Ph.D.: National Institute of Technology, Arunachal Pradesh, January 2026
PG: CSE, Indian Institute of Engineering Science and Technology, Shibpur, 2017
UG: Maulana Abul Kalam Azad University of Technology, 2015
Teaching Experience: 06 years 02 months
Research Experience: 03 years 01 months
Industry Experience: 06 months
Contact Number:
BVRITN Employee ID: BVRIT01034
JNTUH Registration ID: 3403-220223-142100
AICTE Registration ID: 1-11275181108
Ratified by JNTUH: Yes
SCOPUS ID: https://www.scopus.com/authid/detail.uri?authorId=58264924900
ORCID ID: https://orcid.org/0000-0003-2015-7251
Vidwan ID: https://vidwan.inflibnet.ac.in/profile/271078
Web of Science (WOS) ID:
- Deep Learning
- Bioinformatics
- Python
- Machine Learning,
- Data Structure &Algorithm,
- Operating System
- Wipro Certified Faculty (WCF) in Java Full Stack, TalentNext.
- Certified in “Introduction to the Internet of Things and Embedded Systems” for Data Science authorized by University of California, Irvine and offered through Coursera.
- Certified in “Machine Learning Introduction for Everyone’ authorized by IBM and offered through Coursera.
- Certified in “Python for Data Science, AI & Development’ an online course authorized by IBM and offered through Coursera.
- GATE Score: 507 (2015)
- NPTEL Certification:
- Deep Learning
SCIE/Scopus:
- Das, S., Goswami, R.S. ARU-Net: a U-Net variant with attention and residual blocks for automated MRI brain tumor segmentation. Pattern Anal Applic 29, 27 (2026). https://doi.org/10.1007/s10044-026-01609-y [SCIE]
- Surajit Das, Rajat Subhra Goswami, Addressing challenges in accurate brain tumor classification in MRI: a transfer learning approach with EfficientNetB3 and comprehensive model evaluation. Multimedia Tools and Applications (2024). https://doi.org/10.1007/s11042-024-20366-w [Impact Factor: 3.6, SJR: 0.72, Q1 Journal]
- Surajit Das, Rajat Subhra Goswami, “Review, Limitations, and future prospects of neural network approaches for brain tumor classification” Journal: Multimedia Tools and Applications, 2023 https://doi.org/10.1007/s11042-023-17215-7 [Impact Factor: 3.6, SJR: 0.72, Q1 Journal]
- Surajit Das, Rajat Subhra Goswami “Advancements in brain tumor analysis: a comprehensive review of machine learning, hybrid deep learning, and transfer learning approaches for MRI-based classification and segmentation. Multimedia Tools and Applications (2024). https://doi.org/10.1007/s11042-024-20203-0 [ Impact Factor: 3.6, SJR: 0.72, Q1 Journal]
- Prasenjit Chatterjee, Abhijit Saha, Bijoy Krishna Debnath, Annapurani K Panaiyappan, Surajit Das, Gogineni Anusha, “Generalized Dombi-based probabilistic hesitant fuzzy consensus reaching model for supplier selection under healthcare supply chain framework”. Journal: Engineering Applications of Artificial Intelligence (2024), https://doi.org/10.1016/j.engappai.2024.10 7966, [Indexed: SCIE, Impact Factor: 8, SJR: 1.73, Q1].
- P. Chatterjee, S. Das, and S. Samanta, “Multi-Branch Deep Learning Architecture for Improved Colposcopy Image Classification,” Scientific Reports (Springer Nature), SCIE-indexed journal, (Accepted), 2026.
Patents:
- Indian Patent. Application number- 202341088828, “A deep learning based automated cybersecurity system and method thereof”, January 19, 2024. Application status -published
- Indian Patent, APPLICATION NUMBER- 202441081759, “A Novel Approach in Masking of Colposcopy Images”, 01/11/2024. Application status -published
- Indian patent, application number- 202541125236, “ semi-automated brain tumor segmentation using thresholding and morphological processing with real-time opencv gui-control”, application status -published.
- Application number-202541125238, title of invention-an approach to secure decentralized storage system using blockchain and interplanetary file system, application status -published.
Book Chapter:
- Abhijit Saha, Abhay Kumar, Surajit Das, Bishnupada Debnath. Bipolar Fuzzy Generalized Dombi Aggregation Operators for Group Decision-Making. In: Sahoo, L., Senapati, T., Pal, M., Yager, R.R. (eds) Decision Making Under Uncertainty Via Optimization, Modelling, and Analysis. Studies in Systems, Decision and Control, vol 558. Springer, Singapore. https://doi.org/10.1007/978-981-96-0085-4_12
1. G. Sravya, S. Das, K. Anjali, G. V. Priya and S. Gajula, “A Hybrid Deep Learning Approach for Sign Language Recognition Using MobileNetV2 and Attention Mechanism,” 2026 Sixth International Conference on Advances in Electrical, Computing, Communications and Sustainable Technologies (ICAECT), Bhilai, India, 2026, pp. 1-6, doi: 10.1109/ICAECT68478.2026.11426032.
