Research Scholar

Technical Skills

• Programming & Tools: Python, C, C++, Java, SQL, PHP, AWS, CUDA, MATLAB, DICOM, Biopython, BLAST, UPPAAL, NuSMV
• Frameworks & Technologies: TensorFlow, PyTorch, Keras, Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, NiBabel, NLTK, OpenCV

Research Areas

• Medical Imaging, Deep Learning, Artificial Intelligence, Healthcare Cyber-Physical Systems (CPS), Formal Verification, Machine Learning, DNA/Protein Arrays, Cancer Research, Respiratory Diseases, Bioinformatics, High-Performance Computing (HPC), Internet of Things (IoT)

Education

• Ph.D., CSE

  National Institute of Technology Karnataka, Surathkal, India (September 2021 - Present)

• M.Tech., CSE

  Dr. B.R Ambedkar National Institute of Technology Jalandhar, Punjab, India (August 2019 - August 2021)

• B.Tech., IT

  IIMT Groupe of Colleges, G.Noida , India (July 2012 - July 2016)

Work Experience

Teaching Assistant @ National Institute of Technology Karnataka, Surathkal, India (September 2021 - Present)

• Conduct theory, lab, tutorial, and quiz sessions for C Programming and Python for B.Tech 1st Year students during the Odd semester (July–December).
• Lead the theory, lab, and quiz components for Compiler Design and Big Data for B.Tech 3rd-year students.
• Teach High-Performance Computing to M.Tech, M.TR, and Ph.D. 1st Year students focusing on advanced parallel computing concepts and practical implementations.
• Mentored B.Tech (3rd and 4th year) and M.Tech students (1st and 2nd years) on their minor and major projects under the supervision of my research advisor. Guided project design, implementation, technical writing, and presentation skills across programming, system design, and high-performance computing domains.

Researcher @ BISAG-N (MeiT) Govt. of India, Gandhinagar, India (June 2021_September 2021)

• Identified and resolved a critical flaw in the production data pipeline, enhancing data reliability across more than 70% of active user accounts.
• Contributed to applied research in medical and geospatial domains using advanced machine learning and cloud-based technologies.

Teaching Assistant @ Dr. B.R Ambedkar National Institute of Technology Jalandhar, Punjab India (_August 2019_Agust 2021)

• Conduct theory, lab, tutorial, and quiz sessions for C Programming and Software engineering for B.Tech 1st and 2nd Year students during the Odd semester (July–December).
• Lead the theory, lab, and quiz components for Cloud computing and Data Structure for B.Tech 2nd and 3rd Year students.
• Teach Deep Learning to M.Tech 1st Year students, focusing on medical domains and practical implementations.
• Mentored B.Tech (3rd and 4th year) on their minor and major projects under the supervision of my research advisor. Guided project design, implementation, technical writing, and presentation skills across programming and system design domains.

Senior Software Engineer @ KVCH, Noida, India (_Jan 2018_Feb 2019)

• Led the design and development of software modules for enterprise applications, ensuring scalability and performance optimization.
• Collaborated with cross-functional teams to implement end-to-end solutions using modern software engineering practices.
• Provided technical mentorship to junior developers and contributed to code reviews and process improvements.

Software Engineer @ Cogent E Service Pvt Ltd, Noida, India (_May 2017_Nov 2017)

• Developed and maintained web-based applications to support business operations and customer service platforms.
• Participated in requirement analysis, system design, and backend development using industry-standard tools and technologies.
• Collaborated with QA and support teams to ensure software quality and timely delivery.

Software Engineer Intern @ Geeks for Geeks, Noida, India (_September 2016_March 2017)

• Contributed to developing and optimizing educational web content and coding platforms.
• Assisted in building and testing modules for data structures and algorithms tutorials using Python and JavaScript.
• Collaborated with senior developers to enhance platform functionality and improve user experience for learners.

Projects

ADConv-Net: Advanced Deep Convolution Neural Network for COVID-19 Diagnostics Using Chest X-Ray and CT Images

Publication

Developed an objective strategy for identifying COVID-19, Normal, Bacterial Pneumonia, and Viral Pneumonia using a deep learning-based ADConv-Net framework on X-ray and CT images. The proposed data-driven model provides a fully automated and flexible approach to capturing key lung disease patterns and discovering new indicators of pulmonary activity.

