Asia School of Business

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David Asirvatham

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Professor of Practice, AI & Technology,
Head of Information Technology

Area of Expertise:

AI & Technology

Professor Ts. Dr. David Asirvatham is Professor of Practice, AI & Technology and Head, Information Technology at the Asia School of Business (ASB), which was established in collaboration with MIT Sloan. He has been in the academic leadership and CIO roles for 30 years. His areas of expertise include Digital Neural Network, E-Learning Technologies, ICT Project Management, Multimedia Content Creation and AI.

Prior to joining ASB, he was the Executive Dean for the Faculty of Innovation and Technology at Taylor’s University, Director of the Centre of Information Technology at the University of Malaya, and CIO/Senior Director of the Centre for Information Technology at Multimedia University.

He has held numerous posts, including Associate Dean for Faculty of Information Technology (Multimedia University), Project Manager for the Multimedia and IT Infrastructure Development for a university campus (US$14 million project), and SAP Advisory for High Education Council (Germany).

He was the Chairman of the ICT Human Capital Development for 11th Malaysia Plan 2016-2020, Secretary for the Artificial Intelligence Society Malaysia, President of the Data Science Association (Malaysia) 2022-2025, Country Representative for the Asia E-learning Network (Japan), Steering Committee Member for the Implementation of E-Learning for Malaysian Public Sector, and Member of the Malaysian Grid for Learning’s Standards Expert Group 2003-2004.

He also worked on various ICT Projects and conducted workshops in South Africa, Sudan, Iran, Ghana, Kenya, Vietnam, Maldives, Bangladesh (World Bank Project), UAE, India, and Brunei. David completed his Ph.D. from Multimedia University, M.Sc. (Digital System) from Brunel University (U.K.), and B.Sc. (Hons) Ed., and Post-Graduate Diploma in Computer Science from the University of Malaya. He has published over 70 academic papers and graduated 10 PhD students.

