Vijayalakshmi "Viji" Ramasamy, Ph.D.

Vijayalakshmi Ramasamy


  • Data Analytics and Visualization
  • Pattern Recognition and Big Data Applications
  • Machine Learning and NLP
  • Learning Engagement Strategies in CS Education
  • Computational Neuroscience
Dr. Vijayalakshmi Ramasamy is an accomplished academic and researcher with over 27 years of experience. She is the Chair, Associate Professor, and Director of the MSCIS Program of Computer Science at the University of Wisconsin Parkside in Kenosha, Wisconsin, USA. Before joining UW-Parkside, she worked as a Visiting Assistant Professor at Miami University in Ohio and an Associate Professor at PSG College of Technology, Anna University in India. Dr. Ramasamy's research interests span graph data analytics, incorporating areas such as Data Mining, Machine Learning, Pattern Recognition, and Graph Theory. Her research has diverse applications, including computational neuroscience, computer networks, social networks, and undergraduate STEM Education. With over 60 peer-reviewed articles published, she has made significant contributions to the field. Dr. Ramasamy has been recognized for her teaching excellence through various grants, reflecting her commitment to innovative teaching methods. Currently, Dr. Ramasamy collaborates on an NSF research grant (2023-27)( with Florida International University, highlighting her commitment to computing research.

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
Advancing Undergraduate Research

Selected Publications

: Fostering Student Engagement and Success in STEM Education: An AI-Driven Exploration of High Impact Practices from Cross-Disciplinary General Education, Journal of Engineering Education Transformations (JEET)

: Automated Clustering of User Stories to Support Fault Fixation During Requirement Engineering: An Empirical Study, Software Quality Journal, Springer

: Car Accidents Severity Prediction in the USA Using Machine Learning Techniques,

: Literature Review of Assessment of High Impact Practices in General Education Courses Using Text Mining and Natural Language Processing,

: Machine learning approach for optimizing healthcare Supply chain,

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

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

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 795 - Research Methods in CIS
CIS 798 - CIS Seminar
CIS 799 - Independent Study:
CSCI 231 - Discrete Mathematics
CSCI 242 - Computer Science II
CSCI 340 - Data Structures/Algorithm Dsgn
CSCI 412 - Data Mining & Machine Learning
MATH 231 - Discrete Mathematics
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