[ds-undergrads] Fwd: 10/20 at 12:30-2pm ET: Join us this Friday for the Alumni Panel: 3rd event in Undergrad Guide for Grad School virtual series!

Jun Li jun.li at ucr.edu
Mon Oct 16 14:28:51 PDT 2023 

Dear students,

I hope some of you attended the Graduate Student Panel last Friday. This
Friday there is another Alumni Panel in the same series. One of the alumni
panelists and the moderator of this event both studied at UCR.

Jun

Jun Li
Professor of Statistics
Director of the Data Science Major
University of California, Riverside

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From: NISS Communications <communications at niss.org>
Date: Mon, Oct 16, 2023 at 1:59 PM
Subject: 10/20 at 12:30-2pm ET: Join us this Friday for the Alumni Panel:
3rd event in Undergrad Guide for Grad School virtual series!
To: <jun.li at ucr.edu>


Register now for free! Our alumni panel of impressive early career
professionals will share experiences and advice from journey after grad
school.
View this email in your browser
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Attend this virtual Alumni Panel of Early-Career Professionals on Friday,
October 20, 2023 at 12:30-2pm ET!
This is a free virtual alumni panel for aspiring graduate students in
statistics, biostatistics and data science degrees! We encourage current
undergraduate students and others thinking about sending in their
applications soon to join. See full details on the event page here
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.

This event is the 3rd and last event in the Undergraduate Student Guide for
Grad School
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virtual series!

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*Alumni Panel Overview:*

Throughout this series, we've heard from prestigious academic programs and
current graduate students from Statistics, Biostatistics and Data Science
programs; but where could you go professionally after you graduate and
obtain your your PhD or Master's degree? Join us for a captivating and
informative Alumni Panel where you will hear from our impressive early
career professionals who graduated from advanced degrees in Statistics,
Biostatistics, and Data Science programs from some of our NISS Academic
Affiliates. They will share their experiences, advice, and insights to help
you navigate the transition from your graduate degree to the professional
world!

This alumni panel is an excellent opportunity for students, educators, and
professionals interested in the statistical and data science fields to gain
inspiration and insights from those who have successfully navigated similar
paths. Whether you're a student contemplating your career choices or a
seasoned professional seeking to stay updated with industry trends, this
panel discussion promises to be enlightening and thought-provoking.
Register on Zoom
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*Alumni Panelists *

*Lili Wang*, Data Scientist, Youtube Trust & Safety and Payment Risk

   - Recieved PhD Biostatistics, MS Biostatistics, University of Michigan
   (2016), MS Molecular Biology, University of Michigan (2014)

*Ben Seiyon Lee*, Assistant Professor, Department of Statistics at George
Mason University

   - Received PhD, Statistics, Pennsylvania State University, 2020

*Christian Dueñas *is a Data Scientist at Red Bull

   - Received MS in Statistics from University of California, Riverside,
   2023

*Moderator*

*Rebecca Kurtz-Garcia*, Smith College

   - Received PhD, Statistics, University of California, Riverside, 2023


*Key Topics*

*Career Trajectories: *Learn how these alumni transitioned from their
academic studies to fulfilling careers in diverse industries, such as
healthcare, finance, technology, and more.

*Challenges and Opportunities:* Gain insights into the challenges they
faced and the opportunities they seized during their professional journeys.

*Impact of Statistical Education:* Discover the pivotal role statistical
education played in shaping their careers and enabling them to solve
real-world problems.

*Advice for Aspiring Data Scientists:* Get valuable advice and tips for
students and early-career professionals looking to excel in the field of
statistics and data science.

