Prior Sessions
2018: Data Intensive Scientific Computing
The 2018 Summer DISC REU students learned how to use high performance computing and big data technologies to enable new discoveries in computer science, physics, and biology. The students spent 10 weeks working collaboratively with expert mentors on grand challenge problems, like discovering new galaxies in digital imagery, discovering new fundamental particles, using gene sequencing to understand disease, and predicting the effect of new drugs using computational modeling, at Notre Dame. To do this, we harnessed large scale computing clusters and big data systems composed of hundreds or thousands of machines, all working together in concert. To make advances in these areas, our goal is to train the next generation of scholars to be adept in both scientific domains and advanced computing techniques.
The DISC REU summer program is made possible by the U.S. National Science Foundation under grant CNS-1560363.
Alumni Projects
Jeremy Speth
Generation and Matching of Bipartite Graphs
University of Nevada, Reno Junior Computer Science & Engineering (Minor in Mathematics)
Nicholas Potteiger
Archiving Workflows Onto Cloud Based Storage
University of Maryland, Baltimore County Freshman Computer Science
Khaya Klanot
Deep Learning for Particle Physics: Investigating Neural Network Structure and Hyperparameters
Yale University Sophomore Mathematics & Physics
Eric Gronda
Visual Analytics of Student Clickstream Data Using Higher Order Networks
University of Maryland, Baltimore County Freshman Computer Engineering
Jacob Gersfeld
SNP Isolation and Primer Design in R. pomonella
University of North Carolina at Chapel Hill Sophomore Computer Science (Minor in Chemistry)
Jon Genty
Classifying Aging- and Non-Aging-Related Genes in Dynamic Protein-Protein Interaction (PPI) Networks
University of Houston Sophomore Computer Engineering (Minor in Mathematics)
Anne Freeman
Developing Software to Process Malaria Genetic Data for QTL Analysis in a Shared Parent Genetic Cross
Georgetown University Junior Computer Science
Diego Fernandez
Lobster: Harnessing Opportunistic Clusters with a Workflow Management Tool for CMS Data Analysis
University of Edinburgh Year 1 Masters in Physics
Aidan Draper
Classifying marshland plant species by processing light reflectance in satellite images
Elon University Junior Statistics & Computer Science (Minors in Data Science & Mathematics)
Kevin Choy
A Web-Based Tool for Flexible Learning-Free Segmentation And Reconstruction for Sparse Neuronal Circuit Tracing
University of Texas at Austin Junior Biomedical Engineering
Kendrea Beers
Exhaustive Heterogeneous Graphlet Counting for Network Alignment
Oregon State University Freshman Computer Science (Minors in Mathematics, Physics, and/or Philosophy)
