Academic Profile

• Ph.D. in Information and Communication Engineering, Anna University, Chennai.

• M.Tech. (Information Technology) from Anna University Coimbatore with First Class and Distinction (9.14 CGPA).

• B.Tech. (Information Technology) from Anna University, Chennai with First Class and Distinction.

Professional Experience

• Professor in Artificial Intelligence and Data Science, Nandha Engineering College, Erode (June 2024 - Present).

• Associate Professor in Computer Science and Engineering, Christ University, Bangalore (June 2023 – May 2024).

• Associate Professor in Information Technology, Kongu Engineering College, Erode (June 2020 – May 2023).

• Assistant Professor in Information Technology, Kongu Engineering College, Erode (June 2011 – May 2020).

• Lecturer in Information Technology, Nandha College of Engineering, Erode (June 2010 – May 2011).

• Lecturer in Information Technology, CSI College of Engineering, The Nilgiris (June 2009 – May 2010).

• Lecturer in Information Technology, CSI College of Engineering, The Nilgiris (May 2005 – August 2007).

SCI Indexed Research Articles

1. Dr.C. Poongodi, Dr.J. Premalatha, D. Vijay Anand, K. Lalitha, "Region-based Find and Spray Scheme for Co-operative Data Communication in Vehicular Cyber-Physical Systems", Intelligent Automation & Soft Computing, Taylor & Francis, 2016, pp.1-7.

2. Lalitha, K, Thangarajan, R, Siba, K, Udgata, Poongodi, D, Ambika Prasad Sahu, "GCCR: An Efficient Grid-Based Clustering and Combinational Routing in Wireless Sensor Networks", Wireless Personal Communications, Vol. 97, Issue. 1, pp. 1075–1095, 2017.

3. Dr. K. Lalitha, Rajesh Kumar Dhanaraj, D. Ganesh Gopal, Thippa Reddy Gadekallu, Mohamed K. Aboudaif, Emad AbouelNasr, "A Heuristic Angular Clustering Framework for Secured Statistical Data Aggregation in Sensor Networks", Sensors Journal, Vol. 20, Issue. 17, pp. 1-15, 2020.

4. Poongodi Chinnasamy, Siba Kumar Udgata, Lalitha K, Jeevanantam A, “Multi-objective based Deployment of Throwboxes in Delay Tolerant Networks for the Internet of Things environment”, Evolutionary Intelligence, Sep.2020. https://doi.org/10.1007/s12065-020-00474-w.

5. Lalitha Krishnasamy, Thangarajan Ramasamy, Rajeshkumar Dhanaraj, Poongodi Chinnasamy, “A Geodesic deployment and radial shaped clustering (RSC) algorithm with statistical aggregation in Sensor Networks”, Turkish Journal of Electrical Engineering and Computer Sciences, vol.29, pp.1464-1478, 2021. 

6. R. K. Dhanaraj, L. Krishnasamy, O. Geman and D. R. Izdrui, "Black hole and sink hole attack detection in wireless body area networks," Computers, Materials & Continua, vol. 68, no.2, pp. 1949–1965, 2021.

7. Dhanaraj, Rajesh Kumar, Lalitha, K., Anitha, S., Khaitan, Supriya, Gupta, Punit| Goyal, Mayank Kumar, “Hybrid and dynamic clustering based data aggregation and routing for wireless sensor networks”, Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10751-10765, 2021.

8. M. D. Ramasamy, K. Periasamy, L. Krishnasamy, R. K. Dhanaraj, S. Kadry and Y. Nam, "Multi-Disease Classification Model using Strassen’s Half of Threshold (SHoT) Training Algorithm in Healthcare Sector," in IEEE Access, doi: 10.1109/ACCESS.2021.3103746.

9. Rajesh Kumar Dhanaraj, Vinothsaravanan Ramakrishnan, M. Poongodi, Lalitha Krishnasamy, Mounir Hamdi, Ketan Kotecha, V. Vijayakumar, "Random Forest Bagging and X-Means Clustered Antipattern Detection from SQL Query Log for Accessing Secure Mobile Data", Wireless Communications and Mobile Computing, vol. 2021, Article ID 2730246, 9 pages, 2021. https://doi.org/10.1155/2021/2730246

10. M. Sathya, M. Jeyaselvi, Lalitha Krishnasamy, Mohammad Mazyad Hazzazi, Prashant Kumar Shukla, Piyush Kumar Shukla, Stephen Jeswinde Nuagah, "A Novel, Efficient, and Secure Anomaly Detection Technique Using DWU-ODBN for IoT-Enabled Multimedia Communication Systems", Wireless Communications and Mobile Computing, vol. 2021, Article ID 4989410, 12 pages, 2021. https://doi.org/10.1155/2021/4989410.

