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Dr. M. Thilaga

Assistant Professor (Sl. Gd.), Department of Mathematics, School of Physical Sciences, Coimbatore

Qualification: BSc, MPhil, MSc, Ph.D
m_thilaga@cb.amrita.edu
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Research Interest: Computational Neuroscience, Cyber Security Analytics,Graph Data Analytics, Deep Learning, Reinforcement Learning, Data Mining, Machine Learning, Intrusion Detection

Bio Publications Experience  Research Activities Lectures Awards
Bio

Dr. M. Thilaga serves as Assistant Professor (Selection Grade) in the Department of Mathematics, Amrita School of Physical Sciences, Coimbatore. She has received her PhD degree from Anna University , Chennai, M . P hil . and MSc degree s in Computer Science from B harathidasan and Periyar Universit ies respectively. Prior to joining Amrita, she worked in the Department of Applied Mathematics and Computational Sciences at PSG College of Technology for 16 years. S he was the co-investigator of the sponsored research project Cognitive modelling and Analysis funded by Cognitive Neuroengineering Laboratory (CNEL), University of South Australia , Adelaide , Australia . She has published research articles in various peer-reviewed national and international journals. She is a recognized PhD supervisor of Anna University. She is also a reviewer of various journals such as IEEE, Springer, and Elsevier.

Education

  • 2019 Ph.D. Computer Applications, Anna University, India
    Thesis Title :  Computational Techniques for Functional Brain Network Analysis
  • 2006 M.Phil. Master of Philosophy in Computer Science, Bharathidasan University, India
  • 2003 M.Sc.  Master of Science in Computer Science, Periyar University, India
  • 2001 B.Sc. Bachelor of Science in Computer Science, Periyar University, India
Publications

Journal Article

Year : 2024

Comparison of data-driven thresholding methods using directed functional brain networks

Cite this Research Publication : Manickam T, Ramasamy V, Doraisamy N. Comparison of data-driven thresholding methods using directed functional brain networks. Rev Neurosci. 2024 Aug 30. doi: 10.1515/revneuro-2024-0020. Epub ahead of print. PMID: 39217451.

Publisher : De Gruyter

Year : 2018

Shortest Path-Based Network Analysis to Characterize Different Cognitive Load States of Human Brain using EEG based Functional Brain Networks

Cite this Research Publication : Thilaga M, Ramasamy V, Nadarajan R, Nandagopal D. Shortest path based network analysis to characterize cognitive load states of human brain using EEG based functional brain networks. J Integr Neurosci. 2018;17(2):133-148. doi: 10.31083/JIN-170049. PMID: 28968248.

Publisher : IMR Press

Year : 2016

Novel Pattern Mining Approach for Identifying Cognitive Activity in EEG based Functional Brain Networks

Cite this Research Publication : Thilaga M, Vijayalakshmi R, Nadarajan R, Nandagopal D. A novel pattern mining approach for identifying cognitive activity in EEG based functional brain networks. J Integr Neurosci. 2016 Jun;15(2):223-45. doi: 10.1142/S0219635216500151. Epub 2016 Jul 11. PMID: 27401999.

Publisher : World Scientific 

Year : 2015

A heuristic branch-and-bound based thresholding algorithm for unveiling cognitive activity from EEG data

Cite this Research Publication : M. Thilaga, R. Vijayalakshmi, R. Nadarajan, D. Nandagopal, B. Cocks, C. Archana, N. Dahal, "A heuristic branch-and-bound based thresholding algorithm for unveiling cognitive activity from EEG data", Neurocomputing, Vol. 170, 2015, 32-46, ISSN 0925-2312, https://doi.org/10.1016/j.neucom.2015.03.095.

Publisher : Elsevier

Year : 2015

Minimum connected component – A novel approach to detection of cognitive load induced changes in functional brain networks

Cite this Research Publication : R. Vijayalakshmi, D. Nandagopal, N. Dasari, B. Cocks, N. Dahal, M. Thilaga, Minimum connected component – A novel approach to detection of cognitive load induced changes in functional brain networks, Neurocomputing, Vol. 170, 2015, 15-31, ISSN 0925-2312, https://doi.org/10.1016/j.neucom.2015.03.092.

