CS majors Michael Altschuler (Class of 2019), Garrett Beatty (2019), and Ethan Kochis (2020), presented two research papers at the IEEE ICSC 2019 conference in Newport Beach, California, held January 29 – February 1. Both papers were written in collaboration with CS faculty member Dr. Michael Bloodgood as part of the students’ mentored research conducted in fall 2018. Both papers were supported by TCNJ’s Support of Scholarly Activities (SOSA) program and by use of the ELSA high performance computing cluster at TCNJ, supported by the National Science Foundation under grant number OAC-1828163. Dr. Bloodgood also attended the conference and served as a session chair during the conference.
Michael Altschuler and Dr. Bloodgood co-authored a paper titled: “Stopping Active Learning based on Predicted Change of F Measure for Text Classification.” In this paper, a new stopping method called Predicted Change of F Measure is introduced that provides users an estimate of how much performance of machine learning models can be expected to change at each iteration of learning.
Garrett Beatty, Ethan Kochis, and Dr. Bloodgood co-authored a paper titled: “The Use of Unlabeled Data versus Labeled Data for Stopping Active Learning for Text Classification.” This paper compares and contrasts the advantages and disadvantages of methods for stopping machine learning of text classification systems using three different information sources that have not been compared and contrasted before, with the perhaps surprising result that methods that use unlabeled data are more effective than methods that use labeled data. This paper was also supported by TCNJ’s Mentored Undergraduate Summer Experience (MUSE) program.
More information about IEEE ICSC 2019 can be found at: https://semanticcomputing.wixsite.com/icsc-2019
Students in sections of Dr. Pulimood’s CSC 415: Software Engineering class have collaborated with Mercer Street Friends, a community food bank based in Trenton, to upgrade their information systems as part of a semester-long software engineering project.
Sharif Mohammad Shahnewaz Ferdous (Assistant Professor of Computer Science) is a computer scientist specializing in virtual reality, augmented reality, and game development. He received his bachelor’s degree from Bangladesh University of Engineering and Technology in Computer Science and Engineering and his Ph.D. in Computer Science from the University of Texas at San Antonio. His research interests focus on using virtual reality and gaming to help improve quality of life for people with special needs. In particular, his dissertation focused on improving postural stability in virtual and augmented reality for people with balance impairments. He is experienced in interdisciplinary research activities and collaborates with kinesiologists, health care professionals, and first responders. He has published in peer-reviewed conferences, served as a program committee member in international workshops, and applied for a U.S. patent based on his work.
John DeGood (Visiting Assistant Professor of Computer Science) is a computer scientist specializing in real-time embedded systems and computer security. He received his Bachelor of Science in Chemistry followed by graduate study in Electrical Engineering at the Missouri University of Science of Technology. He spent the next 19 years in R&D (research and development) at Hewlett-Packard (now Agilent) helping develop three generations of gas chromatography products. He proposed and led the development of Agilent’s first PC-based chromatography data acquisition and analysis product line. While at Agilent, John earned a Master of Science in Computer and Information Sciences at the University of Delaware. He then spent eight years at Sarnoff Corporation (now SRI International) in a broad range of research including software defined radio, ad hoc networking, and high-performance computing. He then joined the Lockheed Martin Advanced Technology Laboratories where he performed government-funded computer security research for 15 years. John was an adjunct professor of Computer Science at TCNJ in the 2017-2018 academic year.