Rajdeep Chatterjee
Rajdeep Chatterjee
Associate Professor
Rajdeep Chatterjee received his Bachelor of Engineering in Computer Science and Engineering from The University of Burdwan in 2008. He completed both his Master of Technology and Ph.D. in Computer Science and Engineering from KIIT Deemed to be University in 2011 and 2020, respectively. He received an MHRD (Now, Ministry of Education, Govt. of India) scholarship in his masters for possessing All India Rank 1410 in GATE-2008. He started his professional career as Project Linked Person at Machine Intelligence Unit, Indian Statistical Institute, Kolkata. He is currently working as an Associate Professor at the School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, India. Besides, he is associated as an expert member in the Cognitive Systems and Cybernetics Research Lab., MIU, ISI Kolkata, India. He is also one of the founding members of the international conference series on Computational Intelligence & Networks (http://www.cineconf.org). He has published research articles in many reputed international conferences and journals. He is a regular reviewer of various reputed journals such as Medical & Biological Eng. & Computing (SCI-E, IF: 2.602), IEEE Transactions on Biomedical Engineering (SCI-E, IF: 4.538), IEEE Journal of Biomedical and Health Informatics (SCI-E, IF: 5.223), Computers in Biology and Medicine (SCI-E, IF: 4.589), IEEE Transactions on Emerging Topics in Computational Intelligence (Scopus, IF: 8.28), Evolutionary Intelligence (Scopus, DBLP), etc. His research areas include Brain-Computer Interface, Machine Learning, Deep Learning, and Computer Vision.
Profile Links
Email :
[email protected]
Website :
sites.google.com
Scopus Id :
57189530647
Google Scholar :
https://scholar.google.co.in/citations?user=BozHYf4AAAAJ&hl=en
Social Links
Research Interests
Machine learning, Deep Learning, Computer Vision and Bio-signal Classification
Administrative Responsibility
FIC Industrial Training and Grand Viva
Awards & Honours
Memberships
IEEE, ACM and Indian Science Congress
Machine learning, Deep Learning, Computer Vision and Bio-signal Classification
Administrative Responsibility
FIC Industrial Training and Grand Viva
Awards & Honours
- Delivered a Lecture on "Fuzzy Discernibility Matrix: A Novel Feature Selection Technique" at Oxford Machine Learning Summer School 2021 Unconference Track
- Qualified GATE-2008 with All India Rank 1410 and KIITEE-2009 (M.Tech) with All India Rank 1.
- Invited as a keynote speaker to the 1st International Conference on Cyber Intelligence and Information Retrieval (CIIR 2021), which was held at the Institute of Engineering & Management, Kolkata, West Bengal from 20th-21st May 2021.
Memberships
IEEE, ACM and Indian Science Congress
Journals/Conferences :
Bio-signal Classification:
1. A. Chowdhury, R. Chatterjee, G. Aich and K. Ghosh, "ADHDNet: A DNN based Framework for Efficient ADHD Detection from fMRI Dataset," 9th International Conference on Pattern Recognition and Machine Intelligence (PReMI'21), Lecture Notes in Computer Science, Springer, December 2021, ISI Kolkata, India (Accepted)
2. S. Mazumdar, R. Chatterjee, "Deep Learning Approach for Motor-Imagery Brain States Discrimination Problem," International Conference on Advances in Data Computing, Communication and Security, (I3CS-2021), September 2021, NIT Kurukshetra, India (In press)
3. R. Chatterjee, S. Mazumdar, SR. Sherratt, R. Halder, T. Maitra,D. Giri, "Real-Time Speech Emotion Analysis for Smart Home Assistants," IEEE Transactions on Consumer Electronics 67 (1), pp. 68-76, 2021. DOI:10.1109/TCE.2021.3056421
4. R. Chatterjee, A. Chatterjee, "Orthogonal matching pursuit-based feature selection for motor-imagery EEG signal classification,” International Journal of Computer Applications in Technology, Vol.64 No.4, pp. 403 - 414, 2021. DOI: 10.1504/IJCAT.2020.112686
5. R. Chatterjee, N. B. J. Naskar, D. K. Sanyal, "Cellular Automata-Based Pattern Classifier for Brain-state Discrimination Problem," ICIC Express Letters 14(7), pp. 721-729, May 2020.
