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
PhD student in the Statistics Department at the University of California, Riverside
PhD student in the department of statistics at Texas A&M University in College Station, Texas
PhD student in the Statistics Department at Cornell University
Statistics PhD student at Texas A&M University
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.
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.
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!
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.