BME – Healthcare Informatics Program


session topic
Healthcare Informatics
9:00-9:30 Aidong Zhang NSF
9:30-10:00 Jeremy Weiss CMU
Machine learning and survival analysis to forecast clinical risk from electronic health records
10:00-10:30 Munmun De Choudhury Georgia Tech
session topic Bioinformatics
11:00-11:30 Srinivas Aluru Georgia Tech
11:30-12:00 Gregory Cooper
University of Pittsburgh
12:00-12:30 Steve Qin
Georgia Tech/Emory
12:30-1:30 lunch/posters
1:30-2:30 plenary
session topic Neuroinformatics
2:30-3:00 Steve Chase CMU
Using machine learning to understand biological learning
3:00-3:30 Eva Dyer Georgia Tech
3:30-4:00 Daniel Clymer CMU
Convolutional Neural Networks to Improve Radiologist Workflow on 3D Medical Images: Application to Shoulder Labral Tears
session topic Bioinformatics
4:30-5:00 Mark Borodovsky
5:00-5:30 Peng Qiu
5:30-6:00 Ankit Agrawal Northwestern
Big Data Analytics for Deriving Predictive Healthcare Insights from Electronic Healthcare Records
June 8 speaker first name speaker last name affiliation presentation title
session topic Neuroinformatics
9:00-9:30 Rob Kass CMU
Torus Graphs for Multivariate Phase Coupling Analysis
9:30-10:00 Chethan Pandarinth GT/Emory
LFADS: Inferring precise estimates of neural population state and dynamics using sequential auto-encoders
10:00-10:30 Will Bishop CMU
Stabilized Brain-Computer Interface through Neural Manifold Alignment
11:00-11:30 David Goldsman Georgia Tech
Using Machine Learning and Simulation to Compare Increased Risk Kidney Transplant Survival to Waiting for a Non-Increased Risk Organ for Hepatitis C Negative Recipients
11:30-12:00 Melissa Knothe-Tate UNSW
Towards Cellular Epidemiology of Degenerative Disease Using Geographic Information Systems, Multi-beam Electron Microscopy, and Machine Learning
12:00-12:30 May D Wang Georgia Tech
Improving Multi-class Classification for Endomicroscopic Images by Semi-Supervised Learning with Convolutional Autoencoders
12:30-1:30 lunch/posters
1:30-2:30 plenary
session topic systems biology
2:30-3:00 Russell Schwartz CMU
Learning models of clonal evolution from cancer genomic data
3:00-3:30 Mark Styczynski Georgia Tech
Machine Learning in Systems-Scale Metabolic Analysis and Modeling
3:30-4:00 Matt Ruffalo CMU
Network-Guided Prediction of Aromatase Inhibitor Response in Breast Cancer
session topic
healthcare informatics
4:30-5:00 Leontios Hadjileontiadis Khalifa University of Science and Technology
Analysis of keystroke dynamics in mobile touchscreen for depression detection
5:00-5:30 Asim Smailagic CMU
Machine Learning and Virtual Coaches