network. Before embarking on her PhD, she obtained her MS in Biostatistics from Columbia University.



Sithija Manage is a second year Statistics PhD student at Cornell University. His current area of interest is compositional data - specifically tackling the issues that arise when working with microbiome data. Sithija has a passion for teaching, is a member of the Cornell Advanced Graduate Teaching cohort, and hopes to eventually become a professor so that he can help students achieve their goals. He also has a YouTube channel where he creates content about his Grad School experience!



Hannah Waddel is a biostatistics PhD candidate at Emory University, in her fourth year. Her dissertation research focuses on infectious disease modeling, particularly for swine influenza. She has also conducted collaborative research in meta-analyses, nutrition, and cerebrovascular diseases. Hannah serves on the executive committee for the NISS Graduate Student Network. She received her MS in Biostatistics at Emory University and her BS in Mathematics from the University of Utah and an MS in Biostatistics from Emory University.



Lauren Vanasse is a 2nd year Master's student in biostatistics at Emory University. Her thesis is primarily focused on using Bayesian spatio-temporal modeling to find the relationship between transportation vulnerability and diabetic foot ulcers in the state of Georgia. In addition, she is collaborating on research in the exploration of a new biomarker of cell death, circulatory pancreas-specific DNA methylation, and its impacts on Type 2 Diabetes. Lauren received her BA in Statistics and BS in Computational Biology from the University of Rochester. Outside of school, Lauren enjoys baking, cooking, and hiking!


Yanru (Ru) Ma is a 2nd-year master's student in biostatistics at Emory University. Her research passion lies in statistical methods for gene data. Her ongoing research focuses on spatial transcriptomics and chromatin accessibility. Additionally, Ru actively contributes to the Data Analytics and Biostatistics Core team at Emory School of Medicine. Prior to embarking on her statistical journey, Ru held an MD in Internal Medicine and Hematology from Peking University in China, and she practiced as a physician in her home country. In her free time, she enjoys cooking and hiking.


Jacob Andros is a 2nd-year PhD student in the department of statistics at Texas A&M University in College Station, Texas. His research focuses on Bayesian computing, big data problems, and unsupervised learning. In particular, he enjoys seeking out new ways to integrate uncertainty quantification methods from Bayesian statistics into machine learning frameworks. Most recently, Jacob has been working on a new R package that can carry out Bayesian spatial inference in parallel for massive datasets. He serves as a volunteer data science camp instructor during the summers and is also teaching an introductory statistics course to life science majors this semester. After completing a PhD, Jacob hopes to continue in academia as a postdoc or professor. Outside of school, he enjoys watching baseball and playing with his dog.


Sam Gailliot is a 4th year Statistics PhD student at Texas A&M University. His research focuses on statistical methodology for environmental problems. Specifically, he works on Bayesian computational methods for massive dimensional data, scalable Gaussian process regression on manifolds and applications of sequential analysis to climate change attribution. In addition to graduate school, Sam is a year- round intern at Sandia National where he works on statistical methods for multilayer network modeling. Outside of school and work Sam enjoys playing guitar, reading, and watching college football.


Isha Vaish is currently a second year Data Science MS student at Harvard University and she will be joining Microsoft as a full time data scientist this coming summer. She’s originally from Cary, NC and she completed her undergraduate degree from Cornell University where she double majored in Computer Science and Statistics. During her junior year, I fell in love with her “Intro to Machine Learning” class and decided to pursue data science as a career. She applied for Master’s programs to gain more experience with machine learning and strengthen her theoretical background. She has previous experience as a data science intern, research assistant and teaching assistant. She is passionate about data science, especially machine learning and artificial intelligence. 

Event Type


National Institute of Statistical Sciences
NISS Academic Affiliates Committee
NISS Graduate Student Network


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