  • Lee, C.H., Mohamad, A.H., and Asirvatham, D. (2026) Data-Driven Football Performance Measurement: A Measure-First Systematic Review of Action-Centric, Individual, Team, and Financial Analytics (2018–2024). Preprints.
  • Masood, J.A.I.S., John, A., Chakravarthy, N.S.K., Asirvatham, D., Murugesan, R.K., et al. (2026) Churn Prediction in the Telecom Sector Using Deep Learning Techniques. Embracing the Digital Horizon: Pioneering Commerce and Management Strategies …
  • Kumar, E.S., BujjiBabu, D., Ibrhaim, S.J.A., Asirvatham, D., Chakravarthy, N.S.K., et al. (2026) Artificial Intelligence Driven Detection and Classification of Brain Tumors: Advancement and Challenges. Demystifying Emerging Trends in the Digital Horizon, 130-143.
  • Palivela, H., Narvekar, M., Asirvatham, D., Bhushan, S., Rishiwal, V., and Agarwal, U. (2025) Code-switching ASR for low-resource Indic languages: A Hindi-Marathi case study. IEEE Access 13, 9171-9198.
  • Das, S.R., Jhanjhi, N.Z., Asirvatham, D., Rizwan, F., and Javed, D. (2025) Securing AI-based healthcare systems using blockchain technology. AI techniques for securing medical and business practices, 333-356.
  • Abdulkareem Shafiq, D., Marjani, M., Ahamed Ariyaluran Habeeb, R., et al. (2025) Digital footprints of academic success: An empirical analysis of Moodle logs and traditional factors for student performance. Education Sciences 15 (3), 304.
  • Das, S.R., Zaman, D.N., Asirvatham, D., Ashfaq, F., Masud, M., and Shorfuzzaman, M. (2025) Empirical performance analysis of hyperledger fabric. Available at SSRN 5127328.
  • Nidamanuri, S., MASOOD, J.A.I., Asirvatham, D., BIN_ABAS, F., VEERAPPAN, K., et al. (2025) Predictive deep learning models to identify traumatic brain injuries using MRI data. Journal of engineering science technology 2.
  • Sharma, A., Marzani, M., Gani, A., Asirvatham, D., Gusaiwal, B., and Kishan, S. (2025) An Evaluation on Features Selection Using Various Methods for Travel Behavior Model Development. International Conference on Innovations in Data Science, 249-257.
  • Sakib, M.K.H., Islam, M.R., Prome, S.A., Jahan, S., Asirvatham, D., Ragavan, N.A., et al. (2025) MVis4SID: Multimodal Visual Interactive System for Suicide Ideation Detection. Companion Proceedings of the ACM on Web Conference 2025, 2024-2033.
  • Sakib, M.K.H., Ragavan, N.A., Prome, S.A., Islam, M.R., Wei, G.W., Asirvatham, D., et al. (2025) A review on multimodal approaches for deception detection: State-of-the-art, challenges, and future directions.
  • V. Sharma, D. Srivastava, S. Pant, M. Kumar and D. Asirvatham, “A Framework for Predicting Diabetic Retinopathy Using Deep Learning and Image Augmentation,” 2025 5th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), Dehradun, India, 2025, pp. 1-5.
  • Prome, S.A., Ragavan, N.A., Islam, M.R., Asirvatham, D., and Jegathesan, A.J. (2024) Deception detection using machine learning (ML) and deep learning (DL) techniques: A systematic review. Natural Language Processing Journal 6, 100057.
  • Masood, J.A.I.S., Chakravarthy, N.S.K., Asirvatham, D., Marjani, M., Shafiq, D.A., et al. (2024) A hybrid deep learning model to predict high-risk students in virtual learning environments. IEEE Access 12, 103687-103703.
  • Sivalingam, P., Asirvatham, D., Marjani, M., Masood, J.A.I.S., Chakravarthy, N.S.K., et al. (2024) A review of travel behavioural pattern using GPS dataset: A systematic literature review. Measurement: Sensors 32, 101031.
  • Gandhi, M., Mulay, C., Durai, K., Murali, G., Masood, J.A.I.S., Vijayarajan, V., et al. (2024) Quantum blockchain: Trends, technologies, and future directions. IET Quantum Communication 5 (4), 516-542.
  • Hossain Sakib, M.K., Islam, M.R., Akter Prome, S., Nguyen, T.T.L., Asirvatham, D., et al. (2024) MVis4LD: Multimodal Visual Interactive System for Lie Detection. Asian Conference on Intelligent Information and Database Systems, 28-43.
  • Prome, S.A., Islam, M.R., Sakib, M.K.H., Asirvatham, D., Ragavan, N.A., Sanin, C., et al. (2024) Ldnet: A robust hybrid approach for lie detection using deep learning techniques. Computers, Materials and Continua 81 (2), 2845-2871.
  • Asirvatham, D., Gonzalez-Longatt, F., Falkowski-Gilski, P., & Kanthavel, R. (Eds.). (2024). Evolutionary artificial intelligence : proceedings of ICEAI 2023. Springer.
  • Das, S.R., Jhanjhi, N.Z., Asirvatham, D., Ashfaq, F., Javed, D., and Gururaj, H.L. (2024) Blockchain-driven splitfed learning for data protection in iot setting.
  • Tandon, R., Verma, A., Kaur, M., Wadhwa, H., and Asirvatham, D. (2024) Management of metropolitan mobility for public transport and smart vehicles with fog computing. Cloud and Fog Optimization-based Solutions for Sustainable Developments, 48-76.
  • Renjie, L., Wei, G.W., Asirvatham, D., and Khan, N.A. (2024) Study of the Impact of Smoking and Alcohol Consumption on the Physical Health of South Korean Residents and Development of Machine Learning Predictive Models. 2024 IEEE 9th International Conference on Engineering Technologies and …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2024) Enhancing Student Performance LMS Data with Feature Engineering for Improved Cluster Quality. 2024 International Conference on Informatics Engineering, Science …
  • Z. Wentong, H. Jazri, D. Asirvatham and S. Teoh, “Maximizing eSports (Apex Legends) Players Arena Performance With Big Data Modeling,” 2024 IEEE 9th International Conference on Engineering Technologies and Applied Sciences (ICETAS), Bahrain, Bahrain, 2024, pp. 1-5.
  • Ahmed Zafran Bin Ahmed Sharizan, Mohsen Marjani, Dalia Abdulkareem Shafiq and Komal Sharma (2024) Towards Enhanced Breast Cancer Prediction: A Comparative Evaluation Study
  • Akibu Mahmoud Abdullahi, Muhammad Hamza Usmani, Md Amin Ullah Sheikh and Sohini Chowdhury (2024) An Efficient AI Based Approach for Multimedia Traffic Management in Wireless Network
  • Paul Yong Ka Ming, Navid Ali Khan, David Asirvatham and Kavita (2024) Detecting Street Parking Occupancy Using Image Recognition with Yolo
  • Xiao Weiqi, Steve Teoh Chee Hooi, Siva Raja A L Sindiramuttyand Sahil Verma (2024) Surface Anomaly Detection Using Machine Learning Technique
  • Das, S.R., Jhanjhi, N.Z., Asirvatham, D., Ashfaq, F., and Abdulhussain, Z.N. (2023) Proposing a model to enhance the IoMT-based EHR storage system security. International Conference on Mathematical Modeling and Computational Science …
  • Alaros, E., Marjani, M., Shafiq, D.A., and Asirvatham, D. (2023) Predicting consumption intention of consumer relationship management users using deep learning techniques: A review. Indonesian Journal of Science and Technology 8 (2), 307-328.
