Dr. Ramanujam E

IMG20221216094754

Assistant Professor – Grade II
Department of Computer Science and Engineering
National Institute of Technology Silchar
Assam, India – 788010 
Phone  : +91-97881 53765
Email   : ramanujam[at]cse.nits.ac.in | ramanujamge[at]ieee.org
DOJ      : 14/07/2022
Academic/Industrial Experience: 10+ years
Google Scholar | Publons | Scopus  | DBLP | Vidwan

Academic Qualifications

  • B.E – Computer Science and Engineering – Anna University [2006-2010] – College Topper – Gold Medalist
  • M.E – Computer Science and Engineering – Anna University [2010 – 2012] – University 4th Rank
  • Ph.D – Information and Communication Engineering – Anna University – 2021

Area of Interest and Specialization

  • Machine and Deep Learning 
  • Time Series Mining 
  • Activity Recognition 

Subjects Handled

S.No Course Semester Academic Year
1 CS486- Introduction to Neural Networks and Deep Learning B. Tech – 7 Semester Odd Semester (2022-2023) (2023-2024)
2 CS221 – Programming and Data Structures  B. Tech (EE) – 3 Semester Even Semester (2022-2023)
3 CS5205 – Big Data Analytics and Computing  M.Tech (AI) – 2 Semester Even Semester (2022-2023)
4 CS5302 & CS5243 – Data Science M.Tech (AI & DSE) – 1 Semester Odd Semester (2023-2024)

Journal Publications

  1. Reshmi. S, Ramanujam E., An Ensemble Maximal Feature Subset Selection for Smartphone based Human Activity Recognition, Journal of Network and Computer Application, (Accepted on 05/04/2024) – IF – 8.7 [SCIE]
  2. Ramanujam E, Perumal, T., Shankar, K., A Review on Fall Detection Systems in Bathrooms : Challenges and Opportunities. Multimedia Tools and Applications Jan. 2024, https://doi.org/10.1007/s11042-023-18088-6. [SCIE]
  3. Perumal, T., Ramanujam, E., Suman, S., Sharma, A., & Singhal, H. (2023). Internet of Things Centric-Based Multiactivity Recognition in Smart Home Environment. IEEE Internet of Things Journal, 10(2), 1724–1732. https://doi.org/10.1109/jiot.2022.3209970 [SCIE]
  4. Ramanujam, E., & Padmavathi, S. (2021). Real time fall detection using infrared cameras and reflective tapes under day/night luminance. Journal of Ambient Intelligence and Smart Environments, 13(4), 285–300. https://doi.org/10.3233/ais-210605 [SCIE]
  5. Ramanujam, E., Perumal, T., & Padmavathi, S. (2021). Human Activity Recognition With Smartphone and Wearable Sensors Using Deep Learning Techniques: A Review. IEEE Sensors Journal, 21(12), 13029–13040. https://doi.org/10.1109/jsen.2021.3069927 [SCIE]
  6. Ramanujam. E, Perumal. T & Shankar. K. (2023) Fall Detection Systems at Night, IEEE Computer, vol. 56, no. 06, pp. 44-51, 2023. doi: https://doi.org.10.1109/MC.2022.3200404 [SCIE]
  7. Ramanujam, E., Santhiya, C., & Padmavathi, S. (2022). Day-Level Forecasting of COVID-19 Transmission in India Using Variants of Supervised LSTM Models. Journal of Information Technology Research, 15(1), 1–14. https://doi.org/10.4018/jitr.299376 [ESCI]