11. Rajesh Kumar Dhanaraj, Rutvij H. Jhaveri, Lalitha Krishnasamy, Gautam Srivastava, Praveen Kumar Reddy Maddikunta, “Black-Hole Attack Mitigation in Medical Sensor Networks Using the Enhanced Gravitational Search Algorithm”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, World Scientific, Vol. 29, Suppl. 2 (December 2021) 297–315. DOI: 10.1142/S021848852140016X

12. Jeyaselvi, M., Dhanaraj, R.K., Sathya, M.,Lalitha Krishnasamy et al. A highly secured intrusion detection system for IoT using EXPSO-STFA feature selection for LAANN to detect attacks. Cluster Comput (2022). https://doi.org/10.1007/s10586-022-03607-1

13. S. Urooj, S. Suchitra, L. Krishnasamy, N. Sharma and N. Pathak, "Stochastic Learning-Based Artificial Neural Network Model for an Automatic Tuberculosis Detection System Using Chest X-Ray Images," in IEEE Access, vol. 10, pp. 103632-103643, 2022, doi: 10.1109/ACCESS.2022.3208882.

14. Suchitra, S., Krishnasamy, L. & Poovaraghan, R.J. A deep learning-based early alzheimer’s disease detection using magnetic resonance images. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-19677-9

Scopus Indexed Research Articles

1. S. Anitha, Dr. P. Jayanthi, Dr. K. Lalitha, V. Chandrasekaran, "Secured Ant Colony Optimization based on Energy Trust System for Replica Node Attack Detection", International Journal on Emerging Technologies, Vol. 11(2), pp. 104-109, 2020.

2. K. Lalitha, Dr. R. Thangarajan, S. Ponni, "Multi-Objective Clustering Technique with Polar Coordinates and Delivery Guarantees in Wireless Sensor Networks", International Journal of Printing, Packaging & Allied Sciences, Vol. 4, No. 1, December 2016, pp. 344 – 351.

3. K. Lalitha, Dr. R. Thangarajan, V. Manju Barkavi, K. Sree Preethi, "Program Length-based Estimated Facts Assembly with Minimal Information Loss in Wireless Sensor Networks", Advanced Computing and Communication Systems (ICACCS), 3rd Int. Conf., IEEE Xplore, October 2016. DOI: 10.1109/ICACCS.2016.7586404.

4. K. Lalitha, Dr. R. Thangarajan, Dr. C. Poongodi, Mr. D. Vijay Anand, "Sink Originated Unique Algorithm for Clustering and Routing to Forward Aggregated Data in Wireless Sensor Networks", Int. Conf. on Intelligent Comm. for Smart World (I2C2SW 2018), December 2018.

5. Lalitha K., Poongodi C., Anitha S., Vijay Anand D. (2021) An Energy-Efficient Routing with Particle Swarm Optimization and Aggregate Data for IOT-Enabled Software-Defined Networks. In: Udgata S.K., Sethi S., Srirama S.N. (eds) Intelligent Systems. Lecture Notes in Networks and Systems, vol 185. Springer, Singapore. https://doi.org/10.1007/978-981-33-6081-5_10

6. Kowshika, P., Mousika, S., Divya, P., Lalitha, K., Jeevanantham, A., Muthukrishnan, H. (2022). Enhancing the Automated Diagnosis System of Soft Tissue Tumors with Machine Learning Techniques. In: Udgata, S.K., Sethi, S., Gao, XZ. (eds) Intelligent Systems. Lecture Notes in Networks and Systems, vol 431. Springer, Singapore. https://doi.org/10.1007/978-981-19-0901-6_48.

7. J. Veneeswari, S. Sankar Ganesh, Lalitha Krishnasamy, T. Rengaraj, D. Suseela, N. Kumaran, “Efficient Brain Tumor Identification Based on Optimal Support Scaling Vector Feature Selection (OSSCV) Using Stochastic Spin-Glass Model  Classification”, International Journal of Intelligent Systems and Applications in  Engineering, vol. 12(11s), pp.177–187, 2024.

8. K. Lalitha, S. Varadhaganapathy, S. Santhoshi and D. R. Kumar, "A Review on Possibilities of Hearing Loss and Implantable Hearing Devices for Teenagers," 2018 4th International Conference on Computing Communication and Automation (ICCCA), 2018, pp. 1-4, doi: 10.1109/CCAA.2018.8777336.

