Dr. Satheesh Abimannan is an Assistant Professor in the College of Computing at Euro University of Bahrain, specialising in Information Security, Machine Learning, Deep Learning, Cloud Computing, and Big Data Analytics. He holds a Ph.D. in Computer Science and Engineering and completed a Postdoctoral Fellowship at the Research Center on Big Data and Smart City, National Taipei University, Taiwan. His notable roles include Professor and Deputy Director at Amity University, Mumbai, and Professor and Director at Symbiosis Skills and Professional University, Pune.

Throughout his career, he has made significant contributions to teaching and academic leadership. As an Assistant Professor at Euro University of Bahrain and a Professor and Deputy Director at Amity University, he has worked on curriculum design, teaching methodologies, and enhancing student engagement. He has consistently integrated emerging technologies, such as Big Data Analytics and Machine Learning, into his teaching practices to prepare students with industry-relevant skills.

He leverages his research expertise in Information Security, Machine Learning, and Cloud Computing to provide students with practical insights and hands-on experience. He has successfully guided students in interdisciplinary projects, some of which have been recognised at academic conferences. Additionally, he has contributed to academic initiatives nationally and internationally, including organising conferences like the International Conference on Recent Advances in Computational Techniques (IC-RACT 2022) and serving as a guest editor for reputed journals. These roles reflect his commitment to academic excellence and fostering student success.

Management and Leadership Roles in Learning and Teaching

• 2023 – Present: Assistant Professor, Euro University of Bahrain, College of Computing
• 2021 – 2024: Professor and Deputy Director, Amity University, Mumbai
• 2020 – 2021: Professor and Director, School of Data Science, Symbiosis Skills and Professional University
• 2016 – 2019: Associate Professor, School of Computer Science and Engineering (SCOPE), VIT University
• 2007 – 2016: Assistant Professor (Senior Scale) and HoD, Periyar Maniammai University

For more information about Dr. Satheesh’s professional background, you can visit his profiles on Google Scholar, ResearchGate, ORCID, and Scopus.

His current research focuses on Information Security, Machine Learning, Deep Learning, Cloud Computing, and Big Data Analytics. He is particularly interested in exploring the integration of these domains to address emerging challenges in cybersecurity, air quality monitoring, water quality management, and IoT-enabled systems. His work aims to develop innovative methodologies for data-driven decision-making, with a strong emphasis on spatiotemporal modelling, edge intelligence, and secure computing frameworks.

He has a proven track record of securing research funding and collaborating with international institutions, which has allowed him to advance research in diverse areas such as malware analysis, federated learning, and blockchain-based energy trading models. His ongoing projects involve cutting-edge applications of AI and Machine Learning in 5G network security and environmental pollution forecasting.

