Dr. E. Suganya is an Assistant Professor in the Department of Information Technology at Shiv Nadar University Chennai. She has over 9 years of experience, including 6 years of teaching experience and 3 years of research experience. She obtained her Ph.D. from Anna University, Chennai, specializing in Data Analytics and Optimization.

Her research interests include Artificial Intelligence, Machine Learning and Computer Vision. She has published more than 30 research papers in reputed national and international journals and conference proceedings. One of her research papers received the Best Paper Award at an IEEE International Conference. She is a Life Member of the Indian Society for Technical Education (ISTE).

Work Experience

• Present, Assistant Professor, Shiv Nadar University Chennai
• 2022–2026, Assistant Professor, SSN College of Engineering
• 2015–2018, Assistant Professor, Bannari Amman Institute of Technology

Research Projects

Audio Augmented Reality in Smart Learning Environments (SSN Trust, Completed).

Publications

International Journals

1. K. Anitha, R. Arunadevi, E. Suganya, S. Sountharrajan, “Customized dimetric dimension method for optimized attribute reduction with applications in uncertain clinical information systems,”MethodsX, Volume 17, 2026,
   https://doi.org/10.1016/j.mex.2026.104096.
2. Nivaashini M, Suganya E, Sountharrajan S, (2023).” Hybrid intelligent intrusion detection system for multiple Wi‐Fi attacks in wireless networks using stacked restricted Boltzmann machine and deep belief networks” https://doi.org/10.1002/cpe.7769. (Annexure –I AU, Chennai)
3. M. Karthiga, E. Suganya, S. Sountharrajan, J. Jeyalakshmi, Sindhu Ravindran, Shahrol Mohamaddan, “Optimized Alzheimer disorder classification with DACN-MFFN utilizing OBLDE-TDO enhanced deep neural network features”Biomedical Signal Processing and Control,Volume 106,2025,107729,ISSN 1746-8094,
   https://doi.org/10.1016/j.bspc.2025.107729.
4. Kumar, G.S., Suganya, E., Sountharrajan, S. et al. SRADHO: statistical reduction approach with deep hyper optimization for disease classification using artificial intelligence. Sci Rep 15, 1245 (2025). https://doi.org/10.1038/s41598-024-82838-1.
5. M. Karthiga, S. B. Rahayu, E. Suganya, S. Sankarananth, S. Sountharrajan and K. Venkatesan, “Multimodal Fusion and Cutting-Edge AI-Based Smart Vending Machines for Electronic Component Management,” in IEEE Access, vol. 13, pp. 6029-6053, 2025, doi: 10.1109/ACCESS.2024.3523774.
6. Karthiga, M., Suganya, E., Sountharrajan, S. et al. Eeg based smart emotion recognition using meta heuristic optimization and hybrid deep learning techniques. Sci Rep 14, 30251 (2024). https://doi.org/10.1038/s41598-024-80448-5.
7. Nivaashini, M., Suganya, E., Sountharrajan, S. et al. FEDDBN-IDS: federated deep belief network-based wireless network intrusion detection system. EURASIP J. on Info. Security 2024, 8 (2024). https://doi.org/10.1186/s13635-024-00156-5.
8. S. Sankarananth, M. Karthiga, Suganya E., Sountharrajan S., Durga Prasad Bavirisetti,
   AI-enabled metaheuristic optimization for predictive management of renewable energy production in smart grids,Energy Reports,Volume 10,2023,Pages 1299-1312,ISSN 2352-4847,https://doi.org/10.1016/j.egyr.2023.08.005
9. Pazhaniraja, N., Sountharrajan, S., Suganya, E., & Karthiga, M. (2023). “Optimizing high-utility item mining using hybrid dolphin echolocation and Boolean grey wolf optimization”. Journal of Ambient Intelligence and Humanized Computing, 14(3), 2327-2339. (Annexure –I AU, Chennai)
10. E Suganya, S Sountharrajan.(2023),” Gradient Boost-Modified Classifier with Particle Swarm Optimization and Stochastic Diffusion Search Method for Data Optimization in Wireless Sensor Networks.”45(3-4),193-218. . (Annexure –I AU, Chennai)
11. Sountharrajan, S., Karthiga, M., & Suganya, E. (2022). “Alzheimer’s Dementia: Diagnosis and Prognosis using Neuro-Imaging Analysis”. Journal of Pharmaceutical Negative Results, 13(4), 46-63. (Scopus Indexed)