Scopus Indexed Publications

  1. Ramanujam, E., & Perumal, T. (2022). MLMO-HSM: Multi-label Multi-output Hybrid Sequential Model for multi-resident smart home activity recognition. Journal of Ambient Intelligence and Humanized Computing, 14(3), 2313–2325. https://doi.org/10.1007/s12652-022-04487-4 
  2. Ramanujam, E., & Padmavathi, S. (2022). Comprehensive review on time series motif discovery using evolutionary techniques. International Journal of Advanced Intelligence Paradigms, 23(1/2), 155. https://doi.org/10.1504/ijaip.2022.125239
  3. Ramanujam, E., Rasikannan, L., & Balasubramanian A. (2022). Coupling of Dimensionality Reduction and Stacking Ensemble Learning for Smartphone-Based Human Activity Recognition. International Journal of E-Services and Mobile Applications, 14(1), 1–15. https://doi.org/10.4018/ijesma.300267
  4. Ramanujam, E., & Perumal, T. (2022). AIFMS Autonomous Intelligent Fall Monitoring System for the Elderly Persons. International Journal of Ambient Computing and Intelligence, 13(1), 1–22. https://doi.org/10.4018/ijaci.304727
  5. Thangavel, C., Thangavel, R., Ramanujam, E., Bennet, D. T., & Bennet, P. S. (2022). Consumer Perception of Internet Banking and Mobile Banking Using Twitter Analytics. International Journal of Sociotechnology and Knowledge Development, 14(1), 1–14. https://doi.org/10.4018/ijskd.297978
  6. Ramanujam, E., Rasikannan L., Anandhalakshmi P. A., & Kamal, N. A. (2021). Xenobots. International Journal of Sociotechnology and Knowledge Development, 14(1), 1–11. https://doi.org/10.4018/ijskd.289038
  7. Ramanujam, E., & Padmavathi, S. (2021). Discriminate Supervised Weighted Scheme for the Classification of Time Series Signals. International Journal of Sociotechnology and Knowledge Development, 13(3), 1–16. https://doi.org/10.4018/ijskd.2021070101
  8. Ramanujam, E., & Padmavathi, S. (2021). Statistical Assessment of Ambient Assistive Techniques by Elders to Enhance Their Well Being From Fall Events. International Journal of Service Science, Management, Engineering, and Technology, 12(4), 164–179. https://doi.org/10.4018/ijssmet.2021070110
  9. Ramanujam, E., Padmavathi, S., & Kamal, N. A. (2021). Recommendation of Pesticide for Roof Top Pest Image Using Convolutional Neural Network Model. International Journal of Sociotechnology and Knowledge Development, 13(1), 38–51. https://doi.org/10.4018/ijskd.2021010104
  10. Ramanujam, E., Sundareswaran, R., Suganya, R., & Kamal, N. A. (2021). Effect of COVID-19 Quarantine Period on a Married Woman With Special Reference to a TIER-II Selected City in India. International Journal of Sociotechnology and Knowledge Development, 13(1), 133–148. https://doi.org/10.4018/ijskd.2021010110
  11. Ramanujam, E., Mayilmurugan, A., & Sundareswaran, R. (2021). Perception and Importance of Urban Home Gardeners to Improve Sustainable Food Production. International Journal of Social Ecology and Sustainable Development, 13(1), 1–15. https://doi.org/10.4018/ijsesd.290312
  12. Ramanujam, E., Padmavathi, S., Baskar, L. A., & Niwin, P. (2021). Ensemble Feature Selection for the Recognition of Human Activities and Postural Transitions on Smartphones. International Journal of Service Science, Management, Engineering, and Technology, 12(5), 80–101. https://doi.org/10.4018/ijssmet.2021090106
  13. Ramanujam, E., & Padmavathi, S. (2019). Genetic time series motif discovery for time series classification. International Journal of Biomedical Engineering and Technology, 31(1), 47. https://doi.org/10.1504/ijbet.2019.101051
  14. Ramanujam, E., & Padmavathi, S. (2016). Multi-objective genetic motif discovery technique for time series classification. International Journal of Business Intelligence and Data Mining, 11(4), 318. https://doi.org/10.1504/ijbidm.2016.082214