  • Islam, M.R., Sakib, M.K.H., Prome, S.A., Wang, X., Ulhaq, A., Sanin, C., et al. (2023) Machine learning with explainability for suicide ideation detection from social media data. 2023 10th International Conference on Behavioural and Social Computing (BESC …
  • Li, J., Weiwei, G., NZ, J., and David, A. (2023) The smart medicine delivery using UAV for elderly center. International journal of computer science and network security: IJCSNS 23 (1 …
  • Prome, S.A., Islam, M.R., Asirvatham, D., Sakib, M.K.H., and Ragavan, N.A. (2023) Lievis: A visual interactive dashboard for lie detection using machine learning and deep learning techniques. 2023 26th International Conference on Computer and Information Technology …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2022) Student retention using educational data mining and predictive analytics: A systematic literature review. Ieee Access 10, 72480-72503.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2022) Influence maximization diffusion models based on engagement and activeness on instagram. Journal of King Saud University-Computer and Information Sciences 34 (6 …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2022) A Conceptual Predictive Analytics Model for the Identification of at-risk students in VLE using Machine Learning Techniques. 2022 14th International Conference on Mathematics, Actuarial Science …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2022) A narrative review of students’ performance factors for learning analytics models. International Joint Conference on Advances in Computational Intelligence …
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2021) Instagram post popularity trend analysis and prediction using hashtag, image assessment, and user history features. Int. Arab J. Inf. Technol. 18 (1), 85-94.
  • Sharma, A., Gani, A., Asirvatham, D., Ahmed, R., Hamzah, M., and Asli, M.F. (2021) Travel behavior modeling: taxonomy, challenges, and opportunities. Int. J. Adv. Comput. Sci. Appl 12, 774-786.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2021) Influence maximization algorithm: Review on current approaches and limitations. Engineering and Applied Science Research 48 (2), 221-229.
  • Fesabas, A.K.R., Asirvatham, D., and Poulain, J.P. (2021) Facial expression recognition in food studies.
  • Sivalingam, P., Asirvatham, D., and Chinna, K. (2021) A travel behaviour model to predict travel behaviour pattern of urban road user using rule-based approach. 2021 IEEE 7th International Conference on Computing, Engineering and Design …
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2020) Classification of instagram fake users using supervised machine learning algorithms. International Journal of Electrical and Computer Engineering 10 (3), 2763.
  • Perera, C.J., Zainuddin, Z., Piaw, C.Y., Cheah, K.S.L., and Asirvatham, D. (2020) The pedagogical frontiers of urban higher education: Blended learning and co-lecturing. Education and Urban Society 52 (9), 1305-1329.
  • Jayaraman, K., Leow, N.X.C., Asirvatham, D., and Chan, H.R. (2020) Conceptualization of an urban travel behavior model to mitigate air pollution for sustainable environmental development in Malaysia. Management of Environmental Quality: An International Journal 31 (3), 785-799.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2020) An analysis and prediction model of outsiders percentage as a new popularity metric on Instagram. ICT Express 6 (3), 243-248.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2020) Analysis and Prediction of Instagram Users Popularity using Regression Techniques based on Metadata, Media and Hashtags Analysis. Engineering Letters 28 (3), 812.
  • Brohi, S.N., Pillai, T.R., Kaur, S., Kaur, H., Sukumaran, S., and Asirvatham, D. (2019) Accuracy comparison of machine learning algorithms for predictive analytics in higher education. International Conference for Emerging Technologies in Computing, 254-261.
  • Edward, C.N., Asirvatham, D., and Johar, G. (2019) The impact of teaching Oriental music using blended learning approach: An experimental study. Malaysian Journal of Learning and Instruction 16 (1), 81-103.
  • Ayoobkhan, A.L.M., and Asirvatham, D. (2019) A study on the adoption of software as a service (SaaS) in online business SMEs in Sri Lanka. Asian Journal of Research in Computer Science 2 (2), 1-13.
  • Pathirana, S., and Asirvatham, D. (2019) Applicability of multi-agent systems for electroencephalographic data classification. Procedia Computer Science 152, 36-43.
  • Edward, C.N., Asirvatham, D., and Johar, M.G.M. (2018) Effect of blended learning and learners’ characteristics on students’ competence: An empirical evidence in learning oriental music. Education and Information Technologies 23 (6), 2587-2606.
  • Daud, M., Rasiah, R., George, M., Asirvatham, D., and Thangiah, G. (2018) Bridging the gap between organisational practices and cyber security compliance: can cooperation promote compliance in organisations? International Journal of Business & Society 19 (1), 161.
  • Brohi, S.N., Pillai, T.R., Asirvatham, D., Ludlow, D., and Bushell, J. (2018) Towards smart cities development: A study of public transport system and traffic-related air pollutants in Malaysia. IOP conference series: earth and environmental science 167 (1), 012015.
  • Pathirana, S., Asirvatham, D., and Johar, G. (2018) A critical evaluation on low-cost consumer-grade electroencephalographic devices. 2018 2nd International Conference on BioSignal Analysis, Processing and …
  • Vithana, V.N., Asirvatham, D., and Johar, M.G.M. (2018) An empirical study on using agile methods in global software development. 2018 18th International Conference on Advances in ICT for Emerging Regions …
  • Daud, M., Rasiah, R., George, M., Asirvatham, D., Rahman, A.F.A., and Ab Halim, A. (2018) Denial of service:(DoS) Impact on sensors. 2018 4th International Conference on Information Management (ICIM), 270-274.
  • Pathirana, S., Asirvatham, D., and Johar, M.G.M. (2018) An agent based approach for electroencephalographic data classification. 2018 13th International Conference on Computer Science & Education (ICCSE), 1-5.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2018) A study on the methods to identify and classify cyberbullying in social media. 2018 Fourth International Conference on Advances in Computing, Communication …
