There were more than 50 entries in the 2017 MIDAS Annual Symposium Student Poster Competition.
Best Overall
Data Analytics for Optimal Detection of Metastatic Prostate Cancer, Lead Author: Selin Merdan
Most Innovative Use of Data
Computable Hyper-Volume Phenotypes, Lead Author: Hanbo Sun
Optimally Weighted PCA for High-Dimensional Heteroscedastic Data, Lead Author: David Hong
Most Likely to have Societal Impact
Integrated Prediction of Wind Power Production, Lead Author: Jingxing Wang
Computational Testing of Scarf Algorithm for Near Feasible Stable Matching with Couples, Lead Author: Dengwang, Tang
Most Interesting Methodological Advancement
Personalized PageRank Estimation for Many Nodes: The Impact of Clustering on Complexity, Lead Author: Daniel Vial
A convex clustering formulation using the similarity matrix, Lead Author: Yutong Wang
Most Likely to have Transformative Scientific Impact
Predicting Genome-Wide Transcription Factor Binding and Chromatin Architecture from Chromatin Accessibility Data, Lead Author: Ricardo D’Oliveira Albanus
Data-Driven Tools for Patient Risk Stratification for ARDS, Authors: Tejas Prahlad, Daniel Zeiberg
Most Likely to have Health Impact
Predicting the Distribution of Emotion Perception: Capturing Inter-rater Variability, Lead Author: Biqiao Zhang
Detecting differentially expressed metabolic pathways with adjustments for macronutrient intake, Lead Author: Teal Guidici
