| FP-GraphMiner-A Fast Frequent Pattern Mining Algorithm for Network Graphs. R Vijayalakshmi, N Rethnasamy, JF Roddick, M Thilaga, P Nirmala J. Graph Algorithms Appl. 15 (6), 753-776, 2011 | 36 | 2011 |
| Minimum connected component–a novel approach to detection of cognitive load induced changes in functional brain networks R Vijayalakshmi, D Nandagopal, N Dasari, B Cocks, N Dahal, M Thilaga Neurocomputing 170, 15-31, 2015 | 32 | 2015 |
| Breaking the Camel's Back: Can Cognitive Overload be Quantified in the Human Brain? C Bernadine, N Nanda, R Vijayalakshmi, M Thilaga, D Naga, D Nabaraj Procedia-Social and Behavioral Sciences 97, 21-29, 2013 | 16 | 2013 |
| Computational techniques for characterizing cognition using EEG data–new approaches ND Nandagopal, R Vijayalakshmi, B Cocks, N Dahal, N Dasari, M Thilaga, ... Procedia Computer Science 22, 699-708, 2013 | 15 | 2013 |
| Shortest path based network analysis to characterize cognitive load states of human brain using EEG based functional brain networks M Thilaga, V Ramasamy, R Nadarajan, D Nandagopal Journal of integrative neuroscience 17 (2), 253-275, 2018 | 11 | 2018 |
| Change detection and visualization of functional brain networks using EEG data R Vijayalakshmi, N Dasari, D Nandagopal, R Subhiksha, B Cocks, ... Procedia Computer Science 29, 672-682, 2014 | 11 | 2014 |
| A novel approach for detection and elimination of automorphic graphs in graph databases R Vijayalakshmi, R Nadarajan, P Nirmala, M Thilaga Int. J. Open Problems Compt. Math 3 (1), 2010 | 9 | 2010 |
| A novel pattern mining approach for identifying cognitive activity in EEG based functional brain networks M Thilaga, R Vijayalakshmi, R Nadarajan, D Nandagopal Journal of integrative neuroscience 15 (02), 223-245, 2016 | 8 | 2016 |
| A heuristic branch-and-bound based thresholding algorithm for unveiling cognitive activity from EEG data M Thilaga, R Vijayalakshmi, R Nadarajan, D Nandagopal, B Cocks, ... Neurocomputing 170, 32-46, 2015 | 8 | 2015 |
| Performance monitoring of large communication networks using maximum common subgraphs R Vijayalakshmi, R Nadarajan, P Nirmala, M Thilaga International Journal of Artificial Intelligence 6 (S11), 72-86, 2011 | 6 | 2011 |
| Computational neuroengineering approaches to characterise cognitive activity in EEG data D Nandagopal, R Vijayalakshmi, B Cocks, N Dahal, N Dasari, M Thilaga Knowledge-Based Information Systems in Practice, 115-137, 2015 | 5 | 2015 |
| Characterisation of cognitive activity using minimum connected component R Vijayalakshmi, D Nandagopal, M Thilaga, B Cocks Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015 | 2 | 2015 |
| A divisive clustering algorithm for performance monitoring of large networks using maximum common subgraphs R Vijayalakshmi, R Nadarajan, P Nirmala, M Thilaga Int J Artif Intell 7 (A11), 92-109, 2011 | 2 | 2011 |
| Impact of Negative Correlations in Characterizing Cognitive Load States Using EEG Based Functional Brain Networks M Thilaga, R Vijayalakshmi, R Nadarajan, D Nandagopal Computational Intelligence, Cyber Security and Computational Models. Models …, 2018 | | 2018 |
| Challenges in identifying cognitive activity using EEG based functional brain networks M Thilaga, R Vijayalakshmi, R Nadarajan, D Nandagopal Second Annual workshop on Computational Brain Research, IITMadras, 17-20, 2017 | | 2017 |
| “Brain Strain: How much is too much?” M Cocks, B, Nandagopal, D, Vijayalakshmi, R, Dasari, N, Dahal, N, Thilaga Journal of Educational Sciences and Psycology 4 (LXVI), 2014 | | 2014 |
Vijayalakshmi Ramasamy 0000-0001-...Chair & Associate Professor, Academic Director MSCIS Program, University of Wisconsin-ParksideVerified email at uwp.edu
