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  • Thursday, Oct 12th
    8:00 AM – 9:30 AM PDT
    Computational Method Development in Deep Learning
    Location: 324 (Center, Level 3)
    Moderator: Sepideh Dolatshahi, PhD – University of Virgina, Charlottesville
    Moderator: Daniel Abebayehu
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    8:00 AM – 8:15 AM PDT
    Diffusion Model Regulated by Medical Image Statistics
    Location: 324 (Center, Level 3)
    Presenting Author: Christopher Wiedeman (he/him/his) – Rensselaer Polytechnic Institute
    Co-Author: Chuang Niu – Rensselear Polytechnic Institute
    Co-Author: Yongyi Shi – Rensselear Polytechnic Institute
    Co-Author: Wenjun Xia – Rensselear Polytechnic Institute
    Primary Investigator: Ge Wang – Rensselaer Polytechnic Institute
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    8:15 AM – 8:30 AM PDT
    Non-Invasive Screen Exposure Detection Using Object Detection with Spatial Reasoning
    Location: 324 (Center, Level 3)
    Presenting Author: Xueshen Li (he/him/his) – Stevens Institute of Technology
    Co-Author: Steven Holiday – The University of Alabama
    Co-Author: Matthew Cribbet – The University of Alabama
    Co-Author: Susan White – The University of Alabama
    Co-Author: Edward Sazonov – The University of Alabama
    Primary Investigator: Yu Gan – Stevens Institute of Technology
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    8:30 AM – 8:45 AM PDT
    Inferring dynamic regulatory interaction graphs from time series data
    Location: 324 (Center, Level 3)
    Presenting Author: Dhananjay Bhaskar, PhD (he/him/his) – Yale University
    Co-Author: Daniel Sumner Magruder – Yale University
    Co-Author: Edward De Brouwer (he/him/his) – Yale University
    Co-Author: Aarthi Venkat (she/her/hers) – Yale University
    Co-Author: Frederik Wenkel (he/him/his) – Mila, Université de Montréal
    Last Author: Guy Wolf (he/him/his) – Mila, Université de Montréal
    Primary Investigator: Smita Krishnaswamy (she/her/hers) – Yale University
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    12:30 PM – 2:00 PM PDT
    Applications of Deep Learning Approaches in Biomedical Engineering
    Location: 325 (Center, Level 3)
    Moderator: Belinda Akpa, PhD (she/her/hers) – Oak Ridge National Laboratory
    Moderator: Bryana Harris, BChE – University of Virginia
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    12:30 PM – 12:45 PM PDT
    Using Convolutional Dictionary Learning to Detect Task-Related Neuromagnetic Transients and Ageing Trends in a Large Open-Access Dataset
    Location: 325 (Center, Level 3)
    Presenting Author: Lindsey Power (she/her/hers) – Dalhousie University
    Co-Author: Cédric Allain – Université Paris-Saclay
    Co-Author: Thomas Moreau – Université Paris-Saclay
    Co-Author: Alexandre Gramfort – Université Paris-Saclay
    Last Author: Timothy Bardouille – Dalhousie University
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    12:45 PM – 1:00 PM PDT
    Detrimental Activity and Sleep Habits in Children and Adolescents with Obesity during the COVID-19 Pandemic
    Location: 325 (Center, Level 3)
    Presenting Author: Karnika Singh, MS (she/her/hers) – Duke University Department of Biomedical Engineering, Duke Center for Childhood Obesity Research
    Primary Investigator: Jessilyn Dunn, PhD – Duke University Department of Biomedical Engineering, Duke University Department of Biostatistics & Bioinformatics, Duke Center for Childhood Obesity Research
    Co-Author: Sarah Armstrong, MD – Duke University Department of Pediatrics, Duke University Department of Population Health Sciences, Duke University Department of Global Health, Duke Center for Childhood Obesity Research
    Co-Author: Brooke Wagner – Duke University Department of Pediatrics, Duke University Department of Population Health Sciences, Duke Center for Childhood Obesity Research
    Co-Author: Julie Counts – Duke University Molecular Physiology Institute, Duke Center for Childhood Obesity Research
    Co-Author: Asheley Skinner – Duke University Department of Population Health Sciences, Duke Center for Childhood Obesity Research
    Co-Author: Melissa Kay – Duke University Department of Pediatrics, Duke Center for Childhood Obesity Research
    Co-Author: Jennifer Li, MD MHS – Duke University Department of Pediatrics, Duke Center for Childhood Obesity Research
    Co-Author: Svati Shah, MD – Duke University Molecular Physiology Institute, Duke Center for Childhood Obesity Research
    Co-Author: Nancy Zucker, PhD – Duke University Department of Psychiatry and Behavioral Science, Duke Center for Childhood Obesity Research
    Co-Author: Cody Neshteruk, PhD – Duke University Department of Population Health Sciences, Duke Center for Childhood Obesity Research
    Co-Author: Mary Story, PhD – Duke Global Health Institute, Duke Center for Childhood Obesity Research
    Co-Author: Lilianna Suarez – Duke University Department of Pediatrics, Duke Center for Childhood Obesity Research
    Co-Author: William Kraus, MD – Duke University Molecular Physiology Institute, Duke Center for Childhood Obesity Research
    Co-Author: Alexandra Zizzi, MSPH – Duke University Department of Pediatrics, Duke Center for Childhood Obesity Research
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    1:00 PM – 1:15 PM PDT
    Machine learning chained neural network analysis of oxygen transport amplifies the physiological relevance of vascularized microfluidic systems
    Location: 325 (Center, Level 3)
    Co-Author: James Tronolone – Texas A&M University
    Presenting Author: Abhishek Jain, PhD – Texas A&M University
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    1:15 PM – 1:30 PM PDT
    ENABLING IN SILICO SARS-COV-2 VARIANT DEEP MUTATIONAL SCANNING AND MONOCLONAL ANTIBODY REENGINEERING WITH DEEP LEARNING
    Location: 325 (Center, Level 3)
    Presenting Author: Tomasz Kaszuba, Masters in Biomedical Engeering (he/him/his) – Washington University in St. Louis
    Primary Investigator: Daved Fremont – Washington University in St. Louis
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    1:30 PM – 1:45 PM PDT
    Developing an Ultrasound-Electrocardiography Deep Learning Framework for Predictive Cardiac Gating under Arrhythmia and Variable Heart Rate Conditions
    Location: 325 (Center, Level 3)
    Presenting Author: Shambavi Ganesh, MS (she/her/hers) – Georgia Institute of Technology
    Co-Author: Pamela Bhatti – Georgia Institute of Technology
    Co-Author: Srini Tridandapani – University of Alabama at Birmingham
    Co-Author: Brooks Lindsey – Walter H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University
    Data Analysis and Deep Learning
  • Thursday, Oct 12th
    1:45 PM – 2:00 PM PDT
    Stress-strain Prediction of Porcine Heart Valves from Aortic Surface Imaging Using Convolutional Neural Networks
    Location: 325 (Center, Level 3)
    Presenting Author: Luis H. Victor, MS (he/him/his) – Rice Univeristy
    Primary Investigator: K. Jane Grande-Allen – Rice University
    Data Analysis and Deep Learning