  • Pathirana, S., Asirvatham, D., and Johar, M.G.M. (2018) Designing Virtual Keyboards for Brain-Computer Interfaces. 2018 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 1-6.
  • Pathirana, S., Asirvatham, D., and Johar, M.G.M. (2018) A multi-agent system for improving electroencephalographic data classification accuracy. 2018 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 1-6.
  • XeChung, L.N., Krishnaswamy, J., and Asirvatham, D. (2018) Proposed urban travel behavior model to promote smart mobility. 2018 Fourth International Conference on Advances in Computing, Communication …
  • Abdullah, A., Ponnan, R., and Asirvatham, D. (2018) Improving multiclass classification in intrusion detection using clustered linear separator analytics. 2018 8th International Conference on Intelligent Systems, Modelling and …
  • Vithana, V., Asirvatham, D., and Johar, M. (2018) Challenges to Practice Agile Methods in Global Software Development-A Review of Literature. International Journal of Computer Applications 179 (40), 975-8887.
  • Asirvatham, D., Brohi, S.N., Xion, T.E., Theng, T.G., Fei, N.J., Kaur, S., Pillai, T.R., et al. (2018) Smart Mobility Cities: Connecting Bristol and Kuala Lumpur Project Report.
  • Kalith, I.M., Asirvatham, D., Khatibi, A., and Thelijjagoda, S. (2018) Comparison of Syllable and Phoneme Modelling of Agglutinative Tamil Isolated Words in Speech Recognition. Current Journal of Applied Science and Technology, 1-10.
  • Maheswaran, M., and Asirvatham, D. (2018) Real-Time Business Analytical Model Using Big Data Strategies for Telecommunication Industry. Information Systems Design and Intelligent Applications: Proceedings of …
  • Wei, C.Y., Fauzi, I.S.B.M., Thenmoley, R., Elhussein, E.S.E., and Asirvatham, D. (2018) Business and Economics Journal.
  • Chin Yung Wei, Intan Syahidah Bt Mohd Fauzi, Thenmoley Ramkumar and David Asirvatham (2018) E-commerce Adoption and Analysis of the Popular E-commerce Business Sites in Malaysia
  • Ayoobkhan, A.L.M., and Asirvatham, D. (2017) Adoption of cloud computing services in healthcare sectors: Special attention to private hospitals in Colombo District, Sri Lanka. British Journal of Applied Science & Technology.
  • Vithana, V.N., Asirvatham, D., and Johar, M.G.M. (2017) Investigating the issues of using agile methods in offshore software development in Sri Lanka. Asian Conference on Intelligent Information and Database Systems, 515-523.
  • Ayoobkhan, A.L.M., and Asirvatham, D. (2017) Issues and challenges faced by online business organizations in adopting cloud computing: A research agenda. International Journals of Advanced Research in Computer Science and Software …
  • Perera, C.J., Chua, Y.P., Asirvatham, D., Zainuddin, Z., Harris, A., and Jones, M. (2017) The enhancement of teaching and learning through blended learning and collaborative co-lecturing.
  • Ibralebbe Mohamed Kalith, David Asirvatham and Ismail Raisal, 2017. Context-dependent Syllable Modeling of Sentence-based Semi-continuous Speech Recognition for the Tamil Language. Information Technology Journal, 16: 125-133.
  • Kalith, I.M., Ashirvatham, D., and Thelijjagoda, S. (2016) Isolated to connected Tamil digit speech recognition system based on hidden Markov model. www. ijntse. com.
  • David Asirvatham (2014) Functional Discrimination of fMRI Data from Multiple Subjects
  • Ngoc Dung Dui, David Asirvatham, Md Gapar Md Johar and Siew Ann Cheong (2014) Model-Free Analysis of Single fMRI Time Series Based on Spatial Synchronization
  • Asirvatham, D. (2013) Information systems planning. University of Malaya.
  • Syed, S.J.A.N.B., Asirvatham, D., and Khalid, H.H.M. (2012) Quality framework for assessment of multimedia learning materials version 1.0. Procedia-Social and Behavioral Sciences 67, 571-579.
  • Asirvatham, D., and Woods, P. (2012) A Study of a Conductive and Adaptive E-Learning Environment: E-learning Teaching and Learning Artificial Intelligence online learning. LAP Lambert Academic Publishing.
  • Mohamad, S.J.A.N.S. (2010) A PILOT TEST REPORT ON QUALITY FRAMEWORK FOR THE ASSESSMENT OF MULTIMEDIA LEARNING MATERIALS.
  • Asirvatham, D. (2008) Study Of A Conducive And Adaptive E-Learning Environment. Multimedia University.
  • Dauda, Y., and Santhapparaj, A.S. (2007) The impact of e-commerce security, and national environment on consumer adoption of internet banking in Malaysia and Singapore. Journal of Internet Banking and Commerce 12 (2), 01-20.
  • Asirvatham, D. (2007) SCORM 2004: DEVELOPING CONTENT FOR ADAPTIVE E-LEARNING ENVIRONMENT. PENGAJARAN & PEMBELAJARAN IPTA, 37.
  • Jaiballan, M., and Asirvatham, D. (2006) Multimedia learning system (MMLS): Malaysian grown e-learning engine. Available.
  • Chinna, K., Krishnan, K., Woods, P.C., and Asirvatham, D. (2006) A structural model for ESL learning in emerging e-learning environments in Malaysian universities. Institute of Research, Development and Commercialization, Universiti …
  • Asirvatham, D., Kaur, A., and Abas, Z.W. (2005) Country report: e-learning in Malaysia. Retrieved October 1, 2006.
  • Asirvatham, D. (2005) Effective e-learning content management and delivery: Multimedia University’s experience. Online], February 15, 2009.
  • Asirvatham, D., Rahman, A.A., Tat, E.H., Woods, P., Shariman, T.P.N.T., and Ismail, R. (2005) Country Report: Development of e-learning in Malaysia.
  • Abtar, K., Ahmed, A., Abas, Z.W., and Asirvatham, D. (2005) E-learning in malaysia: Streching our horizons. 11th International Conference on Technology Supported Learning & Training …
  • Asirvatham, D., Woods, P., Takahashi, K., and Abtar, K. (2005) E-learning initiatives in Malaysiain E-learning: The future.
  • Kuan, C.Y., and Asirvatham, D. (2004) Addressing Development and Implementation Issues in E-Learning. First COLLA Regional Workshop, Putrajaya, Malaysia, 28-29.
  • Buabeng-Andoh, C., and Asirvatham, D. (2002) Multimedia intelligent system for online learning. International Conference on Computers in Education, 2002. Proceedings., 40-41.
  • Dauda, Y., Guru, B.K., and Asirvatham, D. (2002) Understanding total security architecture for a successful Vol. 4, No. 3, 2014 implementation of e-commerce. International Conference on Internet Economy and Business.
  • Asirvatham, D. (2001) E-Learning: Evolution of education. DISVE-2001 Symposium, November 16 (17), 2002.
  • David Asirvatha0m, Lee Poh Ann and Abu Hassan (2000) The Communication and Multimedia Sector: Cutting-edge Technology
  • Asirvatham, D. (1984) Designing a Database for the Staff Records of the Faculty of Education University of Malaya. Pusat Komputer, Universiti Malaya.

