Data Science Poster Fair

We invite you to attend the annual Data Science Poster Fair! This year's event will be held virtually via Zoom on Friday, April 23 from 11:30 a.m. - 1:00 p.m.

Every year, data science M.S. students present their capstone projects during this event. This year, research preview videos have been posted below so attendees can view and plan their participation during the virtual event. Attendees will have the ability to move between breakout rooms as they please. In order to do so attendees will need to have the Zoom version 5.3 or later.

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.  This event will be offered via a single Zoom session with 4 parallel sessions organized into 5 quarter-hour time slots.  Each parallel session will be in a separate Breakout Room within the same main Zoom session.  If you have Zoom version 5.3 or later, you will be able to move between breakout rooms at will.  Each presenter has already submitted a video on their project.  We urge you to view the videos in advance. Click on the title of each project in the table below to find the abstract and a link to the video. During the live event, the Zoom host will be a moderator who can help with logistical problems.  The moderator can be contacted via the Chat function or by returning to the main Zoom room.

Schedule

Breakout Session When Project A Project B Project C Project D
1 11:30 am - 11:45 am “A Causal Analysis of Bipolar Disorder”
Hunter Chavis-Blakely
Advisor: Erich Kummerfeld		 “Detecting mental state using Machine Learning”
Mingqian Duan
Advisor: Ju Sun		 “Modeling COVID-19 Case Counts with Long Short-Term Memory Networks”
Brandon Voigt
Advisor: Tracy Flood		 “Exploring User Engagement in An Online Health Community”
Ruyuan Wan
Advisor: Lana Yarosh, Maria Gini
2 11:45 am - 12:00 pm “Federated Learning approach to crop identification from satellite data”
Anubha Agrawal
Advisor: Kevin Silverstein		 “Defining and Monitoring Patient Clusters Based on Therapy Adherence in Sleep Apnea Management”
Mourya Karan Reddy Baddam
Advisor: Jaideep Srivastava		 “Inferring level of social connectedness from observed online/offline behavior”
Ayushi Rastogi
Advisor: Lana Yarosh		 “Deep Learning Approaches for Breast Cancer Related Concepts Extraction from Electronic Health Records”
Sicheng Zhou
Advisor: Rui Zhang
3 12:00 pm - 12:15 pm "Using electronic health records to understand the effects of dietary supplements among patients with Mild cognitive impairment"
Jiyang Chen
Advisor: Rui Zhang		 “Machine Learning in Stock Trading”
Yuanyuan Qiu
Advisor: Paul Schrater		 “Deep Learning for Morphology Detection of Self-Assembly in Atomistic Simulation”
Zhengyuan Shen
Advisor: Ilja Siepmann		 “Prediction Model for Mortality in Patients with Rib Fractures Based on ICU Timeline”
Qixian Zhao
Advisor: Christopher Tignanelli
4 12:15 pm - 12:30 pm “Implementing GAN-based method for real-valued medical time series data generation”
Anushree Choudhary
Advisor: Jaideep Srivastava		 “Fraud Detection Using Machine Learning Methods”
Sheng Huang
Advisor: Daniel Boley		 “Anomaly detection in Ship Trajectories”
Divya Shrinivasa Nairy
Advisor: Shashi Shekhar		 “Deep Neural Network Diagnosis of Autism Spectrum Disorder Through Visual Image Eye Movements”
Connor Theisen
Advisor: Catherine Qi Zhao
5 12:30 pm - 12:45 pm “Fake Chest Radiograph Generation”
Rutvij Umesh Bora
Advisor: Daniel Boley		 “Hazard Detection for the Visually Impaired”
Jason Moericke
Advisor: Paul Schrater		 “Leveraging Machine Learning to Predict Inherited Variants Associated with Chronic Lymphocytic Leukemia”
Raphael Mwangi
Advisor: Cavan Reilly

"Chest X-Ray Images Generation Using GAN"

Iris Yan
Advisor: Daniel Boley

 

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

Start date
Friday, April 23, 2021, 11:30 a.m.
End date
Friday, April 23, 2021, 1 p.m.
Location

Zoom link for live session (no longer accessible as the event has past)

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