Publisher : Elsevier

Year : 2015

Computational Neuroengineering Approaches to Characterizing Cognitive Activity in EEG Data

Cite this Research Publication : Nandagopal, D., Vijayalakshmi, R., Cocks, B., Dahal, N., Dasari, N., Thilaga, M. (2015). Computational Neuroengineering Approaches to Characterise Cognitive Activity in EEG Data. In: Tweedale, J., Jain, L., Watada, J., Howlett, R. (eds) Knowledge-Based Information Systems in Practice. Smart Innovation, Systems and Technologies, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-319-13545-8_8

Publisher : Springer

Year : 2014

Change Detection & Visualization of Functional Brain Networks using EEG Data

Cite this Research Publication : Ramasamy, V., Dasari, N., Nandagopal D., Subhiksha, R., Cocks, B., Dahal, N., Thilaga, M. Change Detection & Visualization of Functional Brain Networks using EEG Data. Elsevier Journal of Procedia - Computer Science, Vol. 29, pp. 672–682.

Publisher : Elsevier

Year : 2014

Brain strain: how much is too much?

Cite this Research Publication : Cocks, B., Nandagopal, D., Ramasamy, V., Thilaga M, Dasari N, Dahal N. Brain Strain: How much is too much? Journal of Educational Sciences & Psychology, Vol. IV (LXVI), pp. 94- 106.

Publisher : American Psychological Association

Year : 2011

FPGraphMiner – A Fast Frequent Pattern Mining Algorithm for Network Graphs

Cite this Research Publication : Ramasamy, V., Nadarajan, R., Thilaga, M., Nirmala, P. FPGraphMiner - A Fast Frequent Pattern Mining Algorithm for Network Graphs, Journal of Graph Algorithms and Applications, (JGAA), 2011, Vol. 15(6), pp. 753 - 76.

Publisher : Brown University

Year : 2011

A Divisive Clustering Algorithm for Performance Monitoring of Large Networks using Maximum Common Subgraphs

Cite this Research Publication : Ramasamy, Vijayalakshmi & Nadarajan, R. & Parisutham, Nirmala & Thilaga, M.. (2011). A Divisive Clustering Algorithm for Performance Monitoring of Large Networks using Maximum Common Subgraphs. International Journal of Artificial Intelligence. 7.

Publisher : Centre for Environment & Socio-Economic Research Publications

Year : 2011

Performance monitoring of large communication networks using maximum common subgraphs

Cite this Research Publication : Ramasamy, Vijayalakshmi & Nadarajan, R. & Parisutham, Nirmala & Thilaga, M.. (2011). Performance monitoring of large communication networks using maximum common subgraphs. International Journal of Artificial Intelligence. 6. 72-86.

Year : 2010

A Novel Approach for Detection and Elimination of Automorphic Graphs in Graph Databases

Cite this Research Publication : Ramasamy, V., Nadarajan, R., Thilaga, M., Nirmala, P. “A Novel Approach for Detection and Elimination of Automorphic Graphs in Graph Databases,” International Journal of Open Problems in Computer Science and Mathematics, Vol. 3(1), pp. 56-72.

Publisher : The European Digital Mathematics Library

Conference Paper

Year : 2024

Quantification of Human Intelligence Using Principal Component Analysis

Cite this Research Publication : Vel Vignesh, M., Boolog, V., Bagyalakshmi, M., Thilaga, M. (2024). Quantification of Human Intelligence Using Principal Component Analysis. In: Sharma, H., Shrivastava, V., Tripathi, A.K., Wang, L. (eds) Communication and Intelligent Systems. ICCIS 2023. Lecture Notes in Networks and Systems, vol 967. Springer, Singapore. https://doi.org/10.1007/978-981-97-2053-8_17.