Professor Ts. Dr. David Asirvatham is Professor of Practice, AI & Technology and Head, Information Technology at the Asia School of Business (ASB), which was established in collaboration with MIT Sloan. He has been in the academic leadership and CIO roles for 30 years. His areas of expertise include Digital Neural Network, E-Learning Technologies, ICT Project Management, Multimedia Content Creation and AI.

Prior to joining ASB, he was the Executive Dean for the Faculty of Innovation and Technology at Taylor’s University, Director of the Centre of Information Technology at the University of Malaya, and CIO/Senior Director of the Centre for Information Technology at Multimedia University.

He has held numerous posts, including Associate Dean for Faculty of Information Technology (Multimedia University), Project Manager for the Multimedia and IT Infrastructure Development for a university campus (US$14 million project), and SAP Advisory for High Education Council (Germany).

He was the Chairman of the ICT Human Capital Development for 11th Malaysia Plan 2016-2020, Secretary for the Artificial Intelligence Society Malaysia, President of the Data Science Association (Malaysia) 2022-2025, Country Representative for the Asia E-learning Network (Japan), Steering Committee Member for the Implementation of E-Learning for Malaysian Public Sector, and Member of the Malaysian Grid for Learning’s Standards Expert Group 2003-2004.

He also worked on various ICT Projects and conducted workshops in South Africa, Sudan, Iran, Ghana, Kenya, Vietnam, Maldives, Bangladesh (World Bank Project), UAE, India, and Brunei. David completed his Ph.D. from Multimedia University, M.Sc. (Digital System) from Brunel University (U.K.), and B.Sc. (Hons) Ed., and Post-Graduate Diploma in Computer Science from the University of Malaya. He has published over 70 academic papers and graduated 10 PhD students.