6. R. Chatterjee, D. K. Sanyal, A. Datta, and S. Chatterjee, “Diversity Matrix based Performance Improvement for Ensemble Learning Approach,” Book chapter in Hybrid Computational Intelligence: Research and Applications, CRC Press, Taylor and Francis Group, 2019.
7. R. Chatterjee, T. Moitra, SK. H. Islam, M. M. Hassan, A. Alamri, G. Fortino, “A Novel Machine Learning based Feature Selection for Motor-imagery EEG Signal Classification in Internet of Medical Things Environment,” Future Generation Computer Systems, Elsevier, Volume 98, Pages 419-434, 2019. (IF: 5.768)
8. R. Chatterjee, A. Datta and D. K. Sanyal, “Ensemble Learning Approach to Motor- Imagery EEG Signal Classification,” Book chapter in Academic Press (Elsevier) book titled “Machine Learning in Bio-Signal Analysis and Diagnostic Imaging”. (ISBN 978-0-12-816086-2)
9. A. Datta, R. Chatterjee, “Comparative Study of Different Ensemble Composition in EEG Signal Classification Problem,” International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018), Kolkata, India, February 2018.
10. A. Datta, R. Chatterjee, D. Sanyal and D. Guha, “An Ensemble Classification approach to Motor-Imagery Brain State Discrimination Problem,” IEEE International Conference on Infocom Technologies and Unmanned Systems (ICTUS'2017), Dubai, December 2017.
11. R. Chatterjee, T. Bandyopadhyay, D. Sanyal and D. Guha, “Dimensionality Reduction of EEG Signal using Fuzzy Discernibility Matrix,” Proceedings of 10th Human Computer Interaction (HSI 2017), Ulshan, Republic of Korea, July 2017.
12. R. Chatterjee, T. Bandyopadhyay, D. Guha and D. K. Sanyal, “Comparative Analysis of Feature Extraction Techniques in Motor-Imagery EEG Signal Classification,” International Conference on Smart Systems, Innovations and Computing (SSIC 2017), Volume: Springer book series entitled Smart Innovation, Systems and Technologies, April 2017, Jaipur, India.
13. R. Chatterjee, D. Guha, D. K. Sanyal, and S. N. Mohanty, “Discernibility Matrix based Dimensionality Reduction for EEG Signal,” in Region 10 Conference (TENCON), 2016, IEEE, pp. 2703–2706.
14. R. Chatterjee, T. Bandyopadhyay and D. K. Sanyal, “Effects of Wavelets on Quality of Features in Motor-Imagery EEG Signal Classification”, IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2016), March, Chennai.
15. R. Chatterjee, T. Bandyopadhyay, “EEG based Motor Imagery Classification using SVM and MLP”, 2nd International Conference on Computational Intelligence & Networks (CINE 2016), KIIT University, Bhubaneswar, 11th January 2016, proceedings published by IEEE Computer Society, Volume 2, pp 84-85 (DOI- 10.1109/CINE.2016.22) (ISBN- 978-0-7695-5745-7).
Image processing & Computer Vision:
16. R. Chatterjee, A. Chatterjee, and SK, H. Islam ,& Deep Learning Techniques for Observing the Impact of the Global Warming from Satellite Images of Water- Bodies,& Multimedia Tools and Applications, Springer (In Press)
17. R. Chatterjee, A. Chatterjee, SK, H. Islam, and Md. K. Khan ,& An Object Detection-based Few-shot Learning Approach for Multimedia Quality Assessment,& Multimedia Systems, Springer (In Press)
18. R. Chatterjee, S. Roy, S. Roy, & A Siamese Neural Network-based Face Recognition from Masked Faces,& International Conference on Advanced Network Technologies and Intelligent Computing (ANTIC-2021), December 2021, IIT BHU, India (Accepted)
19. R. Chatterjee, S. Roy, SK. H. Islam, & Trident U-Net: An Encoder Fusion for Improved Biomedical Image Segmentation,& In Bioengineering and Biomedical Signal and Image Processing (BIOMESIP-2021), Lecture Notes in Computer Science, vol 12940, pp 141-154. Springer, Spain.