2. P. P. Lakra, T. K. Saha, B. L. Prajapati, S. Das, S. S. Prodduturi and Y. G. Priya, “Attention-Enhanced ResNet152V2 for Multi-Class Sugarcane Disease Detection Using Transfer Learning,” 2026 3rd International Conference on Advancements and Key Challenges in Green Energy and Computing (AKGEC), Ghaziabad, India, 2026, pp. 1-6, doi: 10.1109/AKGEC68790.2026.11485871.
3. S. Das, P. Chatterjee, A. Harini, P. K. Hamsika and S. H. Reddy, “Semi-Automated Brain Tumor Segmentation Using Thresholding and Morphological Processing with Real-Time OpenCV GUI Control,” 2025 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication (IConSCEPT), Karaikal, India, 2025, pp. 1-6, doi: 10.1109/IConSCEPT66142.2025.11436577.
4. S. Das, S. Gadde, M. A. Reddy and M. V. K. Reddy, “GenSQL: A Generative AI Framework for Natural Language to SQL Conversion,” 2025 IEEE 2nd International Conference on Green Industrial Electronics and Sustainable Technologies (GIEST), Jamshedpur, India, 2025, pp. 1-8, doi: 10.1109/GIEST66547.2025.11387480.
5. Surajit Das, L. G, S. J. Prakash, N. S. Dey, J. Panuganti and R. Poojitha, “Lung Cancer Detection and Classification using Transfer Learning with Pre-trained VGG19 Convolutional Neural Networks,” 2023 3rd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), Patna, India, 2023, pp. 1-6, doi: 10.1109/ICEFEET59656.2023.10452195.
6. S. Das, N. S. Dey and M. Mounika, “Automated Brain Tumor Segmentation in MRI : An Enhanced Mask Generation Approach,” 2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Kirtipur, Nepal, IEEE Xplore, 2023, pp. 891-897, doi: 10.1109/I-SMAC58438.2023.10290265
7. Surajit Das and Prakash, Sangem Jaya and Goswami, Rajat Subhra and G, Lavanya and Sasmal, Binoy, “Efficient Net-B6 model-based Transfer Learning For The Classification of Brain Tumors” (June 10, 2023). Available at SSRN: https://ssrn.com/abstract=4607794 or http://dx.doi.org/10.2139/ssrn.4607794
8. Surajit Das, Santosh Vishwakarma, S Ashish Rao, N Darshini Reddy Das, “Quantum Machine Learning Algorithms for Big Data Analytics in Cyber Security”. In: Patil, M., Vyawahare, V., Birajdar, G. (eds) Intelligent Computing and Big Data Analytics. ICICBDA 2024. Communications in Computer and Information Science, vol 2234. Springer, Cham. https://doi.org/10.1007/978-3-031-74682-6_10
9. P. Chatterjee, S. Das and S. Siddiqui, “Masking of Colposcopy Images- A New Approach,” 2024 International Conference on Advances in Modern Age Technologies for Health and Engineering Science (AMATHE), Shivamogga, India, 2024, pp. 1-6, doi: 10.1109/AMATHE61652.2024.10582189.
10. J. Tulsiani, K. Nayak, P. Premjit Lakra, A. Kumar and S. Das, “Privacy Preserving Scheme for EV Charging Station Using Machine Learning based Intrusion Detection System,” 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI), Coimbatore, India, 2024, pp. 545-552, doi: 10.1109/ICoICI62503.2024.10696403.
11. S. Das, M. A. Reddy, S. S. Prodduturi, Y. G. Priya, S. B. Sai, and N. Siri, “DARU-Net: A Deep Attention Residual U-Net with Boundary-Aware Loss for Brain Tumor Segmentation,”
in Proc. IEEE International Conference. Accepted and presented.
- Successfully completed “Intro to ML, DL and Computer Vision” by AI club from Indian Institute of Technology Madras.
- Successfully completed “One Week Online Short-Term Course on Machine Learning and its Applications in IoT, Computer Vision and Cloud Computing (MICC-2023)” during July 10th-14th, 2023 organized by Department of Computer Science & Engineering, NIT Jamshedpur.
- Successfully completed “Industry assisted online faculty development program” On EMERGING TECHNOLOGIES & REAL-WORLD APPLICATIONS conducted by PALS and industry experts from 22nd November to 24th November 2023.
- Participated in one week online international workshop on “Machine learning and Computer vision: Applications, Research challenges (MLCV-2020)” from NIT Shilchor.
- Participated in 10days workshop on “Big Data Analytics and Management” of the Dept. of CSE in Indian Institute of Engineering Science and Technology, Shibpur.
- Participated in a One Week Online Faculty Development Program on “Emerging Trends in Artificial Intelligence “Organized by Bhimavaram Institute of Engineering & Technology and Blackbuck Engineers Pvt Ltd from 25-31 May, 2022.
- Participated on One Week Faculty Development Program on “Mathematical Modeling for Data Science” Organized by VNR Vignana Jyothi Institute of Engineering and Technology.
- Participated in online international workshop on International Webinar on “Cyber physical Digital Microfluidic Biochips in Healthcare Technologies and Applications” During August 10-12, 2021from Indian Institute of Engineering Science and Technology, Shibpur.
- Participated in National Level One Week Faculty Development Program on “Recent Trends in Data Science for Engineering” organized by Department of Information Technology, Chaitanya Bharathi Institute of Technology, Hyderabad, Telangana in association.