  • Lee, C.H., Mohamad, A.H., and Asirvatham, D. (2026) Data-Driven Football Performance Measurement: A Measure-First Systematic Review of Action-Centric, Individual, Team, and Financial Analytics (2018–2024). Preprints.
  • Masood, J.A.I.S., John, A., Chakravarthy, N.S.K., Asirvatham, D., Murugesan, R.K., et al. (2026) Churn Prediction in the Telecom Sector Using Deep Learning Techniques. Embracing the Digital Horizon: Pioneering Commerce and Management Strategies …
  • Kumar, E.S., BujjiBabu, D., Ibrhaim, S.J.A., Asirvatham, D., Chakravarthy, N.S.K., et al. (2026) Artificial Intelligence Driven Detection and Classification of Brain Tumors: Advancement and Challenges. Demystifying Emerging Trends in the Digital Horizon, 130-143.
  • Palivela, H., Narvekar, M., Asirvatham, D., Bhushan, S., Rishiwal, V., and Agarwal, U. (2025) Code-switching ASR for low-resource Indic languages: A Hindi-Marathi case study. IEEE Access 13, 9171-9198.
  • Das, S.R., Jhanjhi, N.Z., Asirvatham, D., Rizwan, F., and Javed, D. (2025) Securing AI-based healthcare systems using blockchain technology. AI techniques for securing medical and business practices, 333-356.
  • Abdulkareem Shafiq, D., Marjani, M., Ahamed Ariyaluran Habeeb, R., et al. (2025) Digital footprints of academic success: An empirical analysis of Moodle logs and traditional factors for student performance. Education Sciences 15 (3), 304.
  • Das, S.R., Zaman, D.N., Asirvatham, D., Ashfaq, F., Masud, M., and Shorfuzzaman, M. (2025) Empirical performance analysis of hyperledger fabric. Available at SSRN 5127328.
  • Nidamanuri, S., MASOOD, J.A.I., Asirvatham, D., BIN_ABAS, F., VEERAPPAN, K., et al. (2025) Predictive deep learning models to identify traumatic brain injuries using MRI data. Journal of engineering science technology 2.
  • Sharma, A., Marzani, M., Gani, A., Asirvatham, D., Gusaiwal, B., and Kishan, S. (2025) An Evaluation on Features Selection Using Various Methods for Travel Behavior Model Development. International Conference on Innovations in Data Science, 249-257.
  • Sakib, M.K.H., Islam, M.R., Prome, S.A., Jahan, S., Asirvatham, D., Ragavan, N.A., et al. (2025) MVis4SID: Multimodal Visual Interactive System for Suicide Ideation Detection. Companion Proceedings of the ACM on Web Conference 2025, 2024-2033.
  • Sakib, M.K.H., Ragavan, N.A., Prome, S.A., Islam, M.R., Wei, G.W., Asirvatham, D., et al. (2025) A review on multimodal approaches for deception detection: State-of-the-art, challenges, and future directions.
  • V. Sharma, D. Srivastava, S. Pant, M. Kumar and D. Asirvatham, “A Framework for Predicting Diabetic Retinopathy Using Deep Learning and Image Augmentation,” 2025 5th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), Dehradun, India, 2025, pp. 1-5.
  • Prome, S.A., Ragavan, N.A., Islam, M.R., Asirvatham, D., and Jegathesan, A.J. (2024) Deception detection using machine learning (ML) and deep learning (DL) techniques: A systematic review. Natural Language Processing Journal 6, 100057.
  • Masood, J.A.I.S., Chakravarthy, N.S.K., Asirvatham, D., Marjani, M., Shafiq, D.A., et al. (2024) A hybrid deep learning model to predict high-risk students in virtual learning environments. IEEE Access 12, 103687-103703.
  • Sivalingam, P., Asirvatham, D., Marjani, M., Masood, J.A.I.S., Chakravarthy, N.S.K., et al. (2024) A review of travel behavioural pattern using GPS dataset: A systematic literature review. Measurement: Sensors 32, 101031.
  • Gandhi, M., Mulay, C., Durai, K., Murali, G., Masood, J.A.I.S., Vijayarajan, V., et al. (2024) Quantum blockchain: Trends, technologies, and future directions. IET Quantum Communication 5 (4), 516-542.
  • Hossain Sakib, M.K., Islam, M.R., Akter Prome, S., Nguyen, T.T.L., Asirvatham, D., et al. (2024) MVis4LD: Multimodal Visual Interactive System for Lie Detection. Asian Conference on Intelligent Information and Database Systems, 28-43.
  • Prome, S.A., Islam, M.R., Sakib, M.K.H., Asirvatham, D., Ragavan, N.A., Sanin, C., et al. (2024) Ldnet: A robust hybrid approach for lie detection using deep learning techniques. Computers, Materials and Continua 81 (2), 2845-2871.
  • Asirvatham, D., Gonzalez-Longatt, F., Falkowski-Gilski, P., & Kanthavel, R. (Eds.). (2024). Evolutionary artificial intelligence : proceedings of ICEAI 2023. Springer.
  • Das, S.R., Jhanjhi, N.Z., Asirvatham, D., Ashfaq, F., Javed, D., and Gururaj, H.L. (2024) Blockchain-driven splitfed learning for data protection in iot setting.
  • Tandon, R., Verma, A., Kaur, M., Wadhwa, H., and Asirvatham, D. (2024) Management of metropolitan mobility for public transport and smart vehicles with fog computing. Cloud and Fog Optimization-based Solutions for Sustainable Developments, 48-76.
  • Renjie, L., Wei, G.W., Asirvatham, D., and Khan, N.A. (2024) Study of the Impact of Smoking and Alcohol Consumption on the Physical Health of South Korean Residents and Development of Machine Learning Predictive Models. 2024 IEEE 9th International Conference on Engineering Technologies and …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2024) Enhancing Student Performance LMS Data with Feature Engineering for Improved Cluster Quality. 2024 International Conference on Informatics Engineering, Science …
  • Z. Wentong, H. Jazri, D. Asirvatham and S. Teoh, “Maximizing eSports (Apex Legends) Players Arena Performance With Big Data Modeling,” 2024 IEEE 9th International Conference on Engineering Technologies and Applied Sciences (ICETAS), Bahrain, Bahrain, 2024, pp. 1-5.
  • Ahmed Zafran Bin Ahmed Sharizan, Mohsen Marjani, Dalia Abdulkareem Shafiq and Komal Sharma (2024) Towards Enhanced Breast Cancer Prediction: A Comparative Evaluation Study
  • Akibu Mahmoud Abdullahi, Muhammad Hamza Usmani, Md Amin Ullah Sheikh and Sohini Chowdhury (2024) An Efficient AI Based Approach for Multimedia Traffic Management in Wireless Network
  • Paul Yong Ka Ming, Navid Ali Khan, David Asirvatham and Kavita (2024) Detecting Street Parking Occupancy Using Image Recognition with Yolo
  • Xiao Weiqi, Steve Teoh Chee Hooi, Siva Raja A L Sindiramuttyand Sahil Verma (2024) Surface Anomaly Detection Using Machine Learning Technique
  • Das, S.R., Jhanjhi, N.Z., Asirvatham, D., Ashfaq, F., and Abdulhussain, Z.N. (2023) Proposing a model to enhance the IoMT-based EHR storage system security. International Conference on Mathematical Modeling and Computational Science …
  • Alaros, E., Marjani, M., Shafiq, D.A., and Asirvatham, D. (2023) Predicting consumption intention of consumer relationship management users using deep learning techniques: A review. Indonesian Journal of Science and Technology 8 (2), 307-328.