20. K. Chatterjee; M. S. Obaidat; D. Samanta; B. Sadoun; SK H. Islam; R. Chatterjee , "Classification of Soil Images using Convolution Neural Networks, & International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI) , October 2021, Beijing, China
21. R.Chatterjee; S. Roy, SK H. Islam and D. Samanta, & An AI Approach to Pose- based Sports Activity Classification," 8th International Conference on Signal Processing and Integrated Networks (SPIN), August 2021, Noida, India
22. R. Chatterjee, A. Chatterjee, R. Halder, & An Efficient Pneumonia Detection from the Chest X-Ray Images,& In: Prateek M., Singh T.P., Choudhury T., Pandey H.M., Gia Nhu N. (eds) Proceedings of International Conference on Machine Intelligence and Data Science Applications. Algorithms for Intelligent Systems. Springer, Singapore. pp. 779-789, 2021. https://doi.org/10.1007/978-981-33-4087-9_63
23. R. Chatterjee, A. Chatterjee, R. Halder, " Impact of Deep Learning on Arts and Archaeology: An Image Classification Point of View," In: Prateek M., Singh T.P., Choudhury T., Pandey H.M., Gia Nhu N. (eds) Proceedings of International Conference on Machine Intelligence and Data Science Applications. Algorithms for Intelligent Systems. Springer, Singapore. pp. 801-810, 2021. https://doi.org/10.1007/978-981-33-4087-9_65
24. R. Halder, R. Chatterjee, & CNN-BiLSTM Model for Violence Detection in Smart Surveillance,& SN Computer Science 1 (4), pp. 1-9, 2020. https://doi.org/10.1007/s42979-020-00207-x
25. R. Chatterjee, R. Halder, & Discrete Wavelet Transform for CNN-BiLSTM-Based Violence Detection,& Advances in Systems, Control and Automations. Lecture Notes in Electrical Engineering, vol 708. Springer, Singapore. https://doi.org/10.1007/978- 981-15-8685-9_4
26. R. Chatterjee and R. Haldar, & Deep Ensemble Learning-based Smart Teaching ,& IndiaRxiv, March 2020. doi:10.35543/osf.io/re94u.
27. R. Chatterjee and R. Haldar, & Discrete Wavelet Transform for CNN-BiLSTM- based Violence Detection ," The 2nd International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy(ETAEERE-2020) , March 2020.
28. R. Haldar, R. Chatterjee, D. K. Sanyal, P. K. Mallick, & Deep Learning based Smart Attendance Monitoring System," Global AI Congress (GAIC 2019), September 2019.
29. R. Chatterjee, Alenrex Maity and R. Chatterjee, “Image Compression Using VQ for Lossy Compression,” International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018), Kolkata, India, February 2018.
Data & Knowledge Engineering:
30. R. Palit, R. Chatterjee, "Recommender System using K-Nearest Neighbors and Singular Value Decomposition Algorithms: A Hybrid Approach," The 2nd International Conference on Computing Analytics and Networking (ICCAN 2019), Bhubaneswar, India, December 2019.
31. D. K. Sanyal, S. Chattopadhayay and R. Chatterjee “Figure Retrieval from Biomedical Literature: An Overview of Techniques, Tools, and Challenges,” Book chapter in Machine Learning in Bio-Signal Analysis and Diagnostic Imaging, Academic Press, Elsevier, pp. 247-268, 2018.
32. A. Dewangan, R. Chatterjee, “Tourism Recommendation by Machine Learning Approach”, International Conference on Advanced Computing and Intelligent Engineering (ICACIE 2016), Springer (AISC), At C.V. Raman College of Engineering, Bhubaneswar, Odisha, India.
33. S. Sen, R. Chatterjee, “Estimation of Incomplete Data in Mixed Dataset”, 4th International Conference on. Advanced Computing, Networking, and Informatics (ICACNI – 2016), At National Institute of Technology Rourkela.
34. S. Sen, R. Chatterjee, “A Weighted k-NN Approach to Estimate Missing Values”, 3rd IEEE International Conference on Signal Processing & Integrated Networks (SPIN 2016), February, Noida.