Publications

1. Yue-Shan Chang, Shu-Ting Huang, Basanta Haobijam, Satheesh Abimannan, Takayuki Kushida, Marine ecological information prediction by using adjacent location spatiotemporal deep learning model with ensemble learning techniques, Ecological Informatics,85,2025. (Q1, SCI, SCOPUS, 5.9.) https://doi.org/10.1016/j.ecoinf.2024.102964
2. Kuo-Hsuan Chung, Yue-Shan Chang, Wei-Ting Yen, Linen Lin, Satheesh Abimannan, Depression assessment using integrated multi-featured EEG bands deep neural network models: Leveraging ensemble learning techniques, Computational and Structural Biotechnology Journal,23,2024,1450-1468. (Q1, SCI, SCOPUS, 4.5) https://www.csbj.org/article/S2001-0370(24)00075-8/fulltext
3. Satheesh Abimannan, El-Alfy E-SM, Hussain S, Chang Y-S, Shukla S, Dhivyadharsini Satheesh D, Breslin JG. Towards Federated Learning and Multi-Access Edge Computing for Air Quality Monitoring: Literature Review and Assessment. Sustainability. 2023; 15(18):13951. (SCI, IF-3.9) https://doi.org/10.3390/su151813951
4. Satheesh Abimannan, E. -S. M. El-Alfy, Y. -S. Chang, S. Hussain, S. Shukla and Dhivyadharsini Satheesh, “Ensemble Multifeatured Deep Learning Models and Applications: A Survey,” in IEEE Access, vol. 11, pp. 107194-107217, 2023. (SCI, IF-3.9) https://ieeexplore.ieee.org/document/10265042
5. Saurabh Shukla, Shahid Hussain, Satheesh Abimannan, Shahid Husain, Syed Muslim Jameel, Network analysis in a peer-to-peer energy trading model using blockchain and machine learning, Computer Standards & Interfaces,88,2024,103799. (Q1, SCI, IF- 5.0) https://doi.org/10.1016/j.csi.2023.103799
6. Shahid Hussain, Reyazur Rashid Irshad, Fabiano Pallonetto, Satheesh Abimannan, Saurabh Shukla, Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles, Applied Energy,352,2023,121939. https://doi.org/10.1016/j.apenergy.2023.121939
7. Hui-Chin Wu, Yue-Shan Chang *, Yu-Hsiang Chang, Satheesh Abimannan. “The Process and Platform for Predicting PM2.5 Inhalation and Retention during Exercise” Processes. Processes 2021, 9(11). (SCOPUS, SCI, IF 2.847). https://doi.org/10.3390/pr9112026
8. Ankita Bose, Ching-Hsien Hsu, Sanjiban Sekhar Roy, Kun Chang Lee, Behnam Mohammadi-ivatloo, Satheesh Abimannan “Forecasting stock price by hybrid model of cascading Multivariate Adaptive Regression Splines and Deep Neural Network”, Computers & Electrical Engineering, 95(15-16):107405. (Q1, SCOPUS, SCI, IF 3.818) https://doi.org/10.1016/j.compeleceng.2021.107405
9. Chi-Yeh Lin, Yue-Shan Chang, Satheesh Abimannan, “Ensemble Multi-Features Deep Learning Models for Air Quality Forecasting” Atmospheric Pollution Research (2021), 12(5), pp.1-16. https://doi.org/10.1016/j.apr.2021.03.008. (SCOPUS, SCI, IF 3.527) https://www.sciencedirect.com/science/article/abs/pii/S1309104221001057
10. Yue-Shan Chang, Satheesh Abimannan, Hsin-Ta Chiao, Chi-Yeh Lin “An Ensemble Learning based Hybrid Model and Framework for Air Pollution Forecasting” Environmental Science and Pollution Research (2020), https://doi.org/10.1007/s11356-020-09855-1 (SCOPUS, SCI, IF 3.056) https://link.springer.com/article/10.1007/s11356-020-09855-1
11. Yue-Shan Chang, Hsin-Ta Chiao, Satheesh Abimannan, Yo-Ping Huang, Yi_Ting Tsai, Kuan-Ming Lin “An LSTM-based Aggregated Air Pollution Forecasting Model” Atmospheric Pollution Research, 11(8), pp.1451-1463, 2020. (SCOPUS, SCI, IF 3.527) https://doi.org/10.1016/j.apr.2020.05.015
12. Ren-Hung Hwang, Min-chun Peng, Cheng-Yu Wu, Satheesh Abimannan “A Novel RPL-based Multicast Routing Mechanism for Wireless Sensor Networks” International Journal of Ad Hoc and Ubiquitous Computing, 33(2),pp.122-131, 2020. https://doi.org/10.1504/ijahuc.2020.105474. (SCOPUS, SCI, IF 0.648) https://www.inderscience.com/info/inarticle.php?artid=105474
13. Satheesh Abimannan, Kumaravelu R “A Mathematical model of HMST model on Malware Static Analysis” International Journal of Information Security and Privacy (IJISP), vol.13(2),pp.86-103,2019. (SCOPUS, ESCI, Web of Science) https://ideas.repec.org/a/igg/jisp00/v13y2019i2p86-103.html
14. Satheesh A, Ravikumar Ramadoss, Elango N.M, Ching-Hsien Hsu, “EMAPM: Enterprise Modernization Autonomic Predictive Model in Hybrid Cloud Environments” 2017 IEEE 7th International Symposium on Cloud and Service Computing, 22-25 November 2017, Kanazawa, Japan, IEEE Press, pp.56-62. (SCOPUS, Web of Science) https://www.igi-global.com/article/a-mathematical-model-of-hmst-model-on-malware-static-analysis/226951