  • Islam, M.R., Sakib, M.K.H., Prome, S.A., Wang, X., Ulhaq, A., Sanin, C., et al. (2023) Machine learning with explainability for suicide ideation detection from social media data. 2023 10th International Conference on Behavioural and Social Computing (BESC …
  • Li, J., Weiwei, G., NZ, J., and David, A. (2023) The smart medicine delivery using UAV for elderly center. International journal of computer science and network security: IJCSNS 23 (1 …
  • Prome, S.A., Islam, M.R., Asirvatham, D., Sakib, M.K.H., and Ragavan, N.A. (2023) Lievis: A visual interactive dashboard for lie detection using machine learning and deep learning techniques. 2023 26th International Conference on Computer and Information Technology …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2022) Student retention using educational data mining and predictive analytics: A systematic literature review. Ieee Access 10, 72480-72503.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2022) Influence maximization diffusion models based on engagement and activeness on instagram. Journal of King Saud University-Computer and Information Sciences 34 (6 …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2022) A Conceptual Predictive Analytics Model for the Identification of at-risk students in VLE using Machine Learning Techniques. 2022 14th International Conference on Mathematics, Actuarial Science …
  • Shafiq, D.A., Marjani, M., Habeeb, R.A.A., and Asirvatham, D. (2022) A narrative review of students’ performance factors for learning analytics models. International Joint Conference on Advances in Computational Intelligence …
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2021) Instagram post popularity trend analysis and prediction using hashtag, image assessment, and user history features. Int. Arab J. Inf. Technol. 18 (1), 85-94.
  • Sharma, A., Gani, A., Asirvatham, D., Ahmed, R., Hamzah, M., and Asli, M.F. (2021) Travel behavior modeling: taxonomy, challenges, and opportunities. Int. J. Adv. Comput. Sci. Appl 12, 774-786.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2021) Influence maximization algorithm: Review on current approaches and limitations. Engineering and Applied Science Research 48 (2), 221-229.
  • Fesabas, A.K.R., Asirvatham, D., and Poulain, J.P. (2021) Facial expression recognition in food studies.
  • Sivalingam, P., Asirvatham, D., and Chinna, K. (2021) A travel behaviour model to predict travel behaviour pattern of urban road user using rule-based approach. 2021 IEEE 7th International Conference on Computing, Engineering and Design …
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2020) Classification of instagram fake users using supervised machine learning algorithms. International Journal of Electrical and Computer Engineering 10 (3), 2763.
  • Perera, C.J., Zainuddin, Z., Piaw, C.Y., Cheah, K.S.L., and Asirvatham, D. (2020) The pedagogical frontiers of urban higher education: Blended learning and co-lecturing. Education and Urban Society 52 (9), 1305-1329.
  • Jayaraman, K., Leow, N.X.C., Asirvatham, D., and Chan, H.R. (2020) Conceptualization of an urban travel behavior model to mitigate air pollution for sustainable environmental development in Malaysia. Management of Environmental Quality: An International Journal 31 (3), 785-799.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2020) An analysis and prediction model of outsiders percentage as a new popularity metric on Instagram. ICT Express 6 (3), 243-248.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2020) Analysis and Prediction of Instagram Users Popularity using Regression Techniques based on Metadata, Media and Hashtags Analysis. Engineering Letters 28 (3), 812.
  • Brohi, S.N., Pillai, T.R., Kaur, S., Kaur, H., Sukumaran, S., and Asirvatham, D. (2019) Accuracy comparison of machine learning algorithms for predictive analytics in higher education. International Conference for Emerging Technologies in Computing, 254-261.
  • Edward, C.N., Asirvatham, D., and Johar, G. (2019) The impact of teaching Oriental music using blended learning approach: An experimental study. Malaysian Journal of Learning and Instruction 16 (1), 81-103.
  • Ayoobkhan, A.L.M., and Asirvatham, D. (2019) A study on the adoption of software as a service (SaaS) in online business SMEs in Sri Lanka. Asian Journal of Research in Computer Science 2 (2), 1-13.
  • Pathirana, S., and Asirvatham, D. (2019) Applicability of multi-agent systems for electroencephalographic data classification. Procedia Computer Science 152, 36-43.
  • Edward, C.N., Asirvatham, D., and Johar, M.G.M. (2018) Effect of blended learning and learners’ characteristics on students’ competence: An empirical evidence in learning oriental music. Education and Information Technologies 23 (6), 2587-2606.
  • Daud, M., Rasiah, R., George, M., Asirvatham, D., and Thangiah, G. (2018) Bridging the gap between organisational practices and cyber security compliance: can cooperation promote compliance in organisations? International Journal of Business & Society 19 (1), 161.
  • Brohi, S.N., Pillai, T.R., Asirvatham, D., Ludlow, D., and Bushell, J. (2018) Towards smart cities development: A study of public transport system and traffic-related air pollutants in Malaysia. IOP conference series: earth and environmental science 167 (1), 012015.
  • Pathirana, S., Asirvatham, D., and Johar, G. (2018) A critical evaluation on low-cost consumer-grade electroencephalographic devices. 2018 2nd International Conference on BioSignal Analysis, Processing and …
  • Vithana, V.N., Asirvatham, D., and Johar, M.G.M. (2018) An empirical study on using agile methods in global software development. 2018 18th International Conference on Advances in ICT for Emerging Regions …
  • Daud, M., Rasiah, R., George, M., Asirvatham, D., Rahman, A.F.A., and Ab Halim, A. (2018) Denial of service:(DoS) Impact on sensors. 2018 4th International Conference on Information Management (ICIM), 270-274.
  • Pathirana, S., Asirvatham, D., and Johar, M.G.M. (2018) An agent based approach for electroencephalographic data classification. 2018 13th International Conference on Computer Science & Education (ICCSE), 1-5.
  • Purba, K.R., Asirvatham, D., and Murugesan, R.K. (2018) A study on the methods to identify and classify cyberbullying in social media. 2018 Fourth International Conference on Advances in Computing, Communication …
