Faculty Profile

Priyan Malarvizhi Kumar

Assistant Professor
Information Science
College of Information



PhD, Vellore Institute of Technology - India, 2019.
Major: Information Technology
Dissertation Title: A Secured Three Tier IOT Framework for Prediction of Heart Disease
MTech, Vellore Institute of Technology - India, 2015.
Major: Information Technology
BTech, Anna University, 2013.
Major: Information Technology

Current Scheduled Teaching*

DTSC 5505.003, Applied Machine Learning for Data Scientists, Summer 2024

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching*

DTSC 5502.020, Principles and Techniques for Data Science, Spring 2024 SPOT
DTSC 5502.021, Principles and Techniques for Data Science, Spring 2024 SPOT
DTSC 4501.501, Principles of Data Science and Analytics, Spring 2024 Syllabus SPOT
DTSC 4050.020, Statistical Methods for Data Science and Analysis, Spring 2024 Syllabus SPOT
DTSC 5501.002, Fundamentals of Data Science, Fall 2023 Syllabus SPOT
DTSC 3020.501, Introduction to Computation with Python, Fall 2023 Syllabus SPOT

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Publications

Published Intellectual Contributions

Rishiwal, V., Kumar, P., Tomar, A., Malarvizhi Kumar, P. (2023). Towards the Integration of IoT, Cloud and Big Data: Services, Applications and Standards. Springer. https://www.amazon.com/Towards-Integration-IoT-Cloud-Data-ebook/dp/B0CFGLBD9C
Book Chapter
Thota, C., Sundarasekar, R., Manogaran, G., R, V., Malarvizhi Kumar, P. (2018). Centralized Fog Computing Security Platform for IoT and Cloud in Healthcare System. IGI. https://www.igi-global.com/chapter/centralized-fog-computing-security-platform-for-iot-and-cloud-in-healthcare-system/187898
Conference Proceeding
Malarvizhi Kumar, P., Rawal, B., Gao, J. (2022). Blockchain-enabled Privacy Preserving of IoT Data for Sustainable Smart Cities using Machine Learning. 2022 14th International Conference on COMmunication Systems & NETworkS (COMSNETS). https://ieeexplore.ieee.org/abstract/document/9668530
Raza, M., Malarvizhi Kumar, P., Hung, D., Davis, W., Nguyen, H., Trestian, R. (2020). A Digital Twin Framework for Industry 4.0 Enabling Next-Gen Manufacturing. 2020 9th International Conference on Industrial Technology and Management (ICITM). https://ieeexplore.ieee.org/abstract/document/9080395
Malarvizhi Kumar, P., Gokul Nath, C., Vishnu Balan, E., Jeyanthi, R., Rama Prabha, K. (2015). Desktop phishing attack detection and elimination using TSO program. 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM). https://ieeexplore.ieee.org/abstract/document/7225413
Vishnu Balan, E., Malarvizhi Kumar, P., Gokul Nath, C., Usha Devi, G. (2015). Efficient energy scheme for wireless sensor network application. 2014 IEEE International Conference on Computational Intelligence and Computing Research. https://ieeexplore.ieee.org/abstract/document/7238472
Vishnu Balan, E., Malarvizhi Kumar, P., Gokulnath, C., Usha Devi, G. (2015). Fuzzy Based Intrusion Detection Systems in MANET. Procedia Computer Science. https://www.sciencedirect.com/science/article/pii/S1877050915005724
Vishnu Balan, E., Malarvizhi Kumar, P., Gokulnath, C., Usha Devi, G. (2015). Hybrid architecture with misuse and anomaly detection techniques for wireless networks. 2015 International Conference on Communications and Signal Processing (ICCSP). https://ieeexplore.ieee.org/abstract/document/7322846
Gokulnath, C., Malarvizhi Kumar, P., Vishnu Balan, E., Rama Prabha, K., Jeyanthi, R. (2015). Preservation of privacy in data mining by using PCA based perturbation technique. 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM). https://ieeexplore.ieee.org/abstract/document/7225414