Conference Publications

  1. Thirumalai, K.G., Sakthi Prakash K., Abirami, A.M., Ramanujam, E., Sumitra, S., XAI-based Feature Selection for SMS Spam Classification in Dravidian Languages, 5th International Conference on Innovative Trends in Information Technology 2024, organized by the Indian Institute of Information Technology, Kottayam, Kerala. (Accepted for Presentation).
  2. Sakthi Prakash K., Abirami, A.M., Supriya Singh., Ramanujam E. Performance Evaluation of Meta-data features for Spam SMS Classification using Sequential Models, 2024 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS 2024), MANIT Bhopal, February 2024. https://10.1109/sceecs61402.2024.10481874.
  3. Ramanujam, E., Kalimuthu, S., Harshavardhan, B. V., & Perumal, T. (2023, October). Improvement in Multi-resident Activity Recognition System in a Smart Home Using Activity Clustering. In IFIP International Internet of Things Conference (pp. 316-334). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-45878-1_22
  4. Ramanujam, E., Sakthi Prakash K., Abirami, A.M., (2023). Evaluation of Hand-crafted Features for the Classification of Spam SMS in Dravidian Languages, Data Science and Network Engineering: Proceedings of ICDSNE 2023, 791, 3. https://doi.org/10.1007/978-981-99-6755-1_1. 
  5. Ramanujam, E., Shankar, K., Arpit Sharma. (2023). A Review on Artificial Intelligence Techniques for Multilingual SMS Spam detection,  In 3rd International conference on Computer Vision, High Performance Computing, Smart Devices and Networks (CHSN2022), 523-536. https://doi.org/10.1007/978-981-99-6690-5_40 
  6. Ramanujam, E., Chakkaravarthy, G. V., & Lavanya, R. (2022). Hybrid Algorithm for Resource Aware Predictive Scheduling: A case-study to Human Activity Recognition. 2022 International Conference on Knowledge Engineering and Communication Systems (ICKES). https://doi.org/10.1109/ickecs56523.2022.10059785
  7. Ramanujam, E., Shankar, K., & Arpit, S. (2022). Multi-lingual Spam SMS detection using a hybrid deep learning technique. 2022 IEEE Silchar Subsection Conference (SILCON). https://doi.org/10.1109/silcon55242.2022.10028936
  8. Ramanujam, E., Sharma, A., Hussian, J. J., & Perumal, T. (2022). Improving Indoor occupancy estimation using a hybrid CNN-LSTM approach. 2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP). https://doi.org/10.1109/iciccsp53532.2022.9862328
  9. Rasikannan, L., Alli, P., & Ramanujam, E. (2021). Extraction of Opinion Targets and Words from Reviews Using Collective Parallel Cluster Algorithm. Lecture Notes on Data Engineering and Communications Technologies, 363–372. https://doi.org/10.1007/978-981-15-9647-6_28
  10. Ramanujam, E., Chandrakumar, T., Thivyadharsine, K. T., & Varsha, D. (2020). A Multilingual Decision Support System for early detection of Diabetes using Machine Learning approach: Case study for Rural Indian people. 2020 Fifth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN). https://doi.org/10.1109/icrcicn50933.2020.9296187
  11. Ramanujam, E., Padmavathi, S., Dharshani, G., & Madhumitta, M. R. R. (2019). Evaluation of Feature Extraction and Recognition for Human Activity using Smartphone based Accelerometer data. 2019 11th International Conference on Advanced Computing (ICoAC). https://doi.org/10.1109/icoac48765.2019.247124
  12. Rasikannan, L., Alli, P., & Ramanujam, E. (2020). Improved Feature Based Sentiment Analysis for Online Customer Reviews. Lecture Notes on Data Engineering and Communications Technologies, 148–155. https://doi.org/10.1007/978-3-030-38040-3_17
  13. Ramanujam, E., Chandrakumar, T., Nandhana, K., & Laaxmi, N. T. (2020). Prediction of Fetal Distress Using Linear and Non-linear Features of CTG Signals. Advances in Intelligent Systems and Computing, 40–47. https://doi.org/10.1007/978-3-030-37218-7_5
  14. Pudumalar, S., Ramanujam, E., Rajashree, R. H., Kavya, C., Kiruthika, T., & Nisha, J. (2017). Crop recommendation system for precision agriculture. 2016 Eighth International Conference on Advanced Computing (ICoAC). https://doi.org/10.1109/icoac.2017.7951740
  15. Ramanujam, E., & Padmavathi, S. (2016). Double constrained genetic algorithm for ECG signal classification. 2016 International Conference on Emerging Trends in Engineering, Technology and Science (ICETETS). https://doi.org/10.1109/icetets.2016.7603010
  16. Padmavathi, S., & Ramanujam, E. (2015). Naïve Bayes Classifier for ECG Abnormalities Using Multivariate Maximal Time Series Motif. Procedia Computer Science, 47, 222–228. https://doi.org/10.1016/j.procs.2015.03.201
  17. Ramanujam, E., & Padmavathi, S. (2012). Constraint Frequent Motif Detection in sequence datasets. 2012 Fourth International Conference on Advanced Computing (ICoAC). https://doi.org/10.1109/icoac.2012.6416844  