15. Ravikumar Ramadoss, N. M. Elango, Satheesh A. and Ching-Hsien Hsu, ”Non-Intrusive Transaction Aware Filtering During Enterprise Application Modernization”, Journal of Supercomputing,74(3),pp.1157-1181,2018. (SCOPUS, SCI, EI, IF:1.5) https://link.springer.com/article/10.1007/s11227-017-2123-6
16. Ravikumar Ramadoss, N. M. Elango, Satheesh A. and Ching-Hsien Hsu, “PSPO: A Framework for Cost Effective Service Placement Optimization during enterprise modernization on Hybrid Clouds”, International Journal of Web and Grid Services, vol.14(2),pp.170-199, 2018. (SCOPUS, SCI, EI, IF:1.229) https://www.inderscience.com/info/inarticle.php?artid=90740
17. A. Satheesh, D.Kumar, P.Dharmalingam, TKS.Lakshmipriya “Dynamically Reconfigurable Queue for Intel IXP2400 Network Processor” Journal of Internet Technology, Vol.18(1),pp.95-101,2017. (SCOPUS, SCI, EI: IF-1.930) https://jit.ndhu.edu.tw/article/view/1440
18. Krishnaveni, A.Satheesh, Kannan.E, “Review of Big Data on Student Information for Finding the Uncertainty in Higher Education Enrollment” International Journal of Grid and High Performance Computing (IJGHPC), Vol.7 (4) ,pp.21-32, 2015. (SCOPUS, ESCI, Web of Science) https://www.igi-global.com/article/review-of-big-data-on-student-information-for-finding-the-uncertainty-in-higher-education-enrollment/141354
19. Manju Kaushal, Satheesh Abimannan “Automated slicing scheme for test case prioritization in regression testing” International Journal of Engineering & Technology, vol.7(4.17),pp.5266-5271,2018. (Scopus). https://www.sciencepubco.com/index.php/ijet/article/view/28037
20. Purshottam J. Assudani, Satheesh Abimannan “Cost Efficient Resource Scheduling in Cloud Computing: A Survey” International Journal of Engineering & Technology, vol.7(4.17),pp.38-43,2018. (Scopus) https://www.sciencepubco.com/index.php/ijet/article/view/21799
21. Purshottam J. Assudani, Satheesh Abimannan “Power Efficient and Workload Aware Scheduling in cloud: A Review” International Journal of Engineering & Technology, vol.7(4.17),pp.44-52, 2018. (Scopus) https://www.sciencepubco.com/index.php/ijet/article/view/21801
22. A. Satheesh., Kumar.D and Jayakumar.K ”Energy Efficient Dynamic Adaptive Self-configurable Network Processor”, Journal of Theoretical and Applied Information Technology, Vol. 63, No. 2, pp.477-485, 2014. (Scopus) http://www.jatit.org/volumes/Vol63No2/28Vol63No2.pdf
23. A. Satheesh, S.Krishnaveni, S.Ponkarthick “Self-Configurable Environment for the Intel IXP2400 Network processor”, International journal of Computers and Network Applications”, vol.31, pp.268-273 , 2009. (Scopus) https://www.tandfonline.com/doi/abs/10.1080/1206212X.2009.11441950
24. Abhishek Vyas, Satheesh A.,”Implementing Security Features in MANET Routing Protocols”, International Journal of Computer Network and Information Security (IJCNIS), Vol.10, No.8, pp.51-57, 2018.DOI: 10.5815/ijcnis.2018.08.06 http://www.mecs-press.org/ijcnis/ijcnis-v10-n8/IJCNIS-V10-N8-6.pdf
25. Kumaravelu, Satheesh. A, Poornima. S, V.Murugesh “Wireless Sensor Network Storage with Light Weight File System using Update Logic for Cloud Interface” International Journal of Applied Engineering Research, vol.12(17),pp. 6323-6329, 2017. http://www.ripublication.com/ijaer17/ijaerv12n17_01.pdf
26. A. Satheesh, D.Kumar , A.V.Jeyakumar “ Run-Time Adaptive Processor Allocation of Self-Configurable Intel IXP 2400 Network Processor ”, International Journal of Computer Networks (IJCN), Vol.10, Issue.4, pp16-33,2010 https://www.cscjournals.org/manuscript/Journals/IJCN/Volume2/Issue1/IJCN-24.pdf
27. Abimannan, S., El-Alfy, ES.M., Shukla, S., Dhivyadharsini. (2024). Spatiotemporal Particulate Matter Pollution Prediction Using Cloud-Edge Intelligence. In: Luo, B., Cheng, L., Wu, ZG., Li, H., Li, C. (eds) Neural Information Processing. ICONIP 2023. Communications in Computer and Information Science, vol 1965. Springer, Singapore. https://doi.org/10.1007/978-981-99-8145-8_8
28. S. Abimannan, J. A, S. Shukla and Dhivyadharsini, S, “Federated Learning for Improved Air Pollution Prediction: A Combined LSTM-SVR Approach,” 2023 IEEE 4th Annual Flagship India Council International Subsections Conference (INDISCON), Mysore, India, 2023, pp. 1-7. https://ieeexplore.ieee.org/document/10270612