9. Lalitha Krishnasamy, Poongodi Chinnasamy, Anitha S, VijayAnand Duraisamy, “An Energy Efficient Routing with Particle Swarm Optimization and Aggregate Data for IOT enabled Software Defined Networks”, Int. Conf. on Machine Learning, Internet of Things and Big Data (ICMIB 2020), September 2020.

10. K. Lalitha, G. K. Kamalam, R. Priyan, A. S. Rithanya, and P. Shanmugapriya, “Optimizing the sensor deployment strategy for large-scale Internet of Things (IoT) using Artificial Bee Colony”, AIP Conference Proceedings 2387, 140032, 2021. https://doi.org/10.1063/5.0068995

11. T. Abirami, K. Lalitha, P. Jayadharshini, and T. Madhuvanthi, “Future: HCI in public conveyances”, AIP Conference Proceedings 2387, 140042, 2021. https://doi.org/10.1063/5.0069393

12. G. K. Kamalam, K. Lalitha, E. Priyadarshini, V. C. Janani, and P. M. Sasidhar, “Forecasting the spread of COVID-19 using supervised machine learning models”, AIP Conference Proceedings 2387, 140017, 2021. https://doi.org/10.1063/5.0070366

13. J. Arumugam, K. Lalitha, S. M. Supreetha, R. T. Shrinithi and S. Tamilarasan, "Machine Learning For Detecting Twitter Bot," 2022 Fifth International Conference on Computational Intelligence and Communication Technologies (CCICT), 2022, pp. 278-282, doi: 10.1109/CCiCT56684.2022.00059.

14. L. Krishnasamy, R. K. Dhanaraj, M. Gupta, P. Rai, K. Sruthi and G. T, "Detection of diabetic Retinopathy using Retinal Fundus Images," 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 449-455, doi: 10.1109/ICAC3N56670.2022.10074340.

15. L. Krishnasamy, K. Somasundaram, M. Quadir, R. K. Dhanaraj, C. Roopa and K. P, "A Deep Learning Model for Intelligent Energy Management," 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 1307-1311, doi: 10.1109/ICAC3N56670.2022.10074310.

16. Krishnasamy, L., Aparnaa, M., Deepa Prabha, G. and Kavya, T., “Predicting the Thyroid Disease Using Machine Learning Techniques”, Lecture Notes in Network and Systems, 2024, 728 LNNS, pp. 49-57. DOI: 10.1007/978-981-99-3932-9_6

17. Preethi, P., Lalitha, K., Yogapriya, J., “Self-Organizing Computational System for Network Anomaly Exploration using Learning Algorithms”, Journal of Machine and Computing, 2023, 3(4), pp. 431–445

18. Lalitha Krishnasamy, D. Vijay Anand, T. Vigneshwaran, Laxmi Kumari Pathak, Maheswaran S, “An Enhanced Data-Driven Weather Forecasting using Deep Learning Model” , 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), New Delhi.

19. Ramesh M, Maheswaran S, Theivanayaki S, Kodeeswari K, Lalitha Krishnasamy, Sriram N, “Efficient Lung Cancer Classification on Multi level Convolution Neural Network using Histopathological Images”, 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), New Delhi.

20. Lalitha Krishnasamy, Kiruthika M, Manjunatha Swamy C, Vigneshwaran T, Sharon Roji Priya C, D Vijay Anand, “Identification on cyberbullying and finding target user's intension on public forums”, 6th International Conference on Contemporary Computing and Informatics IC3I, Sept. 2023, Amity University, UP, The Greater Noida.

21. G K Kamalam, Nusrat Hamid Shah, Lalitha Krishnasamy, Manjunatha Swamy C, Laxmi Kumari Pathak, P Vanitha, “TSM: A Cloud Computing Task Scheduling Model”, 6th International Conference on Contemporary Computing and Informatics IC3I, Sept. 2023, Amity University, UP, The Greater Noida.

22. G K Kamalam, Lalitha Krishnasamy, Vani Rajasekar, Fathima Kadhoon M, “Comparative Analysis of Maize Leaf Disease Detection using Convolutional Neural Networks”, 2023 IEEE International Conference on ICT in Business Industry & Government (ICTBIG), Dec. 2023.

23.  P.Jayadharshini, Sharon Roji Priya. C, K.Lalitha, S.Santhiya, S.Keerthika, N.Abinaya, “Enhancing Retailer Auctions and Analyzing the Impact of Coupon Offers on Customer Engagement and Sales through Machine Learning”, ICCEBS Dec.2023, Sri Sairam Engineering College, Chennai.

24. Malathy S, Vanitha CN, Rajesh Kumar Dhanaraj and Lalitha Krishnasamy, “Augmented Reality based Medical Education”, ICCEBS Dec.2023, Sri Sairam Engineering College, Chennai.