35. S. Dey, B. Jana, M. K. Gourisaria, S. Mohanty and R. Chatterjee, “Evaluation of Indian B2C E-Shopping Websites under Multi Criteria Decision-Making using Fuzzy Hybrid Technique”, International Journal of Applied Engineering Research, August 2015.
36. A. Roy, R. Chatterjee, “Realizing New Hybrid Rough Fuzzy Association Rule Mining Algorithm (RFA) Over Apriori Algorithm”, Intelligent Computing, Communication and Devices, Springer Book Series on Advances in Intelligent Systems and Computing 2015, Proceedings of ICCD 2014, Volume 1, pp 157-167 (DOI- 10.1007/978-81-322-20121_17).
37. A. Roy, R. Chatterjee, “Introducing New Hybrid Rough Fuzzy Association Rule Mining Algorithm”, 21st-22nd March 2014, Recent Trends in Information Technology, Association of Computer Electronics and Electrical Engineers, Proceedings of Fifth International Conference on Recent Trends in Information, Telecommunication and Computing – ITC 2014, Chandigarh, India. (DOI- 02.ITC.2014.5.101, ISBN- 978-94-91587-21-3)
38. A. Roy, R. Chatterjee, “A Review on Fuzzy Association Rule Mining Algorithm”, Nov.– Dec. 2013, Vol. 15, Issue 6, pp 01-08, IOSR Journal of Computer Engineering (IOSRJCE) (e-ISSN: 2278-0661, p-ISSN: 2278-8719).
Blockchain:
39. S. K. Pani, R. Chatterjee and N. R. Mahapatra, “Towards Trusted, Transparent and Motivational Professional Education System Through Blockchain,” International Journal of Information Systems and Social Change, IGI Global, Volume 10, Issue 2, April-June 2019.
40. Rishav Chatterjee and Rajdeep Chatterjee, “An Overview of the Emerging Technology: Blockchain,” International Conference on Computational Intelligence and Networks (CINE 2017), Bhubaneswar, India, October 2017.
Optimization Techniques:
41. R. Chatterjee, M. N. Das, “A Novel Physics Inspired Multi-objective Optimization Algorithm: Multiple Objective Gravitational Optimization”, International Conference on Computational Intelligence & Networks (CINE 2015), KIIT University, Bhubaneswar, 12th -13th January 2015, proceedings published by IEEE Computer Society, Volume 1, pp 32-35 (DOI- 10.1109/CINE.2015.16) (ISBN- 978-1-4799-7549-5).
42. R. Chatterjee, M. N. Das, “Physics Inspired Optimization Algorithms Introducing New Hybrid Gravitational Differential Evolution and Gravitational Search Algorithm with mutation”, International Symposium on Devices, MEMS, Intelligent System & Communication System (ISDMISC 2011), SMIT, Majitar-737136, Rangpo, East Sikkim, India. (ISSN 0975-8887)
Control & Intelligent Systems:
43. D. Mukherjee, R. Chatterjee, “A Better Performance Analysis of Robust Fuzzy PI Controller With a Conventional Tuning Method and Its Performance Evaluation on a Servo Position Control System”, Second Michael Faraday IET India Summit 2013: An IET Conference (MFIIS -2013), 17-18 November 2013.
44. S. Bandyopadhyay, D. Mukherjee, and R. Chatterjee, " Design of two stage cmos operational amplifier in 180nm technology with low power and high cmrr ," International Journal on Recent Trends in Engineering & Technology, Association of Computer Electronics and Electrical Engineers (ACEEE)
Bio-signal Classification:
1. A. Chowdhury, R. Chatterjee, G. Aich and K. Ghosh, "ADHDNet: A DNN based Framework for Efficient ADHD Detection from fMRI Dataset," 9th International Conference on Pattern Recognition and Machine Intelligence (PReMI'21), Lecture Notes in Computer Science, Springer, December 2021, ISI Kolkata, India (Accepted)
2. S. Mazumdar, R. Chatterjee, "Deep Learning Approach for Motor-Imagery Brain States Discrimination Problem," International Conference on Advances in Data Computing, Communication and Security, (I3CS-2021), September 2021, NIT Kurukshetra, India (In press)
3. R. Chatterjee, S. Mazumdar, SR. Sherratt, R. Halder, T. Maitra,D. Giri, "Real-Time Speech Emotion Analysis for Smart Home Assistants," IEEE Transactions on Consumer Electronics 67 (1), pp. 68-76, 2021. DOI:10.1109/TCE.2021.3056421
4. R. Chatterjee, A. Chatterjee, "Orthogonal matching pursuit-based feature selection for motor-imagery EEG signal classification,” International Journal of Computer Applications in Technology, Vol.64 No.4, pp. 403 - 414, 2021. DOI: 10.1504/IJCAT.2020.112686
5. R. Chatterjee, N. B. J. Naskar, D. K. Sanyal, "Cellular Automata-Based Pattern Classifier for Brain-state Discrimination Problem," ICIC Express Letters 14(7), pp. 721-729, May 2020.
