Multimedia and Image Processing Lab

Dr. Badal Soni

Assistant Professor, CSE, NIT Silchar.

Phone: +91 96785 47361

Email: badal@cse.nits.ac.in

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Biography: Badal Soni (Senior Member, IEEE) is currently working as an Assistant Professor at the Department of Computer Science & Engineering, National Institute of Technology (NIT) Silchar, Assam, India. He has completed his B.Tech from Rajiv Gandhi Technical University (formerly RGPV) in Bhopal, India and M. Tech from the Indian Institute of Information Technology, Design and Manufacturing (IIITDM), Jabalpur, India. He has done his PhD in Computer Science & Engineering Under MoU with NIT Silchar and Indian Institute of Technology (IIT) Guwahati, Assam, India. He has teaching experience of over 10 years in the area of computer science and information technology with a special interest in Image Processing, Machine Learning and Language Processing. He has published 60 publications in refereed journals and contributed books and international conference proceedings. He is a Senior Member of IEEE and a professional member of various bodies like IEEE, ACM, IAENG and IACSIT. His research interest includes Image Processing, Medical Image Processing, Machine Learning Applications, Fake News Detection and Human Activity Recognition.

Candy Lalrempuii

PhD Topic: Machine Translation

Email: candylalrempuii@gmail.com

Biography: Candy Lalrempuii completed her B.E degree in Computer Science and Engineering from Coimbatore Institute of Technology (CIT), Coimbatore, India and the M.Tech degree from Malaviya National Institute of Technology (MNIT), Jaipur, India. She is currently pursuing her PhD degree in Computer Science and Engineering at the National Institute of Technology (NIT) Silchar, Assam, India. Her current research interests include Natural Language Processing, Machine Translation, Artificial Intelligence.

Publications:

1. Candy Lalrempuii, Badal Soni and Partha Pakray “An Improved English to Mizo Neural Machine Translation", In: ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), 20, 4, Article 61 (July 2021)
2. Candy Lalrempuii, Badal Soni "Attention-based English to Mizo Neural Machine Translation", In: International Conference on Machine Learning, Image Processing, Network Security and Data Sciences 2020, Communications in Computer and Information Science, vol 1241. Springer, Singapore.
3. Candy Lalrempuii and Badal Soni "Low Resource Indic Languages Translation using Multilingual Approaches" In: 3rd International Conference on Computer Vision, High Performance Computing, Smart Devices and Networks (CHSN 2022). (Accepted)
4. Candy Lalrempuii and Badal Soni “Improving Unsupervised Neural Machine Translation for Low- resource Language pair English-Mizo via Lexically-enhanced Pre-trained Language Models", In: ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP). (Major Revision as on 12-11-2022)

Arpita Ghosh

PhD Topic: Medical Image Processing

Email: arpita5102_rs@cse.nits.ac.in

Biography: Arpita Ghosh has done B.tech from Tripura Institute of Technology and M.tech from Vellore Institute of Technology, Vellore in the year 2016 and 2018 respectively. Currently she is working as a full time research scholar at National Institute of Technology, Silchar. Her current research interests include Medical Image classification and segmentation, Transfer learning and Deep Learning algorithms.

Publications:

1. Arpita Ghosh and Badal Soni (2021)”An Automatic Tumor Identification Process to Classify MRI Brain Images”, In: Verma G.K., Soni B., Bourennane S., Ramos A.C.B. (eds) Data Science. Transactions on Computer Systems and Networks. Springer, Singapore.
2. Arpita Ghosh, Badal Soni, Ujwala Baruah, and R. Murugan, “Classification of Brain Hemorrhage using Fine Tuned Transfer Learning”, Advanced Machine Intelligence and Signal Processing. Lecture Notes in Electrical Engineering, vol 858. Springer, Singapore.
3. Arpita Ghosh, Badal Soni, Ujwala Baruah, “Brain Hemorrhage Classification from CT Scan Images using Fine-tuned Transfer Learning Deep Features” Published in International Journal of Business Intelligence and Data Mining, Inderscience, 2022,
4. Arpita Ghosh, Badal Soni, Ujwala Baruah, “Brain Hemorrhage Classification using Leaky ReLU based Transfer Learning Approach”, International Conference on Advances in Data-driven Computing and Intelligent Systems (ADCIS 2022). (Accepted and Presented).
5. Arpita Ghosh, Badal Soni, Ujwala Baruah, “Leaky ReLU based Transfer Learning Strategy for Brain Hemorrhage Classification”, Journal of Supercomputing, Springer. (Submitted).

Eduri Raja

Research Topic: Fake News Detection

Email: eduri_rs@cse.nits.ac.in

Publications:

1. Raja Eduri, Badal Soni, Shivangi Mishra, and Ashish Dwivedi. "Stand-Alone Bidirectional Encoder Representations from Transformer-Based Fake News Detection Model." In Proceedings of the International Conference on Computational Intelligence and Sustainable Technologies, pp. 647-655. Springer, Singapore, 2022.
2. Eduri Raja, Badal Soni and Samir Kumar Borgohain, “Fake News Detection in Dravidian Languages using Transformer Models”, in Proceedings of Springer 3rd International Conference on Computer Vision, High-Performance Computing, Smart Devices and Networks (CHSN-2022). (Accepted)

Nurul Amin Choudhury

Research Topic: Human Activity Recognition

Email: nurul21_rs@cse.nits.ac.in

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Biography: Nurul Amin Choudhury received the B. Tech degree in Computer Science and Engineering from the Jawaharlal Nehru Technological University Hyderabad, India and the M.Tech degree from the National Institute of Technology (NIT) Meghalaya, India in the year 2018 and 2021, respectively. Currently, he is working towards his PhD degree in Computer Science and Engineering at the National Institute of Technology (NIT) Silchar, Assam, India. His current research interests include Human Activity Recognition, Gait Recognition, Machine Learning and Deep Learning Applications, AI-IoT in Healthcare and Smart Learning algorithms.

Publications:

1. N. A. Choudhury and B. Soni, "An Adaptive Batch Size based-CNN-LSTM Framework for Human Activity Recognition in Uncontrolled Environment," in IEEE Transactions on Industrial Informatics.
2. N. A. Choudhury and B. Soni, "An Efficient CNN-LSTM Approach for Smartphone Sensor-Based Human Activity Recognition System," 2022 5th International Conference on Computational Intelligence and Networks (CINE), Bhubaneswar, India, 2022, pp. 01-06.
3. N. A. Choudhury, B. Soni, "Effect of Shallow and Ensemble Learning Models for Human Activity Recognition in Uncontrolled Environment" in IEEE 17th India Council International Conference - INDICON 2022,, Kerala - Accepted and Presented (03-12-2022).
4. N. A. Choudhury, B. Soni, S. Moulik, “HAR-DIFS: Data Intensity-based Feature Selection for Wearable Sensor-based Human Activity Recognition System”, in IEEE Transactions on Human-Machine Systems – Under Review (As of 15-01-2023).
5. N. A. Choudhury, B. Soni, "In-depth Analysis of Sensor-based Human Activity Recognition Systems", in Springer Multimedia Tools and Applications - Under Review (As of 17-12-2022).