Vijayalakshmi "Viji" Ramasamy, Ph.D.

Vijayalakshmi Ramasamy

AREAS OF EXPERTISE

  • Data Analytics and Visualization
  • Pattern Recognition and Big Data Applications
  • Machine Learning and NLP
  • Learning Engagement Strategies in CS Education
  • Computational Neuroscience
Vijayalakshmi Ramasamy is an Associate Professor of Computer Science at the University of Wisconsin Parkside, Kenosha, Wisconsin, USA. She brings to bear an extensive academic and research experience of over 25 years. Before joining UW-Parkside, she was a Visiting Assistant Professor at Miami University, Oxford, Ohio, and an Associate Professor at PSG College of Technology, Anna University, India. She also held an adjunct position at the University of South Australia (UniSA), received a research grant from Cognitive NeuroEngineering Lab at UniSA, established a Computational Neuroscience Laboratory at Anna University, India, and worked on an NSF research grant in collaboration with Florida International University. She has taught multiple courses in Data Science, Computer Science, and Software Engineering and has supervised several MS and Ph.D. research scholars. Her research interests include graph data analytics as a multidisciplinary domain comprising work from various fields such as Data Mining, Machine Learning, Pattern Recognition, and Graph Theory applied to different disciplines, including computational neuroscience, computer, biological, social networks, and, most recently, undergraduate STEM Education (educational data mining and learning analytics). She has published over 54 peer-reviewed articles, at top-tier venues in Computer Science, including IEEE, ACM SIGCSE, Neurocomputing, and Journal of Neural Engineering. She has received many teaching grants, including the eLearning Teaching Research Grant for Innovative Learning Space and Center for Teaching Excellence Major Teaching Research Project at Miami University, Ohio, USA.

Teaching Interests

Data Mining and Machine Learning, Deep Learning, Applied Data Analytics for Data Science, Data Structures and Algorithm Design, Database Management Systems, Software Engineering (Agile and Waterfall), Fundamentals of Programming & Problem-Solving

Research Interests

Graph data analytics as a multidisciplinary domain comprising work from various fields such as Data Mining, Machine Learning, Pattern Recognition, and Graph Theory applied to different disciplines, including computational neuroscience, computer, biological, social networks, and, most recently, undergraduate STEM Education (educational data mining and learning analytics).

Consulting Interests

Empowering Women in Computing

Selected Publications

2021: Application of Back-translation – A Transfer Learning Approach to Identify Ambiguous Software Requirements, ACM Southeast (ACMSE) conference, 2021 (130-137 pp.)

2021: Characterizing EEG electrodes in directed functional brain networks using normalized transfer entropy and page rank, Springer Verlag Germany

2021: Directed Functional Brain Networks Characterization of Information Flow Direction during Cognitive Function Using Non-Linear Granger Causality, CRC Press (21 pp.)

2021: Evaluation of Student Collaboration on Canvas LMS Using Educational Data Mining Techniques, ACM Southeast (ACMSE) conference, 2021 (55-62 pp.)

2021: Characterizing EEG electrodes in directed functional brain networks using normalized transfer entropy and page rank, Springer Nature Switzerland AG (27-49 pp.)

2021: Classification of Testable and Valuable User Stories by using Supervised Machine Learning Classifiers, IEEE Computer Society (130–137 pp.)

2021: Meta-analysis to Study the Impact of Learning Engagement Strategies in Introductory Computer Programming Courses: A Multi-institutional Study, The ACM Southeast (ACMSE) conference, 2021 (40–46 pp.)

2020: A User Interface (UI) and User eXperience (UX) evaluation framework for cyberlearning environments in computer science and software engineering education, Heliyon (e03917 pp.)

2020: A Study on Student Performance Evaluation using Discussion Board Networks, (500--506 pp.)

2019: Analyzing Link Dynamics in Student Collaboration Networks using Canvas-A Student-Centered Learning Perspective, IEEE Conference on Frontiers in Education, FIE-2019

2019: Evaluating the Impact of Combination of Engagement Strategies in SEP-CyLE on Improve Student Learning of Programming Concepts, (1130--1135 pp.)

2018: Impact of Negative Correlations in Characterizing Cognitive Load States Using EEG Based Functional Brain Networks, Springer (74-86 pp.)

2018: Tp-graphminer: a clustering framework for task-based information networks, IEEE International Conference on System, Computation, Automation and Networking (ICSCA) (1--7 pp.)

2018: A minimally disruptive approach of integrating testing into computer programming courses, 2018 IEEE/ACM International Workshop on Software Engineering Education for Millennials (SEEM) (1--7 pp.)

2018: Shortest path based network analysis to characterize cognitive load states of human brain using EEG based functional brain networks, Journal of integrative neuroscience (253--275 pp.)

2017: Capturing cognition via eeg-based functional brain networks, Springer, Singapore (147--172 pp.)

2011: A divisive clustering algorithm for performance monitoring of large networks using maximum common subgraphs, Int J Artif Intell (92--109 pp.)

2011: FP-GraphMiner-A Fast Frequent Pattern Mining Algorithm for Network Graphs., J. Graph Algorithms Appl. (753--776 pp.)

Departmental Service

: Committee Member - Faculty Search Committee
: Committee Member - Faculty Search Committee

College Service

: Committee Member - Information Technology Practice Center (ITPC)

University Service

: Committee Member - General Education (Gen Ed) Committee
: Committee Member - Institutional Review Boards (IRB) committee
CIS 540 - Data Structures/Algorithm Dsgn
CIS 612 - Data Mining & Machine Learning
CIS 614 - Deep Learning
CIS 690 - Special Topics in CIS:
CIS 710 - Data Science-Cmptr Info Systms
CIS 793 - Internship
CIS 798 - CIS Seminar
CIS 799 - INDEPENDENT STUDY:
CSCI 231 - Discrete Mathematics
CSCI 242 - Computer Science II
CSCI 274 - UNIX CONCEPTS AND TOOLS
CSCI 275 - UNIX SCRIPTING
CSCI 340 - Data Structures/Algorithm Dsgn
CSCI 412 - Data Mining & Machine Learning
CSCI 435 - UNIX SYSTEM ADMINISTRATION
MATH 231 - Discrete Mathematics
Scroll to top