EffiCOVID-Net: A Highly Efficient Convolutional Neural Network for COVID-19 Diagnosis Using Chest X-Ray Imaging

Publication

Implemented a lightweight EffiCOVID-Net model in Python, incorporating EffiCOVID block to classify chest X-ray images. The model accurately distinguished between COVID-19, Normal, and Viral Pneumonia classes.

Verification of COVIFIND Test Kit for COVID-19

Publication

Utilized UPPAAL to model and verify the architecture and functionality of the COVIFIND rapid antigen test kit, which ICMR approved. This formal verification approach ensures the kit’s reliability and correctness in detecting COVID-19 infections.

Automated Segmentation of COVID-19 Infected Lungs via Modified U-Net Model

Publication

Proposed an automated lung segmentation framework using Python and a modified U-Net model. The system dynamically generates randomized image patches with extensive data augmentation. The semantic segmentation approach achieved a Dice coefficient of 98.3% and an IoU of 96.8%, ensuring robust detection of COVID-19-infected lung regions.

Detecting COVID-19 Infection Using Customized Convolutional Neural Network

Publication

Designed a customized deep learning framework in Python for classifying chest X-ray images into four classes: COVID-19, Normal, Pediatric Bacterial Pneumonia, and Pediatric Viral Pneumonia. Leveraged popular models including VGG19, DenseNet201, EfficientNet, MobileNetV2, and InceptionV3. Achieved 97.06% accuracy, with a precision of 97.34%, recall of 96.36%, and F1-score of 97.01%.

Role of Genomics in the Smart Era and Its Application in COVID‐19

Publication

Explores the genetic underpinnings of human diseases and complex traits. Emphasizes how comparative genomic studies and DNA sequencing can advance disease resistance, treatment development, and population adaptability. The chapter provides an overview of genomics fundamentals and its various application areas.

Brain Tumor Detection Analysis Using CNN

Publication

Applied CNN-based deep learning approach for brain tumor detection and classification. The system distinguishes between benign and malignant tumors and effectively classifies different types using labeled medical imaging datasets—supporting early diagnosis and treatment planning.

Awards

• Earned the Best Paper Award at the IEEE GCON, 2023
• Recipient of MHRD Scholarship, Govt. of India as NIT Karnataka Institute Assistantship for Doctoral Programme, September 2021 – September 2026.
• Received a First Prize in the Research Ethics Competition organized by IEEE TEMSCON ASPAC 2024.
• Recipient of Project Fellow Assistantship sponsored by BISAG-N, MeitY, Govt. of India, May 2021 – September 2021.
• Guest Lecture: Deep Learning and Machine Learning for Scientific Discovery, organized by ISRO at BISAG-N 2021.
• Earned the Best Paper Award at the IEEE ICAIS, 2021.
• Recipient of MHRD Scholarship, Govt. of India, as NIT Jalandhar Institute Assistantship for Post Graduation, August 2019 – June 2021.