Publisher : Springer

Conference Proceedings

Year : 2013

Breaking the Camel’s Back: Can Cognitive Overload Be Quantified in The Human Brain?

Cite this Research Publication : Cocks, B., Nandagopal, D., Ramasamy, V., Thilaga, M., Dasari, M., Dahal, N. Breaking the Camel’s Back: Can Cognitive Overload Be Quantified in The Human Brain? Procedia - Social and Behavioral Sciences, Vol. 97(6) pp. 21-29.

Publisher : Elsevier

Year : 2013

Computational Techniques for Characterizing Cognition using EEG – New Approaches

Cite this Research Publication : Nandagopal, D., Ramasamy, V., Cocks, B., Dahal, N., Dasari, N., Thilaga, M. Computational Techniques for Characterizing Cognition using EEG - New Approaches, Elsevier Journal of Procedia Computer Science, Vol.22, pp. 699–708. https://doi.org/10.1016/j.procs.2013.09.151.

Publisher : Elsevier

Book Chapter

Year : 2018

Impact of Negative Correlations in Characterizing Cognitive Load States Using EEG Based Functional Brain Networks

Cite this Research Publication : Thilaga, M., Ramasamy, V., Nadarajan, R., Nandagopal, D. Impact of Negative Correlations in Characterizing Cognitive Load States Using EEG Based Functional Brain Networks. Computational Intelligence, Cyber Security and Computational Models. Models and Techniques for Intelligent Systems and Automation, Springer, pp. 74-86, 2018.

Publisher : Springer

Year : 2015

Characterisation of Cognitive Activity Using Minimum Connected Component

Cite this Research Publication : Vijayalakshmi, R., Nandagopal, D., Thilaga, M., Cocks, B. (2015). Characterisation of Cognitive Activity Using Minimum Connected Component. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. Lecture Notes in Computer Science, vol 9492. Springer, Cham. https://doi.org/10.1007/978-3-319-26561-2_63.

Publisher : Springer

Year : 2015

Computational Neuroengineering Approaches to Characterise Cognitive Activity in EEG Data

Cite this Research Publication : Nandagopal, D., Vijayalakshmi, R., Cocks, B., Dahal, N., Dasari, N., Thilaga, M. (2015). Computational Neuroengineering Approaches to Characterise Cognitive Activity in EEG Data. In: Tweedale, J., Jain, L., Watada, J., Howlett, R. (eds) Knowledge-Based Information Systems in Practice. Smart Innovation, Systems and Technologies, vol 30. Springer, Cham. https://doi.org/10.1007/978-3-319-13545-8_8.

Poster

Year : 2017

Challenges in Identifying Cognitive Activity using EEG based Functional Brain Networks

Cite this Research Publication : Thilaga M, Ramasamy, V., Nadarajan, R., Nandagopal, D. Challenges in Identifying Cognitive Activity using EEG based Functional Brain Networks. 2nd CCBR workshop on Computational Brain Research, Indian Institute of Technology-IITM, Chennai, India, 2017.

Experience 

Teaching Experience

  • PSG College of Technology, Coimbatore – June 2008 – July 2024
  • Associate Professor, Department of Applied Mathematics and Computational Sciences (Aug 2022 –June 2024)
  • Assistant Professor (Selection Grade), Department of Applied Mathematics and Computational Sciences (July 2016 – July 2022)
  • Assistant Professor (Senior Grade), Department of Applied Mathematics and Computational Sciences (Jan 2014 – June 2016)
  • Assistant Professor, Department of Mathematics and Computer Applications (Sep 2010 – Dec 2013)
  • Lecturer, Department of mathematics and Computer Applications (June 2008-Aug 2010)
  • KGiSL Institute of Information Management, Coimbatore
  • Lecturer, Department of Computer Applications (June 2007 –May 2008)
  • Dr. SNS Rajalakshmi College of Arts and Science, Coimbatore
  • Lecturer, Department of Computer Science (June 2005 –May 2007)
  • Muthayammal Engineering College, Rasipuram
  • Lecturer, Department of Computer Science and Engineering (May 2003 –May 2005)
Research