12. Suganya,E, Rajan C,2020 ‘An Adaboost-Modified Classifier Using Particle Swarm Optimization and Stochastic Diffusion Search in Wireless IoT Networks’, Wireless Networks, Springer. vol. 27, issue no. 4, pp. 2287-2299. Impact factor: 2.659 (SCIE)
13. Nivashini M, Thangaraj P, Sountharrajan S and E Suganya, “Effective Feature Selection for Hybrid Wireless IoT Network Intrusion Detection Systems Using Machine Learning Techniques”, Ad Hoc & Sensor Wireless Networks 49(3-4) p.175-206 , Impact Factor: 1.0.2021
14. Suganya, E., Rajan, C. An AdaBoost-modified classifier using stochastic diffusion search model for data optimization in Internet of Things. Soft Comput 24, 10455–10465 (2020). https://doi.org/10.1007/s00500-019-04554-7
15. Pazhaniraja, N., Sountharrajan, S., Suganya, E., & Karthiga, M. (2021). “Top ‘N’Variant Random Forest Model for High Utility Itemsets Recommendation”. EAI Endorsed Transactions on Energy Web, 8(35), e7-e7. (Scopus Indexed)
16. Karthiga, M., Sountharrajan, S., Suganya, E., & Sankarananth, S. (2021). “Sentence Semantic Similarity Model Using Convolutional Neural Networks”. EAI Endorsed Transactions on Energy Web, 8(35). (Scopus Indexed)
17. Sountharrajan, S., Suganya, E., Karthiga, M., Nandhini, S. S., Vishnupriya, B., & Sathiskumar, B. (2020). “On-the-Go Network Establishment of IoT Devices to Meet the Need of Processing Big Data Using Machine Learning Algorithms”. Business Intelligence for Enterprise Internet of Things, 151-168. (Scopus Indexed)
18. Sountharrajan, S., Nivashini, M., Shandilya, S. K., Suganya, E., Bazila Banu, A., & Karthiga, M. (2020). “Dynamic recognition of phishing URLs using deep learning techniques”. Advances in cyber security analytics and decision systems, 27-56. (Scopus Indexed)
19. Suganya, E., Sountharrajan, S., Shandilya, S. K., & Karthiga, M. (2019). “Mobile cancer prophecy system to assist patients: Big data analysis and design”. Journal of Computational and Theoretical Nanoscience, 16(8), 3623-3628. (Scopus Indexed)
20. Suganya, E., Sountharrajan, S., Shandilya, S. K., & Karthiga, M. (2019). “IoT in agriculture investigation on plant diseases and nutrient level using image analysis techniques”. In Internet of Things in Biomedical Engineering (pp. 117-130). Academic Press. (Scopus Indexed)
21. Sountharrajan, S., Suganya, E., Karthiga, M., & Rajan, C. (2018). “Automatic glioblastoma multiforme detection using hybrid-SVM with improved particle swarm optimisation”. International Journal of Biomedical Engineering and Technology, 26(3-4), 353-364. (Scopus Indexed)
22. Sountharrajan, S., Karthiga, M., Suganya, E., & Rajan, C. (2017). “Automatic classification on bio medical prognosisof invasive breast cancer”. Asian Pacific Journal of Cancer Prevention: APJCP, 18(9), 2541. (Scopus Indexed).
23. Vijayakumar, K, Sountharrajan, S, Suganya, E, 2018, Synthesis, Characterization, and Evaluation of Cancer Prevention Activity of Novel Modified Heterocyclic Compounds’ Asian Pacific Journal of Cancer Prevention, Volume 19, Issue 1, January 2018, Page 247-252. (SCOPUS).
24. E. Suganya, N. Aravindhraj, S. Sountharrajan, G. Sathish Kumar and C. Rajan, 2017,’Automatic Classification for Preventing Duplication of Online Multimedia Data in Secure Cloud Infrastructure’, International Journal of Advanced Intelligence Paradigms.16(3-4):DOI:10.1504/IJAIP.2020.10028402. Inderscience Publishers. (Scopus).
25. Sountharrajan, S, Suganya, E, Aravindhraj, N, and Rajan, C, 2017, ‘HDFS Based Parallel and Scalable Pattern Mining Using Clouds for Incremental Data’, International Journal of Computer Aided Engineering and Technology. DOI: 10.1504/IJCAET.2020.10029059, Inderscience Publishers. (SCOPUS).
26. Sountharrajan, S, Karthiga, M, Suganya, E and Rajan,C, 2017, ‘Automatic Classification on Bio Medical Prognosis of Invasive Breast Cancer’, Asian Pacific Journal of Cancer Prevention, Volume 18, Issue 9, Page 2541-2544.(SCOPUS).
27. Suganya, E, Sountharrajan, S, Archana, M and Rajan,C, 2017, ‘Metaheuristic Optimization Technique for Feature Selection to Detect The Alzheimer Disease From MRI’,International Journal of Advanced research and Dynamic Systems, Pages: 1368-1381.(SCOPUS).