  • Pathirana, S., Asirvatham, D., and Johar, M.G.M. (2018) Designing Virtual Keyboards for Brain-Computer Interfaces. 2018 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 1-6.
  • Pathirana, S., Asirvatham, D., and Johar, M.G.M. (2018) A multi-agent system for improving electroencephalographic data classification accuracy. 2018 IEEE Region 10 Humanitarian Technology Conference (R10-HTC), 1-6.
  • XeChung, L.N., Krishnaswamy, J., and Asirvatham, D. (2018) Proposed urban travel behavior model to promote smart mobility. 2018 Fourth International Conference on Advances in Computing, Communication …
  • Abdullah, A., Ponnan, R., and Asirvatham, D. (2018) Improving multiclass classification in intrusion detection using clustered linear separator analytics. 2018 8th International Conference on Intelligent Systems, Modelling and …
  • Vithana, V., Asirvatham, D., and Johar, M. (2018) Challenges to Practice Agile Methods in Global Software Development-A Review of Literature. International Journal of Computer Applications 179 (40), 975-8887.
  • Asirvatham, D., Brohi, S.N., Xion, T.E., Theng, T.G., Fei, N.J., Kaur, S., Pillai, T.R., et al. (2018) Smart Mobility Cities: Connecting Bristol and Kuala Lumpur Project Report.
  • Kalith, I.M., Asirvatham, D., Khatibi, A., and Thelijjagoda, S. (2018) Comparison of Syllable and Phoneme Modelling of Agglutinative Tamil Isolated Words in Speech Recognition. Current Journal of Applied Science and Technology, 1-10.
  • Maheswaran, M., and Asirvatham, D. (2018) Real-Time Business Analytical Model Using Big Data Strategies for Telecommunication Industry. Information Systems Design and Intelligent Applications: Proceedings of …
  • Wei, C.Y., Fauzi, I.S.B.M., Thenmoley, R., Elhussein, E.S.E., and Asirvatham, D. (2018) Business and Economics Journal.
  • Chin Yung Wei, Intan Syahidah Bt Mohd Fauzi, Thenmoley Ramkumar and David Asirvatham (2018) E-commerce Adoption and Analysis of the Popular E-commerce Business Sites in Malaysia
  • Ayoobkhan, A.L.M., and Asirvatham, D. (2017) Adoption of cloud computing services in healthcare sectors: Special attention to private hospitals in Colombo District, Sri Lanka. British Journal of Applied Science & Technology.
  • Vithana, V.N., Asirvatham, D., and Johar, M.G.M. (2017) Investigating the issues of using agile methods in offshore software development in Sri Lanka. Asian Conference on Intelligent Information and Database Systems, 515-523.
  • Ayoobkhan, A.L.M., and Asirvatham, D. (2017) Issues and challenges faced by online business organizations in adopting cloud computing: A research agenda. International Journals of Advanced Research in Computer Science and Software …
  • Perera, C.J., Chua, Y.P., Asirvatham, D., Zainuddin, Z., Harris, A., and Jones, M. (2017) The enhancement of teaching and learning through blended learning and collaborative co-lecturing.
  • Ibralebbe Mohamed Kalith, David Asirvatham and Ismail Raisal, 2017. Context-dependent Syllable Modeling of Sentence-based Semi-continuous Speech Recognition for the Tamil Language. Information Technology Journal, 16: 125-133.
  • Kalith, I.M., Ashirvatham, D., and Thelijjagoda, S. (2016) Isolated to connected Tamil digit speech recognition system based on hidden Markov model. www. ijntse. com.
  • David Asirvatham (2014) Functional Discrimination of fMRI Data from Multiple Subjects
  • Ngoc Dung Dui, David Asirvatham, Md Gapar Md Johar and Siew Ann Cheong (2014) Model-Free Analysis of Single fMRI Time Series Based on Spatial Synchronization
  • Asirvatham, D. (2013) Information systems planning. University of Malaya.
  • Syed, S.J.A.N.B., Asirvatham, D., and Khalid, H.H.M. (2012) Quality framework for assessment of multimedia learning materials version 1.0. Procedia-Social and Behavioral Sciences 67, 571-579.
  • Asirvatham, D., and Woods, P. (2012) A Study of a Conductive and Adaptive E-Learning Environment: E-learning Teaching and Learning Artificial Intelligence online learning. LAP Lambert Academic Publishing.
  • Mohamad, S.J.A.N.S. (2010) A PILOT TEST REPORT ON QUALITY FRAMEWORK FOR THE ASSESSMENT OF MULTIMEDIA LEARNING MATERIALS.
  • Asirvatham, D. (2008) Study Of A Conducive And Adaptive E-Learning Environment. Multimedia University.
  • Dauda, Y., and Santhapparaj, A.S. (2007) The impact of e-commerce security, and national environment on consumer adoption of internet banking in Malaysia and Singapore. Journal of Internet Banking and Commerce 12 (2), 01-20.
  • Asirvatham, D. (2007) SCORM 2004: DEVELOPING CONTENT FOR ADAPTIVE E-LEARNING ENVIRONMENT. PENGAJARAN & PEMBELAJARAN IPTA, 37.
  • Jaiballan, M., and Asirvatham, D. (2006) Multimedia learning system (MMLS): Malaysian grown e-learning engine. Available.
  • Chinna, K., Krishnan, K., Woods, P.C., and Asirvatham, D. (2006) A structural model for ESL learning in emerging e-learning environments in Malaysian universities. Institute of Research, Development and Commercialization, Universiti …
  • Asirvatham, D., Kaur, A., and Abas, Z.W. (2005) Country report: e-learning in Malaysia. Retrieved October 1, 2006.
  • Asirvatham, D. (2005) Effective e-learning content management and delivery: Multimedia University’s experience. Online], February 15, 2009.
  • Asirvatham, D., Rahman, A.A., Tat, E.H., Woods, P., Shariman, T.P.N.T., and Ismail, R. (2005) Country Report: Development of e-learning in Malaysia.
  • Abtar, K., Ahmed, A., Abas, Z.W., and Asirvatham, D. (2005) E-learning in malaysia: Streching our horizons. 11th International Conference on Technology Supported Learning & Training …
  • Asirvatham, D., Woods, P., Takahashi, K., and Abtar, K. (2005) E-learning initiatives in Malaysiain E-learning: The future.
  • Kuan, C.Y., and Asirvatham, D. (2004) Addressing Development and Implementation Issues in E-Learning. First COLLA Regional Workshop, Putrajaya, Malaysia, 28-29.
  • Buabeng-Andoh, C., and Asirvatham, D. (2002) Multimedia intelligent system for online learning. International Conference on Computers in Education, 2002. Proceedings., 40-41.
  • Dauda, Y., Guru, B.K., and Asirvatham, D. (2002) Understanding total security architecture for a successful Vol. 4, No. 3, 2014 implementation of e-commerce. International Conference on Internet Economy and Business.
  • Asirvatham, D. (2001) E-Learning: Evolution of education. DISVE-2001 Symposium, November 16 (17), 2002.
  • David Asirvatha0m, Lee Poh Ann and Abu Hassan (2000) The Communication and Multimedia Sector: Cutting-edge Technology
  • Asirvatham, D. (1984) Designing a Database for the Staff Records of the Faculty of Education University of Malaya. Pusat Komputer, Universiti Malaya.