Research Positions Held

  • Co-researcher – Cognitive Neuro-Engineering Laboratory (CNEL), University of South Australia (UNISA), 2013–2016
  • Co-Investigator – Computational Neuroscience Laboratory, PSG College of Technology, 2012 – 2019

Research Sponsors / Funding

  • University of South Australia (UniSA), Adelaide, Australia.
    Defence Science and Technology Organisation (DSTO) – UniSA – 2011/1167673/1 
    Grant : AUD-20K
    Year :2012-2018
    Title : Cognitive modeling and analysis
    Collaborative grant at Cognitive Neuroengineering Lab (CNeL) led by Prof. Nandagopal D, Dean International, and Chair Defence Systems, UniSA.

Software Products Developed 

  • Functional Brain Network Analysis Tool – The tool automates the processes in analyzing multi-channel EEG data. It includes loading the EEG dataset in .mat file format, viewing it using EEGLAB, and computing linear and non- linear metrics.
  • FBN Visualization & Investigation Tool for EEG data -The pre-processed Electroencephalograph (EEG) data serves as input to compute statistical measures and construct graph databases. Software Tools Used: MATLAB, EEGLAB
Activities

Synergetic Activities

  • Local Coordinator – ACM summer school on “Algorithmic Approaches to NP- Completeness”, to be held at PSG College of Technology during the third and fourth week of July, 2024.
  • Track Chair – International Conference on Computational Models, Cyber Security & Computational Intelligence (ICC3, 2023, December 2023), PSG College of Technology, Coimbatore.
  • Session Chair – International Conference on Computational Models, Cyber Security & Computational Intelligence (ICC3, 2023, December 2023), PSG College of Technology, Coimbatore.
  • Session Chair – IEEE International Conference on Intelligent Systems for Communication, IOT and Security, ICISCoIS 2023 organized by the Department of Information Technology, PSG College of Technology, Coimbatore.
  • Jury Member – AthenaHacks (a 24-hour Hackathon) held on 24th and 25th November, 2023 at PSG College of Technology, Coimbatore.
  • Session Chair – Research Conclave 2022 organized by PSG College of Technology, Coimbatore.
Lectures

Keynotes/ Special Lectures

  • AICTE-ATAL Faculty Development Programme on ‘IOT for Precision Agriculture and Transportation’ Jan 2023.
  • AICTE-ATAL Faculty Development Programme on ‘Foundations of Data Science and Machine Learning for Cross domain applications’, Dec 2021.
  • Graph Analysis of Functional Brain Networks: Practical Issues in Translational Neuroscience’, Department of AMCS, PSG College of Technology, July 2019.
  • Computational Techniques for functional brain network analysis’ – National Seminar on Computational Biomedical Engineering (NCBE-2018), SSN College of Engineering, Kalavakkam, Chennai, 26-27 Sep 2018.
  • Training program on ‘Introduction to Computer Programming‘- Department of Production Engineering, PSG College of Technology, Coimbatore, May 2018.
  • Computational Techniques for Functional Brain Network Analysis’, Department of AMCS, PSG College of Technology, Sep 2018.
  • Impact of Negative Correlations in Characterizing Cognitive Load States using EEG Based Functional Brain Networks, Department of AMCS, PSG College of Technology’, July 2017.
  • Social Network Analysis and Graph Mining – Overview’, Department of AMCS, PSG College of Technology, June 2016
  • Challenges in Identifying Cognitive Activity using EEG based Functional Brain Networks’, Department of AMCS, PSG College of Technology, Dec 2016.
Awards

Awards and Honors

  • Best Paper Award, 9th International Conference on Cognitive Science, Malaysia, 2013.
  • Recognized Ph.D. Supervisor at Anna University, Chennai (Reference No: 4070001).
  • Qualified (TNSET 2017) – Tamilnadu State Level Eligibility Test Conducted by Mother Teresa Women’s University, Kodaikanal, 2017
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