Chapters in Edited Books

  1. Ramanujam, E., Chandrakumar, T., & Sakthipriya, D. (2023). Investigation on Improving the Performance of Class-imbalanced Medical Health Datasets. In Machine Learning for Healthcare Systems (pp. 1-18). River Publishers. https://doi.org/10.1201/9781003438816-1.
  2. Katiyar, S., Kumar, K., Ramanujam, E., Suganya Devi, K., & Naidu, V. N. (2023). Comparative analysis of lumpy skin disease detection using deep learning models. Deep Learning in Medical Image Processing and Analysis, 79–96. https://doi.org/10.1049/pbhe059e_ch5
  3. Ramanujam, E., & Manikandakumar, M. (2022). Mobile Application-based Assistive System for Visually Impaired People: A Hassle-Free Shopping Support System. Object Detection with Deep Learning Models: Principles and Applications. https://doi.org/10.1201/9781003206736-4
  4. Ramanujam, E., Rasikannan, L., Viswa, S., & Prashanth, B. D. (2021). Predictive Strength of Ensemble Machine Learning Algorithms for the Diagnosis of Large Scale Medical Datasets. In Applications of Big Data in Large-and Small-Scale Systems (pp. 260-281). IGI Global.
  5. Ramanujam, E. (2020). The Dark Web: Hidden Access to Internet Today. In Encyclopedia of Criminal Activities and the Deep Web (pp. 129-139). IGI Global.
  6. Ramanujam, E., & Padmavathi, S. (2019). A vision-based posture monitoring system for the elderly using intelligent fall detection technique. Guide to Ambient Intelligence in the IoT Environment: Principles, Technologies and Applications, 249-269.
  7. Ramanujam, E., & Prianga, M. (2019) Side Channel Attacks in Cloud Computing.  In Cognitive Social Mining Applications in Data Analytics and Forensics (pp. 77-98). IGI Global, 2019.
  8. Manikandakumar, M., & Ramanujam, E. (2018). Security and Privacy Challenges in Big Data Environment. In Handbook of Research on Network Forensics and Analysis Techniques (pp. 315-325). IGI Global. 

Dataset

  1. Spam SMS in Dravidian Languages – IEEE Dataport –  https://dx.doi.org/10.21227/dcym-pd69   

Membership in Professional Societies

  • IEEE – Senior Member’ 22
  • Indian Society for Technical Education(ISTE)  – Member(LM93654) [2012- Present]

List of Administrative Responsibilities

S.No Responsibility Date From Date To
1 M.Tech Coordinator May 2023 Till Date
2 Departmental ERP Coordinator November 2022 Till Date
3 Departmental Exam Coordinator  October 2023 Till Date

Session Chair

S.No Conference Organized by Date
3 2022 IEEE Silchar Subsection Conference (SILCON 2022) Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Assam 06-November 2022
2 International Conference on Intelligent Computing Systems and Applications (2022) Department of Computer Science and Engineering, National Institute of Technology Silchar, Assam 23 – September 2022
1 3rd Congress on Intelligent Systems Soft Computing Research Society & Christ University – Bangalore 06-September 2022

Details of PhD Guidance

S.No Name of the Student Status Topic
1 Supriya Singh [Group B – Self Supported] July 2023 –

Workshop Organized

  • Title: Explainable AI : Theoretical Insights and Engineering Applications; Funding Agency: SERB under Karyashala Accelerate Vigyan (AV) Scheme; Duration: 03th-09st July 2023; Cost: Rs. 05 Lakh, Role: Coordinator; Status: Completed

Details of B.Tech Projects

  • “Automated Proctoring System using Deep Learning Techniques” – Keerthi Satya Sai Sundar, Addanki Vamsi Krishna, Kadimi Varun Chandra Sai – July 2023
  • “Deep Learning Technique for Cattle Disease Detection” – Shikhar Katiyar, Krishna Kumar, Vadagana Nagendra Naidu – July 2023 [Published a Book chapter B7]

Details of M.Tech Scholar Guided/ Guiding

  • “Maximal Feature Subset Selection for Smartphone based Human Activity Recognition” – S Reshmi (Published a Journal J7) [Currently working in Philips, Bengaluru] – July 2023

Reviewing Services

  • IEEE Sensors Journal
  • ACM Transactions on Asian and Low-Resource Language Information Processing
  • IEEE Internet of Things Journal
  • Computers in Biology and Medicine, Elsevier
  • Journal of Ambient Intelligence and Humanized Computing, Springer
  • Image Processing, IET
  • Signal Processing, IET
  • Disability and Rehabilitation: Assistive Technology, Taylor and Francis
  • Applied Sciences, Springer Nature
  • Proceedings of the National Academy of Sciences, India Section A: Physical Sciences, Springer
  • International Journal of Pervasive Computing and Communications, Emerald

 Looking for highly motivated UG/PG students to work in the field of Activity Recognition using Deep Learning Techniques – Interested can drop me a mail 

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