Journal Article
Malarvizhi Kumar, P., Kamruzzaman, M., Alfurhood, B., Hossain, B., Nagarajan, H., Sitaraman, S. (2024). Balanced Performance Merit on Wind and Solar Energy Contact with Clean Environment Enrichment. IEEE Journal of the Electron Devices Society. https://ieeexplore.ieee.org/document/10413364
Sivaparthipan, C., Malarvizhi Kumar, P., Chandu, T., Muthu, B., Hasan Ali, M., Tomaš, B. (2023). Classification analysis of burnout people's brain images using ontology-based speculative sense model. Computational Intelligence. https://onlinelibrary.wiley.com/doi/abs/10.1111/coin.12595
Gao, ., Manogaran, ., Nguyen, ., Kadry, ., Hsu, ., Malarvizhi Kumar, P. (2022). A Vehicle-Consensus Information Exchange Scheme for Traffic Management in Vehicular Ad-Hoc Networks. IEEE Transactions on Intelligent Transportation Systems. 23(10), 19602 - 19612. https://ieeexplore.ieee.org/abstract/document/9707610
Malarvizhi Kumar, P., Konstantinou, C., Basheer, S., Manogaran, G., S. Rawal, B., Chandra Babu, G. (2022). Agreement-Induced Data Verification Model for Securing Vehicular Communication in Intelligent Transportation Systems. IEEE Transactions on Intelligent Transportation Systems. 24(1), 980 - 989. https://ieeexplore.ieee.org/abstract/document/9905743
C. B., S., Muthu, ., G., ., Malarvizhi Kumar, P., Alazab, ., Díaz, V. (2022). Blockchain Assisted Disease Identification of COVID-19 Patients with the Help of IDA-DNN Classifier. Wireless Personal Communications. 1379(126), 2597–2620. Springer. https://link.springer.com/article/10.1007/s11277-022-09831-7
Yousafzai, A., Malarvizhi Kumar, P., Hong, . (2022). Blockchain-based incentive management framework for desktop clouds. Journal of Cluster Computing. 26(383), 137–156. https://link.springer.com/article/10.1007/s10586-022-03557-8
Vincent Paul, S., Balasubramaniam, S., Panchatcharam, P., Malarvizhi Kumar, P., Mubarakali, A. (2022). Intelligent Framework for Prediction of Heart Disease using Deep Learning. Arabian Journal for Science and Engineering. https://link.springer.com/article/10.1007/s13369-021-06058-9
Malarvizhi Kumar, P., Hong, C. (2022). Internet of things for secure surveillance for sewage wastewater treatment systems. Environmental Research. https://www.sciencedirect.com/science/article/abs/pii/S0013935121011944
Wei, W., C. B, ., Malarvizhi Kumar, P. (2022). Online shopping behavior analysis for smart business using big data analytics and blockchain security. International Journal of Modeling and Simulation. 13(04), . https://www.worldscientific.com/doi/abs/10.1142/S1793962322500532
Zhao, J., Xi, ., Zhang, ., Malarvizhi Kumar, P. (2022). Reuse of knowledge by efficient data analytics to fix societal challenges. Information Processing & Management. 59(1), . https://www.sciencedirect.com/science/article/abs/pii/S0306457321002454
Zhang, W., Qinb, G., Zhao, Z., Liu, W., Zhang, S., Malarvizhi Kumar, P. (2022). The role of socioeconomic status gradients for the child's developmental health.. Early Child Development and Care. 193((7)), 869-885. London: Taylor & Francis. https://www.tandfonline.com/doi/abs/10.1080/03004430.2022.2050718
Malarvizhi Kumar, P., Basheer, S., Rawal, B., Afghah, F., Chandra Babu, G., Arunmozhi, M. (2022). Traffic scheduling, network slicing and virtualization based on deep reinforcement learning. Elsevier International Journal on Computers and Electrical Engineering. 100, . https://www.sciencedirect.com/science/article/abs/pii/S0045790622002567
