The Department of Computer Science is pleased to announce that we will offer a seminar presentation. All are welcome to attend, but registration is required. Please register at this link:
Graduate students are invited to attend these Computer Science Seminars as part of their degree fulfillment requirements.
DATE: Friday, November 1
TIME: 1:00 - 2:00 p.m.
LOCATION: Comal 212
PRESENTER: Dr. Joshua Chang, UT Dell Medical School
TITLE: Finding Optimal Stimulus Waveforms with Intelligent Algorithms
Abstract: The use of electrical stimulation as medicine is becoming more prevalent today thanks to advances in technology from both a hardware and a software perspective. Most of these electroceutical devices use simple waveforms, where clinicians can empirically tune the parameters without altering the fundamental shape of the stimulus. This process takes a long time, and these waveforms use much more energy than necessary leading to potential adverse side effects and decreased battery life. In this talk, we examine how stochastic search techniques and other advances in intelligent algorithms can be brought to bear to develop patient-specific treatment protocols.
Bio: Joshua Chang completed both his Bachelors of Science as well as his Masters of Engineering at MIT in Electrical Engineering and Computer Science, focusing on signal processing and artificial intelligence. His masters dissertation was completed at MIT Lincoln Laboratory in missile tracking using different radar modalities. Before pursuing an MD/PhD at the University of Massachusetts Medical School (UMass), he worked as a software engineer at the Broad Institute and Harvard’s School of Public Health – Center for Health Decision Science. At UMass, he completed thesis in Quantitative Health Sciences and Neurology, under the supervision and mentorship of Dr. David Paydarfar designing and developing adaptive control algorithms to optimize stimulus waveforms for implantable medical devices. He continues his research now at Dell Medical School, studying ways to leverage artificial intelligence to better improve healthcare across diagnostics, therapeutics and predictive analytics.
Deadline: Nov. 2, 2019, midnight