International Conference

1. BlockCred: A Private Blockchain and IPFS-Based Wallet for Academic Credentials Presented by Dr. E. Suganya at the CIMA 2026 – International Conference, organized by the National Institute of Technology (NIT), Puducherry, India, conducted in Hybrid Mode, on 23–24 May 2026.
2. Sangapu Sreenivasa Chakravarthi, Shaik Nagoor Meeravali, Mohammad Aazmi Irfan, S. Sountharrajan, E. Suganya,” Pneumonia Detection using Chest X rays A comprehensive Review”2024 7th International Conference on Computational Intelligence in Data Science (ICCIDS-2024) organized by the Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India held during February 21-23, 2024.
3. Sangapu Sreenivasa Chakravarthi, Rishabh Rajput, Suganya E, S Sountharrajan,” Intrusion Detection System Trends : An Overview of Current Advances in IoV &
   Communication Networks” 2024 7th International Conference on Computational Intelligence in Data Science (ICCIDS-2024) organized by the Department of Computer Science and Engineering, Sri Sivasubramaniya Nadar College of Engineering, Chennai, India held during February 21-23, 2024.
4. Suganya E, “HYBRID BLOCKCHAIN PLATFORM BASED ON DRAGONCHAIN FOR SECURE STORAGE AND SHARING OF ELECTRONIC CLINICAL REPORTS”2024 14th International Conference on Computer Communication and Informatics (ICCI) held during January 29-31, 2024 organized by sri sakthi institute of technology Coimbatore.
5. E. Suganya, “Sparsely Supervised Learning for Medical Image Classification on Noisy Heterogeneous Data,” 2023 3rd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), Greater Noida, India, 2023, pp. 1617-1621, doi: 10.1109/ICACITE57410.2023.10183290.
6. Karthiga, M., Sountharrajan, S., Bazila Banu, A., Sankarananth, S., Suganya, E., & Sathish Kumar, B. (2022). “Similarity Analytics for Semantic Text Using Natural Language Processing”. In 3rd EAI International Conference on Big Data Innovation for Sustainable Cognitive Computing (pp. 239-248). Springer International Publishing. (Scopus Indexed)
7. Karthiga, M., Aravindhraj, N., & Priyanka, S. (2019, April). “Machine learning-based sentiment analysis of Twitter data”. In 2019 International Conference on Advances in Computing and Communication Engineering (ICACCE) (pp. 1-8). IEEE. (Scopus Indexed).
8. Prakhar, K., Sountharrajan, S., Suganya, E., Karthiga, M., & Kumar, S. (2022, April). “Effective Stock Price Prediction using Time Series Forecasting”. In 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI) (pp. 1636-1640). IEEE. (Scopus Indexed)
9. Karthiga, M., Sountharrajan, S., Nandhini, S. S., Suganya, E., & Sankarananth, S. (2021, March). “A Deep Learning Approach to classify the Honeybee Species and health Identification”. In 2021 Seventh International conference on Bio Signals, Images, and Instrumentation (ICBSII) (pp. 1-7). IEEE. (Scopus Indexed)
10. E. Suganya, “Ensemble Learning Solution for the Aspect-based Sentimental Analysis on IMDB reviews,” 2023 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET), Chennai, India, 2023, pp. 01-08, doi: 10.1109/WiSPNET57748.2023.10134144.
11. Sountharrajan S: Karthiga M, Sountharrajan S , E Suganya and B Sathiskumar, “Semantic analytics for Semantic text using Natural Language Processing”, BDCC 2020-EAI International Conference on Big Data Innovation for sustainable Cognitive Computing, Scopus Indexed. 10.1007/978-3-030-78750-9.
12. M Karthiga, S Sountharrajan, SS Nandhini, E Suganya, S Sankarananth, “A Deep Learning Approach to classify the Honeybee Species and health Identification”, 2021 Seventh International conference on Bio Signals, Images, and Instrumentation (ICBSII). 1-7. IEEE. (Scopus).
13. Sagar C Bellad, Ananya Mahapatra, Sahil Dilip Ghule, Satvik Sridhar Shetty, S Sountharrajan, M Karthiga, E Suganya, “Prostate Cancer Prognosis-a comparative approach using Machine Learning Techniques”, 2021 5th International Conference on Intelligent Computing and Control Systems (ICICCS), 1722-1728. IEEE.
14. Suganya, E, and Thiruvenkatasamy, S.’ Distributed Mining Algorithm Using Hadoop on Large Data Set’, International Journal of Advanced Information and Communication Technology, 2014.

Published Patent

Adaptive AR/VR Learning Environment Using Real-Time Object Detection and AI Tutoring (IN202641054428).

Research Interests

• Artificial Intelligence
• Machine Learning
• Deep Learning
• Data Science
• Computer Vision
• AR/VR
• Agentic AI

Research Profiles

• ORCID : 0000-0003-1544-5320
• Scopus ID : 57194427618
• Google Scholar : https://tinyurl.com/GSSuganyaE