Laura Brown (CS/AIM) is the principal investigator on the research and development project, “Collaborative Research: CRISP Type 2: Revolution through Evolution: A Controls Approach to Improve How Society Interacts with Electricity” that has received a $699,796 grant from the National Science Foundation. Also working on the project are co-pi’s Chee WooiTen (ECE) and Wayne Weaver . . .
Canvas courses taught by Dr. Laura Brown and Leo Ureel (CS) were selected as two of the eight spring 2015 CTL Creative Canvas Course Contest (C-4) winners. Their Canvas courses were recognized as effective by both students and the Center for Teaching and Learning (CTL). Both instructors will have the opportunity to record a “video . . .
Assistant Professor of Computer Science Dr. Laura Brown’s research is centered broadly on the application and design of methods in artificial intelligence and machine learning. This work spans from the theoretical design of algorithms for feature selection and learning Bayesian networks, to the application of methods across domains including clinical healthcare, biomedicine, power distribution networks, . . .
Philart Jeon: PI, National Health Institute. “NRI: Colloborative: Interactive Robotic Orchestration – Music-based emotion and social interaction therapy for children with ASD,” 2014-2017. Philart Jeon: Co-PI, US DOT-OST, National University Rail Center Project. “NURail-Tier I,” 2014-2017 Robert Pastel & Charles Wallace: CI-Team, National Science Foundation.”Environmental CyberCitizens: Engaging Citizen Scientists in Global Environmental Change through Crowdsensing . . .
Laura Brown and Zhenlin Wang (CS) have received $91,451 of $299,993 from the National Science Foundation for the first year of a three-year research and development project titled “CSR: Small: Collaborative Research: Adaptive Memory Resource Management in a Data Center-A Transfer Learning Approach.”
PI Timothy C. Havens (ECE) and Co-PIs Laura Elizabeth Brown (CS), Saeid Nooshabadi (ECE) and Allan Struthers (Math), “BIGDATA: F: DKA: Heterogeneous Algorithms for Media Mining in Big Data Using Massively-Parallel Architectures,” National Science Foundation.