6. R. Chatterjee, D. K. Sanyal, A. Datta, and S. Chatterjee, “Diversity Matrix based Performance Improvement for Ensemble Learning Approach,” Book chapter in Hybrid Computational Intelligence: Research and Applications, CRC Press, Taylor and Francis Group, 2019.
7. R. Chatterjee, T. Moitra, SK. H. Islam, M. M. Hassan, A. Alamri, G. Fortino, “A Novel Machine Learning based Feature Selection for Motor-imagery EEG Signal Classification in Internet of Medical Things Environment,” Future Generation Computer Systems, Elsevier, Volume 98, Pages 419-434, 2019. (IF: 5.768)
8. R. Chatterjee, A. Datta and D. K. Sanyal, “Ensemble Learning Approach to Motor- Imagery EEG Signal Classification,” Book chapter in Academic Press (Elsevier) book titled “Machine Learning in Bio-Signal Analysis and Diagnostic Imaging”. (ISBN 978-0-12-816086-2)
9. A. Datta, R. Chatterjee, “Comparative Study of Different Ensemble Composition in EEG Signal Classification Problem,” International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018), Kolkata, India, February 2018.
10. A. Datta, R. Chatterjee, D. Sanyal and D. Guha, “An Ensemble Classification approach to Motor-Imagery Brain State Discrimination Problem,” IEEE International Conference on Infocom Technologies and Unmanned Systems (ICTUS'2017), Dubai, December 2017.
11. R. Chatterjee, T. Bandyopadhyay, D. Sanyal and D. Guha, “Dimensionality Reduction of EEG Signal using Fuzzy Discernibility Matrix,” Proceedings of 10th Human Computer Interaction (HSI 2017), Ulshan, Republic of Korea, July 2017.
12. R. Chatterjee, T. Bandyopadhyay, D. Guha and D. K. Sanyal, “Comparative Analysis of Feature Extraction Techniques in Motor-Imagery EEG Signal Classification,” International Conference on Smart Systems, Innovations and Computing (SSIC 2017), Volume: Springer book series entitled Smart Innovation, Systems and Technologies, April 2017, Jaipur, India.
13. R. Chatterjee, D. Guha, D. K. Sanyal, and S. N. Mohanty, “Discernibility Matrix based Dimensionality Reduction for EEG Signal,” in Region 10 Conference (TENCON), 2016, IEEE, pp. 2703–2706.
14. R. Chatterjee, T. Bandyopadhyay and D. K. Sanyal, “Effects of Wavelets on Quality of Features in Motor-Imagery EEG Signal Classification”, IEEE International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET 2016), March, Chennai.
15. R. Chatterjee, T. Bandyopadhyay, “EEG based Motor Imagery Classification using SVM and MLP”, 2nd International Conference on Computational Intelligence & Networks (CINE 2016), KIIT University, Bhubaneswar, 11th January 2016, proceedings published by IEEE Computer Society, Volume 2, pp 84-85 (DOI- 10.1109/CINE.2016.22) (ISBN- 978-0-7695-5745-7).
