Spotlight – Chris Glasz
Chris Glasz is a graduating senior in the class of 2016. Chris began his collegiate career by experimenting with a triple major in Computer Engineering, Music Composition and Chinese; however, after an introductory programming course, he switched his major to Computer Science, having found a passion for the field.
Among Chris’ favorite department courses are CSC 481 and CSC 440. CSC 481, an introductory artificial intelligence class, was the course that began his interest in machine learning, which has now become his central research focus. However, Chris feels that he may have learned the most in CSC 440, which is the department’s algorithm design and analysis course.
Chris has participated in multiple undergraduate research projects within the department, including a project advised by Dr. Jean-Yves Hervé, in which he worked on a virtual reality environment. In 2015, he presented a poster detailing the state of this research at the annual CCSCNE conference in Massachusetts, titled “Physiological Responses to Immersion in Virtual Reality“.
Chris has also engaged in his own independent research, under the supervision of Dr. Lutz Hamel, in the area of machine learning. This research included the implementation of an artificial neural network library in C++, capable of constructing deep convolutional networks using modular blocks. The library was later parallelized, and tested on the problem of classifying handwritten digits, achieving 99.07% classification accuracy.
Chris has worked as a teaching assistant in the department, most recently for the undergraduate Artificial Intelligence course (CSC 481), and for a special topics mathematics course taught by Professor Lamagna (MTH 108). He is also the Vice President of RamHacks, the University’s official Computer Science interest group, and was a coach for Dr. Hamel’s Programming Language Boot Camp.
After graduation, Chris plans to continue his academic career, and intends to complete a master’s degree, and later a Ph.D., in Computer Science, with a research focus in machine learning.