Data Science Poster Fair

We invite you to attend the Fall 2022 Data Science Poster Fair! This semester's event will be held on Friday, December 2 from 10 a.m. - 12 p.m.

As a part of their degree requirements, Data Science M.S. students conduct research under the direction of a faculty advisor culminating with a capstone project and poster presentation. Students presenting at this event will discuss details of their capstone project, including their driving question, methods, and results, and will be available to address questions and connect with guests during their time slot. Faculty from numerous departments across the University are affiliated with the data science graduate program, therefore a variety of areas are represented with each student’s capstone project. 

The poster fair is open to the public and all interested undergraduate and graduate students, alumni, staff, faculty, and industry professionals are encouraged to attend.  To let us know you'll be joining us, please fill out our RSVP form. We ask those who plan to attend to RSVP by November 27th. 

Schedule

Breakout Session When Project A Project B Project C Project D
1 10 - 11 a.m.

Pui Ying Yew
Advisor: Chih-Lin Chi, Institute for Health Informatics

"Association of the 2013 blood cholesterol guidelines and generic statin availability with statin treatment in the U.S. population"

Shuai An
Advisor: Daniel Boley, Department of Computer Science & Engineering

"Projecting rice yield in the Mekong River Delta under climate change"

Linxin Li
Advisor: Qian Qin, School of Statistics

"Performance of MCMC in different scenario"

Sarthak Jain
Advisor: Sandra Safo, School of Public Health

"Disease classification using multi-view longitudinal data with Deep IDA"
2 11 - 12 p.m.

Fafa Hoshyargar
Advisor: Ilja Siepmann, Department of Chemistry

"Neural networks for automated soft-material mesophase discovery from simulation and experimental microscope data"

Anthony Cotter
Advisor: Michael Steinbach, Department of Computer Science & Engineering

"Risk model development for peer to peer sports betting"

Yizhe Wang
Advisor: Qian Qin, School of Statistics

"Exploring time series stock market forecasting with CPI, PPI and Nonfarm data"

  

 

Please contact Allison Small at csgradmn@umn.edu with any questions.

Start date
Friday, Dec. 2, 2022, 10 a.m.
End date
Friday, Dec. 2, 2022, Noon
Location

Keller Hall 3-176 and Keller Atrium

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