Liu, Y., Zhou, ., Wang, ., R., ., Malarvizhi Kumar, P. (2021). Brain-computer Interaction Enabled AAC for Visual Interactive Paradigm. International Journal on Artificial Intelligence Tools. https://www.worldscientific.com/doi/abs/10.1142/S0218213021400133
Manimuthu, A., Dharshini, V., Zografopoulos, I., Malarvizhi Kumar, P., Konstantinou, C. (2021). Contactless Technologies for Smart Cities: Big Data, IoT, and Cloud Infrastructures. SN Computer Science. https://link.springer.com/article/10.1007/s42979-021-00719-0
Zhan, H., Wang, L., Chen, S., Malarvizhi Kumar, P., P., M. (2021). Detection and alerting system of nearby medical facilities during emergency using IoT sensors. Journal of Ambient Intelligence and Humanized Computing. https://link.springer.com/article/10.1007/s12652-021-03007-0
He, Y., Nie, B., Zhang, J., Malarvizhi Kumar, P., Muthu, B. (2021). Fault Detection and Diagnosis of Cyber-Physical System Using the Computer Vision and Image Processing. Wireless Personal Communications. https://link.springer.com/article/10.1007/s11277-021-08774-9
Manogaran, G., Mohamed Shakeel, P., Baskar, S., Hsu, C., Kadry, S., Sundarasekar, R., Malarvizhi Kumar, P. (2021). FDM: Fuzzy-Optimized Data Management Technique for Improving Big Data Analytics. IEEE Transactions on Fuzzy Systems. https://ieeexplore.ieee.org/abstract/document/9166621
Zhen, H., Malarvizhi Kumar, P., R., D. (2021). Internet of Things Framework in Athletics Physical Teaching System and Health Monitoring. International Journal on Artificial Intelligence Tools. https://www.worldscientific.com/doi/abs/10.1142/S0218213021400169
Manogaran, G., Balasubramanian, V., S. Rawal, B., Saravanan, V., Montenegro-Marin, C., Ramachandran, V., Malarvizhi Kumar, P. (2021). Multi-Variate Data Fusion Technique for Reducing Sensor Errors in Intelligent Transportation Systems. IEEE Sensors. https://ieeexplore.ieee.org/abstract/document/9169903
Gandhi, U., Malarvizhi Kumar, P., Chandra Babu, G., Karthick, G. (2021). Sentiment Analysis on Twitter Data by Using Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM). Wireless Personal Communications.
Son, L., Ngan, R., Ali, M., Fujita, H., Abdel-Basset, M., Long Giang, N., Malarvizhi Kumar, P. (2020). A New Representation of Intuitionistic Fuzzy Systems and Their Applications in Critical Decision Making. IEEE Intelligent Systems. https://ieeexplore.ieee.org/abstract/document/8821387
Bi, D., Kadry, S., Malarvizhi Kumar, P. (2020). Internet of things assisted public security management platform for urban transportation using hybridised cryptographic-integrated steganography. IET Intelligent Transport Systems. https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/iet-its.2019.0833
Selvaraj, A., Selvaraj, J., Maruthaiappan, S., Chandra Babu, G., Malarvizhi Kumar, P. (2020). L1 norm based pedestrian detection using video analytics technique. Computational Intelligence. https://onlinelibrary.wiley.com/doi/abs/10.1111/coin.12292
Jegadeesan, S., Azees, M., Malarvizhi Kumar, P., Manogaran, G., Chilamkurti, N., Varatharajan, ., Hsu, C. (2019). An efficient anonymous mutual authentication technique for providing secure communication in mobile cloud computing for smart city applications. Sustainable Cities and Society. https://www.sciencedirect.com/science/article/abs/pii/S2210670718301720
Manogaran, G., Varatharajan, R., Lopez, D., Malarvizhi Kumar, P., Sundarasekar, R., Thota, C. (2018). A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system. Future Generation Computer Systems. https://www.sciencedirect.com/science/article/abs/pii/S0167739X17305149
Malarvizhi Kumar, P., Gandhi, U. (2018). A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases. Computers & Electrical Engineering. https://www.sciencedirect.com/science/article/abs/pii/S0045790617328410
