Ten MInDS students
presented their research to industry leaders at the annual Computing-Mines Affiliates Partnership Program ( C-MAPP) event in Golden, Colorado.
Members of the team presented applications of machine learning in additive manufacturing, robotics, and bioinformatics. The event was an opportunity for the team to network with members of industry, meet new computer science students, and showcase the exciting MInDS@Mines research portfolio.
Saad explains his work on ex4ml, a Python library for streamlining machine learning experiments.
Madeline and Zoe present a method for visualizing machine learning results on a brain.
Lou describes the intuition behind the Sample-Specific Distance to CS@Mines Faculty member Dr. Bo Wu.
Kai L. shows how his method can accurately identify locations regardless of weather conditions.
Kai N. introduces a new MInDS@Mines project aimed at identifying voice-based biomarkers that are predictive of coronary artery disease.
Lyujian answers questions on his deep learning approach for image segmentation with applications in additive manufacturing.
Arun speaks to a Google employee about his ADMM-based clustering algorithm that can incorporate uncertain data.
Matt describes the results of the Hough Transform and its application in identifying additively manufactured parts.
Haoxuan shows a C-MAPP attendee how manifold learning can be used to cluster corrupted data.