25. T.Abirami, Shrikant Mapari, P.Jayadharshini, Lalitha Krishnasamy, T.Kavin, V.S.Kanagasubramaniyan, “A Machine Learning Techniques for Early Autism Spectrum Disorder Detection through Comparative Analysis of Feature Engineering and Classification Models”, ICAICCIT-23, IEEE Delhi section, Nov. 2023.

26. S.Santhiya, Shrikant Mapari, N.Abinaya, P.Jayadharshini, S.Priyanka, Lalitha Krishnasamy, “Early Detection of Cervical Cancer using Machine Learning Classifiers for Improved Diagnosis in Underserved Regions”, ICAICCIT-23, IEEE Delhi section, Nov. 2023.

27. T.Abirami, Shrikant Mapari, P.Jayadharshini, Lalitha Krishnasamy, R. Ragavendra Vigneshwaran, “Streamlined Deployment and Monitoring of Cloud-Native Applications on AWS using Kubernetes, Keda, Argocd, Prometheus and Grafana”, ICAICCIT-23, IEEE Delhi section, Nov. 2023.

28. Kiruthika M, Lalitha Krishnasamy, Prithi Samuel, Kaavya Kanagaraj, “FADA: Flooding Attack Defense AODV Protocol to counter Flooding Attack in MANET”, ICAEEC, Sept.2023, REVA University, Bengaluru.

29. Ramesh M, Maheswaran S, Theivanayaki S, Kodeeswari K, Lalitha Krishnasamy, Sriram N, “Efficient Lung Cancer Classification on Multilevel Convolution Neural Network using Histopathological Images”, 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), New Delhi. 

Book Chapter Publications

• Rajesh Kumar D., Rajkumar K., Lalitha K., Dhanakoti V., "Big Data in the Management of Diabetes Mellitus Treatment", in Internet of Things for Healthcare Technologies, Springer, 2021. DOI: 10.1007/978-981-15-4112-4_14.

• C. Poongodi, K. Lalitha, Rajesh Kumar Dhanaraj, "The Role of Blockchains for Medical Electronics Security", in Essential Enterprise Blockchain Concepts and Applications, Auerbach Publications, 2021. DOI: 10.1201/9781003097990.

• K. Lalitha, D. Rajesh Kumar, C. Poongodi, Jeevanantham Arumugam, "Healthcare Internet of Things – The Role of Communication Tools and Technologies", in Blockchain, Internet of Things, and Artificial Intelligence, Chapman and Hall/CRC, 2021. DOI: 10.1201/9780429352898.

• Lalitha Krishnasamy, A. Tamilselvi, Rajesh Kumar Dhanaraj, "An Innovative Outcome of Internet of Things and Artificial Intelligence in Remote Centered Healthcare Application Schemes", Healthcare 4.0, 1st Edition, Chapman and Hall/CRC, 2022.Pages.21.

Books Edited

1. Krishnasamy, L., Dhanaraj, R. K., Balusamy, B., Sabharwal, M., & Chinnasamy, P. (Eds.), "Healthcare 4.0: Health Informatics and Precision Data Management", Chapman and Hall/CRC, 2022. DOI: 10.1201/9781003217435.

Patent Publications

• Title: Smart Stick
  Indian Patent Application No.: 201941016422 A

• Title: Machine Learning-Based System for Prediction of Setup Security Failure of Artificial Lift
  Indian Patent Application No.: 202011004965 A

• Title: Soil Quality Monitoring and Enhancing the Soil Nutrients to Bring Good Quality Crops Using CPS and Machine Learning Techniques
  Patent Application No.: 2020103446

• Title: Automated Wearable Dietary Monitoring Device and Methods of Recommending Diet Thereof
  Indian Patent Application No.: 202141017316 A

• Title: IoT-Based Agricultural Machine for Mixing Chemicals or Fertilizers
  Indian Design Patent Application No.: 391953-001

Consultancy Work

• Project : Safety Module - EHS Report System
  Company : Gilbarco Veeder Root India Private Limited, Coimbatore - 641021

• Project : DTA Automation System Phase-I
  Company : Gilbarco Veeder Root India Private Limited, Coimbatore - 641021

• Project : EHS Online Report System - Safety Module Phase-II
  Company : Gilbarco Veeder Root India Private Limited, Coimbatore - 641021

• Project : MIS Automation Software

Company : Gilbarco Veeder Root India Private limited, Coimbatore- 641021

• Project : Maintenance Spares Management System

Company : Gilbarco Veeder Root India Private limited, Coimbatore- 641021

Professional Society Membership

• Life Member: Indian Society for Technical Education(ISTE), CSI

• IEEE Member