Don't miss this chance to connect with NISS Academic Affiliate alumni and
broaden your understanding of the limitless possibilities that a
statistical education can offer! Mark your calendars for October 20, 2023,
at 12:00 PM ET, and register now to secure your spot for this enlightening
webinar. We look forward to having you join us for this engaging discussion!
*About Alumni Panelists*

*Lili Wang* is a data scientist at YouTube, working on multiple exciting
projects related to YouTube's Trust & Safety and Payment Risk. Before
joining YouTube, she was a Data Scientist at Google where she designed and
built a platform to evaluate payments risk, worked on experiment design and
data analysis, and developed statistical methods for payments risk. For her
educational background, she was a research assistant for the University of
Michigan Kidney Epidemiology and Cost Center (UM-KECC) from 2015 to 2020
and an intern for Sanofi in 2019. She graduated with a Ph.D. in
Biostatistics from the University of Michigan and was advised by Prof.
Douglas E. Schaubel and Prof. Peter Xuekun Song. Her research interests
include developing statistical methods and software for dependent event
data analysis, infectious disease transmissions, causal inference, and
machine learning.


*Ben Seiyon Lee *is an Assistant Professor in the Department of Statistics
at George Mason University. Ben Lee’s research interests include (1)
computational methods for modeling high-dimensional spatial/Spatiotemporal
data; (2) statistical methods and algorithms for calibrating complex
computer models; and (3) interdisciplinary research in the environmental
sciences. Lee's most exciting project was calibrating a hydrological
computer model on flash floods and inland flooding in central Pennsylvania.
His research goals included finding out how global warming affects the
severity of inland floods and how those projections affect flood zones and
insurance. So, he designed a hydrological computer model to project future
inland flooding hazards. To aid him in his research, he studied data on the
streamflow heights (water levels) in Selinsgrove, PA, and temperature
inputs from high-quality climate models. He analyzed his data using the
Sequential Monte Carlo to calibrate hydrological models and further
assessed future hazards and risks based on climate change scenarios. He
teaches survival analysis (STAT668) and alternative regression methods
(STAT676) for the department. He's involved in many organizations such as
student seminar co-chair, faculty advisor to the graduate student
association, and liaison to the National Institute of Statistical Science
(NISS).


*Christian Dueñas* is a Data Scientist at Red Bull where he works on
various projects related to growth opportunities within the company. Most
of his daily tasks involve performing data analysis, statistical modeling
and web scraping. He began as an intern in the Summer of 2022, and landed a
full-time data scientist position after finishing graduate school. He is an
alumnus of the University of California, Riverside, where he obtained a
B.S. (2021) and an M.S. (2023) in Statistics. During his time at UCR,
Christian also worked as researcher for the United States Department of
Agriculture. He performed the statistical analyses for two RNA-seq
experiments, both of which became peer-reviewed publications in scientific
journals. He was also the co-president of UCR’s undergraduate statistical
club, HiSS, and led student-based projects regarding the effect of COVID-19
on undergraduates in the statistics department.

*About Our Moderator*
*Rebecca Kurtz-Garcia*, is an assistant professor of mathematics and
statistical and data sciences at Smith College, Department of Statistical &
Data Sciences. She earned her M.S. degree in statistics at Ball State
University and her Ph.D. in applied statistics from the University of
California, Riverside. She has worked on a variety of projects related to
time series, reliability analysis, biostatistics, sports analysis and
fiscal policy.  Her current research is on robust variance estimation for
dependent multivariate data, which is often a critical component in
hypothesis-testing procedures. Common settings with dependent data include
economic indicators, steady state simulations, environmental metrics and
other time series applications. Rebecca is also one of the founding members
of the NISS Graduate Student Network.
*Organizing Committee*

*NISS Academic Affiliates Committee*

   - *Piaomu Liu*, Bentley University
   - *Analisa Flores*, University of California, Riverside
   - *Wei (Vivian) Li*, University of California, Riverside
   - *Samuel Wang*,  Cornell University
   - *Sharmistha Guha*, Texas A&M University

*NISS Graduate Student Network Committee*

   - *Hannah Waddel*, Emory University
   - *Manqi Cai*, University of Pittsburgh
   - *Rebecca Kurtz-Garcia*, Smith College
   - *Piaomu Liu*, Bentley University
   - *Samuel Wang*,  Cornell University
   - *Sharmistha Guha*, Texas A&M University

Register Today!
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-- 
Jun Li
Professor of Statistics
University of California, Riverside
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