Varatharajan, R., Vasanth, K., Gunasekaran, M., Malarvizhi Kumar, P., Gao, X. (2018). An adaptive decision based kriging interpolation algorithm for the removal of high density salt and pepper noise in images. Computers & Electrical Engineering. https://www.sciencedirect.com/science/article/abs/pii/S0045790617315409
Malarvizhi Kumar, P., G, U., Manogaran, G., Sundarasekar, R., Chilamkurti, N., Varatharajan, R. (2018). Ant colony optimization algorithm with Internet of Vehicles for intelligent traffic control system. Computer Networks. https://www.sciencedirect.com/science/article/abs/pii/S1389128618304845
Malarvizhi Kumar, P., Lokesh, S., Varatharajan, R., Chandra Babu, G., Parthasarathy, P. (2018). Cloud and IoT based disease prediction and diagnosis system for healthcare using Fuzzy neural classifier. Future Generation Computer Systems. https://www.sciencedirect.com/science/article/abs/pii/S0167739X18303753
Gandhi, U., Malarvizhi Kumar, P., Varatharajan, R., Manogaran, G., Sundarasekar, R., Kadu, S. (2018). HIoTPOT: Surveillance on IoT Devices against Recent Threats. Wireless Personal Communications. https://link.springer.com/article/10.1007/s11277-018-5307-3
Sundarasekar, R., Thanjaivadivel, ., Manogaran, G., Malarvizhi Kumar, P., Varatharajan, R., Chilamkurti, N., Hsu, C. (2018). Internet of Things with Maximal Overlap Discrete Wavelet Transform for Remote Health Monitoring of Abnormal ECG Signals. Journal of Medical Systems. https://link.springer.com/article/10.1007/s10916-018-1093-4
Varatharajan, R., Peace Preethi, A., Manogaran, G., Malarvizhi Kumar, P., Sundarasekar, R. (2018). Stealthy attack detection in multi-channel multi-radio wireless networks. Multimedia Tools and Applications. https://link.springer.com/article/10.1007/s11042-018-5866-z
Malarvizhi Kumar, P., Usha Devi, G. (2017). Energy efficient node selection algorithm based on node performance index and random waypoint mobility model in internet of vehicles. Journal of Cluster Computing. https://link.springer.com/article/10.1007/s10586-017-0998-x
Malarvizhi Kumar, P., Gandhi, U. (2017). Enhanced DTLS with CoAP-based authentication scheme for the internet of things in healthcare application. Journal of Supercomputing. https://link.springer.com/article/10.1007/s11227-017-2169-5
Manogaran, G., Vijayakumar, V., Varatharajan, R., Malarvizhi Kumar, P., Sundarasekar, R., Hsu, C. (2017). Machine Learning Based Big Data Processing Framework for Cancer Diagnosis Using Hidden Markov Model and GM Clustering. Wireless Personal Communications. https://link.springer.com/article/10.1007/s11277-017-5044-z
Varatharajan, R., Manogaran, G., Malarvizhi Kumar, P., Balaş, V., Barna, C. (2017). Visual analysis of geospatial habitat suitability model based on inverse distance weighting with paired comparison analysis. Multimedia Tools and Applications. https://link.springer.com/article/10.1007/s11042-017-4768-9
Varatharajan, R., Manogaran, G., Malarvizhi Kumar, P., Sundarasekar, R. (2017). Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm. Journal of Cluster Computing. https://link.springer.com/article/10.1007/s10586-017-0977-2

Awarded Grants

Contracts, Grants and Sponsored Research

Grant - Research
Malarvizhi Kumar, P. (Principal), Xiao, T. (Co-Principal), Korani, W. (Co-Principal), "Cohort II of the Capacity Building for Research at Minority-Serving Institutions: Infrastructure Research Readiness," Sponsored by NSF, Federal, $3000 Funded. (November 2023August 2024).
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was