Image processing & Computer Vision:
16. R. Chatterjee, A. Chatterjee, and SK, H. Islam ,& Deep Learning Techniques for Observing the Impact of the Global Warming from Satellite Images of Water- Bodies,& Multimedia Tools and Applications, Springer (In Press)
17. R. Chatterjee, A. Chatterjee, SK, H. Islam, and Md. K. Khan ,& An Object Detection-based Few-shot Learning Approach for Multimedia Quality Assessment,& Multimedia Systems, Springer (In Press)
18. R. Chatterjee, S. Roy, S. Roy, & A Siamese Neural Network-based Face Recognition from Masked Faces,& International Conference on Advanced Network Technologies and Intelligent Computing (ANTIC-2021), December 2021, IIT BHU, India (Accepted)
19. R. Chatterjee, S. Roy, SK. H. Islam, & Trident U-Net: An Encoder Fusion for Improved Biomedical Image Segmentation,& In Bioengineering and Biomedical Signal and Image Processing (BIOMESIP-2021), Lecture Notes in Computer Science, vol 12940, pp 141-154. Springer, Spain.
20. K. Chatterjee; M. S. Obaidat; D. Samanta; B. Sadoun; SK H. Islam; R. Chatterjee , "Classification of Soil Images using Convolution Neural Networks, & International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI) , October 2021, Beijing, China
21. R.Chatterjee; S. Roy, SK H. Islam and D. Samanta, & An AI Approach to Pose- based Sports Activity Classification," 8th International Conference on Signal Processing and Integrated Networks (SPIN), August 2021, Noida, India
22. R. Chatterjee, A. Chatterjee, R. Halder, & An Efficient Pneumonia Detection from the Chest X-Ray Images,& In: Prateek M., Singh T.P., Choudhury T., Pandey H.M., Gia Nhu N. (eds) Proceedings of International Conference on Machine Intelligence and Data Science Applications. Algorithms for Intelligent Systems. Springer, Singapore. pp. 779-789, 2021. https://doi.org/10.1007/978-981-33-4087-9_63
23. R. Chatterjee, A. Chatterjee, R. Halder, " Impact of Deep Learning on Arts and Archaeology: An Image Classification Point of View," In: Prateek M., Singh T.P., Choudhury T., Pandey H.M., Gia Nhu N. (eds) Proceedings of International Conference on Machine Intelligence and Data Science Applications. Algorithms for Intelligent Systems. Springer, Singapore. pp. 801-810, 2021. https://doi.org/10.1007/978-981-33-4087-9_65
24. R. Halder, R. Chatterjee, & CNN-BiLSTM Model for Violence Detection in Smart Surveillance,& SN Computer Science 1 (4), pp. 1-9, 2020. https://doi.org/10.1007/s42979-020-00207-x
25. R. Chatterjee, R. Halder, & Discrete Wavelet Transform for CNN-BiLSTM-Based Violence Detection,& Advances in Systems, Control and Automations. Lecture Notes in Electrical Engineering, vol 708. Springer, Singapore. https://doi.org/10.1007/978- 981-15-8685-9_4
26. R. Chatterjee and R. Haldar, & Deep Ensemble Learning-based Smart Teaching ,& IndiaRxiv, March 2020. doi:10.35543/osf.io/re94u.
27. R. Chatterjee and R. Haldar, & Discrete Wavelet Transform for CNN-BiLSTM- based Violence Detection ," The 2nd International Conference on Emerging Trends and Advances in Electrical Engineering and Renewable Energy(ETAEERE-2020) , March 2020.
28. R. Haldar, R. Chatterjee, D. K. Sanyal, P. K. Mallick, & Deep Learning based Smart Attendance Monitoring System," Global AI Congress (GAIC 2019), September 2019.
29. R. Chatterjee, Alenrex Maity and R. Chatterjee, “Image Compression Using VQ for Lossy Compression,” International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018), Kolkata, India, February 2018.
Data & Knowledge Engineering:
30. R. Palit, R. Chatterjee, "Recommender System using K-Nearest Neighbors and Singular Value Decomposition Algorithms: A Hybrid Approach," The 2nd International Conference on Computing Analytics and Networking (ICCAN 2019), Bhubaneswar, India, December 2019.
31. D. K. Sanyal, S. Chattopadhayay and R. Chatterjee “Figure Retrieval from Biomedical Literature: An Overview of Techniques, Tools, and Challenges,” Book chapter in Machine Learning in Bio-Signal Analysis and Diagnostic Imaging, Academic Press, Elsevier, pp. 247-268, 2018.