29. Y. S. Chang, S. Abimananan, S. Shukla and Dhivyadharsini,S, “Forecasting Continuous Air Pollution with Cloud-Based Big Data Platform using Spatial-Temporal Visualization,” 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), Lonavla, India, 2023, pp. 1-8. https://ieeexplore.ieee.org/document/10126153
30. Kajal Jewani, Satheesh Abimannan, “Edge Intelligence in IoT: Architecture and Applications” Proceedings of the 8th International Conference on Communication and Electronics Systems (ICCES 2023), pp.326-335, 2023. https://ieeexplore.ieee.org/document/10192608
31. Thirunavukkarasu K., Gupta A., Satheesh Abimannan., Khan S. (2021) Intracranial Hemorrhage Detection Using Deep Convolutional Neural Network. In: Saini H.S., Sayal R., Govardhan A., Buyya R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 171. Springer, Singapore. (SCOPUS indexed) https://link.springer.com/chapter/10.1007/978-981-33-4543-0_46
32. Shahnawaz Khan; Mohamed Redha Qader; Thirunavukkarasu K; Satheesh Abimannan “Analysis of Business Intelligence Impact on Organizational Performance” 2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), Sakheer, Bahrain, 2020, pp. 1-4. (SCOPUS indexed) https://ieeexplore.ieee.org/document/9325610
33. Satheesh Abimannan, Yue-Shan Chang, Chi-Yeh Lin “Air Pollution Forecasting Using LSTM-Multivariate” 2019 IEEE 9th International Symposium on Cloud and Service Computing, 18-21 November 2019, Kaohsiung, Taiwan. IOV 2019, LNCS 11894, pp. 318–326, 2020. (SCOPUS indexed) https://link.springer.com/chapter/10.1007/978-3-030-38651-1_25
34. Chi-Yeh Lin, Yue-Shan Chang, Hsin-Ta Chiao, Satheesh Abimannan “Design a Hybrid Framework for Air Pollution Forecasting” IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2019) 06-09 October, Bari, Italy, IEEE Press, 2472-2477. (SCOPUS indexed) https://ieeexplore.ieee.org/document/8914257
35. Abhishek Vyas, Satheesh Abimannan “Intrusion Detection and Prevention Mechanism Implemented Using NS-2 Based on State Context and Hierarchical Trust in WSNs” 4th International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2019. ICIoTCT 2019. Advances in Intelligent Systems and Computing, vol.1122, pp.229-240, Springer, Cham. (SCOPUS indexed) https://doi.org/10.1007/978-3-030-39875-0_25
36. A Satheesh, D Christy Sujatha, TKS Lakshmipriya, D Kumar, “Cloud Based Virtual Agriculture Marketing and Information System (C-VAMIS)” Emerging ICT for Bridging the Future – Proceedings of the 49th Annual Convention of the Computer Society of India (CSI),Hyderabad, India,337, pp 549-556, 2015.(Springer LNCS). (SCOPUS indexed) https://link.springer.com/chapter/10.1007/978-3-319-13728-5_62
37. D Christy Sujatha, A Satheesh, D Kumar, S Manjula, “Smart Infrastructure at Home using Internet of Things” ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India, Vishakapatnam, India,249, pp 627-634, 2014. (Springer LNCS). (SCOPUS indexed) https://link.springer.com/chapter/10.1007/978-3-319-03095-1_68
38. A. Satheesh, Kumar Durai, Krishnaveni.S “Dynamic Adaptive Self-Configurable Network Processor”, Int. Conference on Ubiquitous Intelligence and Computing (UIC 2010), Xian, China, 26-29,Oct.2010. IEEE Press.pp.No.160-164. (SCOPUS indexed) https://ieeexplore.ieee.org/document/5667209
39. Velu, M., Abimannan, S. (2022). Computational Approaches for Detection and Classification of Crop Diseases. In: Tomar, R., Hina, M.D., Zitouni, R., Ramdane-Cherif, A. (eds) Innovative Trends in Computational Intelligence. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-78284-9_5
40. Satheesh Abimannan, Deepak Kochhar, Yue-Shan Chang, Thirunavukkarasu K, Shanawaz Khan. Evolution of Long Short-term Memory (LSTM) in Air Pollution Forecasting. (2022). Handbook of Research on Machine Learning: Foundations and Applications (1st ed.). Apple Academic Press. https://doi.org/10.1201/9781003277330
41. Abhishek Vyas,and Satheesh Abimannan. “Sensitive Healthcare Data: Privacy and Security Issues and Proposed Solutions” Emerging Technologies for Healthcare, Scrivener Publishing, pp.93-127, 2021, ISBN: 9781119791720 https://doi.org/10.1002/9781119792345.ch4
42. John A, Satheesh Abimannan, El-Sayed M. El-Alfy, Yue-Shan Chang “Spatiotemporal Data Analytics and Modeling: Techniques and Applications” Big Data Book Series, Springer Publications, 2024.  https://link.springer.com/book/10.1007/978-981-99-9651-3