32. A. Dewangan, R. Chatterjee, “Tourism Recommendation by Machine Learning Approach”, International Conference on Advanced Computing and Intelligent Engineering (ICACIE 2016), Springer (AISC), At C.V. Raman College of Engineering, Bhubaneswar, Odisha, India.
33. S. Sen, R. Chatterjee, “Estimation of Incomplete Data in Mixed Dataset”, 4th International Conference on. Advanced Computing, Networking, and Informatics (ICACNI – 2016), At National Institute of Technology Rourkela.
34. S. Sen, R. Chatterjee, “A Weighted k-NN Approach to Estimate Missing Values”, 3rd IEEE International Conference on Signal Processing & Integrated Networks (SPIN 2016), February, Noida.
35. S. Dey, B. Jana, M. K. Gourisaria, S. Mohanty and R. Chatterjee, “Evaluation of Indian B2C E-Shopping Websites under Multi Criteria Decision-Making using Fuzzy Hybrid Technique”, International Journal of Applied Engineering Research, August 2015.
36. A. Roy, R. Chatterjee, “Realizing New Hybrid Rough Fuzzy Association Rule Mining Algorithm (RFA) Over Apriori Algorithm”, Intelligent Computing, Communication and Devices, Springer Book Series on Advances in Intelligent Systems and Computing 2015, Proceedings of ICCD 2014, Volume 1, pp 157-167 (DOI- 10.1007/978-81-322-20121_17).
37. A. Roy, R. Chatterjee, “Introducing New Hybrid Rough Fuzzy Association Rule Mining Algorithm”, 21st-22nd March 2014, Recent Trends in Information Technology, Association of Computer Electronics and Electrical Engineers, Proceedings of Fifth International Conference on Recent Trends in Information, Telecommunication and Computing – ITC 2014, Chandigarh, India. (DOI- 02.ITC.2014.5.101, ISBN- 978-94-91587-21-3)
38. A. Roy, R. Chatterjee, “A Review on Fuzzy Association Rule Mining Algorithm”, Nov.– Dec. 2013, Vol. 15, Issue 6, pp 01-08, IOSR Journal of Computer Engineering (IOSRJCE) (e-ISSN: 2278-0661, p-ISSN: 2278-8719).
Blockchain:
39. S. K. Pani, R. Chatterjee and N. R. Mahapatra, “Towards Trusted, Transparent and Motivational Professional Education System Through Blockchain,” International Journal of Information Systems and Social Change, IGI Global, Volume 10, Issue 2, April-June 2019.
40. Rishav Chatterjee and Rajdeep Chatterjee, “An Overview of the Emerging Technology: Blockchain,” International Conference on Computational Intelligence and Networks (CINE 2017), Bhubaneswar, India, October 2017.
Optimization Techniques:
41. R. Chatterjee, M. N. Das, “A Novel Physics Inspired Multi-objective Optimization Algorithm: Multiple Objective Gravitational Optimization”, International Conference on Computational Intelligence & Networks (CINE 2015), KIIT University, Bhubaneswar, 12th -13th January 2015, proceedings published by IEEE Computer Society, Volume 1, pp 32-35 (DOI- 10.1109/CINE.2015.16) (ISBN- 978-1-4799-7549-5).
42. R. Chatterjee, M. N. Das, “Physics Inspired Optimization Algorithms Introducing New Hybrid Gravitational Differential Evolution and Gravitational Search Algorithm with mutation”, International Symposium on Devices, MEMS, Intelligent System & Communication System (ISDMISC 2011), SMIT, Majitar-737136, Rangpo, East Sikkim, India. (ISSN 0975-8887)
Control & Intelligent Systems:
43. D. Mukherjee, R. Chatterjee, “A Better Performance Analysis of Robust Fuzzy PI Controller With a Conventional Tuning Method and Its Performance Evaluation on a Servo Position Control System”, Second Michael Faraday IET India Summit 2013: An IET Conference (MFIIS -2013), 17-18 November 2013.
44. S. Bandyopadhyay, D. Mukherjee, and R. Chatterjee, " Design of two stage cmos operational amplifier in 180nm technology with low power and high cmrr ," International Journal on Recent Trends in Engineering & Technology, Association of Computer Electronics and Electrical Engineers (ACEEE)