Publications

1. Kumar, S., & Bhowmik, B. (2025). ADConv-Net: Advanced Deep Convolution Neural Network for COVID-19 Diagnostics Using Chest X-Ray and CT Images. SN Computer Science, 6(5), 1-22. https://doi.org/10.1007/s42979-025-03923-4
2. Kumar, S., & Bhowmik, B. (2025). EffiCOVID-net: A highly efficient convolutional neural network for COVID-19 diagnosis using chest X-ray imaging. Methods. https://doi.org/10.1016/j.ymeth.2025.04.008
3. Reddy, M. R. V., Kumar, S., & Bhowmik, B. (2025, February). A Comprehensive Survey on Breast Cancer Diagnostics: From Artificial Intelligence to Quantum Machine Learning. In 2025 3rd International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) (pp. 1179-1187). IEEE. DOI: 10.1109/ISACC65211.2025.10969410
4. Chavan, S., Nile, P., Kumar, S., & Bhowmik, B. (2025, February). Taskgraph Framework: A Competitive Alternative to the OpenMP Thread Model. In 2025 3rd International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) (pp. 343-348). IEEE. DOI: 10.1109/ISACC65211.2025.10969267
5. Kumar, S., Rathore, R., & Bhowmik, B. (2024, December). Verification of COVIFIND Test Kit for COVID-19. In 2024 IEEE 21st India Council International Conference (INDICON) (pp. 1-6). IEEE. DOI: 10.1109/INDICON63790.2024.10958463
6. Bhowmik, B., Kumar, S., Raju, S. R., Prakash, A., & Mense, O. (2024, December). Optimizing Split Algorithm Performance: A Heuristic Method for Enhanced Tensor Product Matrix Computations. In 2024 IEEE 21st India Council International Conference (INDICON) (pp. 1-6). IEEE. DOI: 10.1109/INDICON63790.2024.10958524
7. Kumar, S., & Talib, M. (2024, December). Optimizing Performance of OpenMP Parallel Applications through Variable Classification. In 2024 IEEE 21st India Council International Conference (INDICON) (pp. 1-6). IEEE. DOI: 10.1109/INDICON63790.2024.10958418
8. Singh, R., Zadokar, V. N., Kumar, S., Doddamani, S. S., & Bhowmik, B. (2024, November). Leveraging Hybrid Modeling for Enhanced Runtime Prediction in Big Data Jobs. In 2024 International Conference on Computing, Semiconductor, Mechatronics, Intelligent Systems and Communications (COSMIC) (pp. 48-53). IEEE. DOI: 10.1109/COSMIC63293.2024.10871292
9. Nayaka, P. S. J., Kumar, S., Singh, A., & Sohail, M. (2024). MPI for SPH Methods and Parallel Computing on CPUs and GPUs. International Journal of Microsystems and IoT, 2(9), 1162–1169. https://doi.org/10.5281/zenodo.14066770
10. Kumar, S., Kisku, B., Kumar, S., & Bhowmik, B. (2024, August). Detecting COVID-19 Infection Using Customized Convolutional Neural Network. In 2024 Control Instrumentation System Conference (CISCON) (pp. 1-6). IEEE. DOI: 10.1109/CISCON62171.2024.10696823
11. Kumar, S., & Bhowmik, B. (2024, June). Automated Segmentation of COVID-19 Infected Lungs via Modified U-Net Model. In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-7). IEEE. DOI: 10.1109/ICCCNT61001.2024.10724997
12. Girish, K. K., Kumar, S., & Bhowmik, B. R. (2024). Industry 4.0: Design principles, challenges, and applications. Topics in Artificial Intelligence Applied to Industry 4.0, 39-68.
13. Kumar, S., & Bhowmik, B. (2023, December). Diagnosis of sars-cov-2 via rapid antigen kits. In 2023 IEEE Technology & Engineering Management Conference-Asia Pacific (TEMSCON-ASPAC) (pp. 1-7). IEEE. DOI: 10.1109/TEMSCON-ASPAC59527.2023.10531579
14. Kumar, S., & Bhowmik, B. (2024, January). Emergence, evolution, and applications of cyber-physical systems in smart society. In 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) (pp. 1-8). IEEE. DOI: 10.1109/ICAECT60202.2024.10468864
15. Kumar, S., & Bhowmik, B. R. (2023). Role of Genomics in Smart Era and Its Application in COVID‐19. Privacy Preservation of Genomic and Medical Data, 73-112.
16. Kumar, S., & Bhowmik, B. (2023, June). Covid-19 waves and their impacts to society. In 2023 IEEE Guwahati subsection conference (GCON) (pp. 1-5). IEEE. DOI: 10.1109/GCON58516.2023.10183544
17. Shandilya, S., & Kumar, S. (2023). Time series analysis of stocks using deep learning. In Emerging Trends in IoT and Computing Technologies (pp. 437-442). Routledge.
18. Kumar, S., Dhir, R., & Chaurasia, N. (2022). Identification of brain tumor detection from MRI image using convolution neural network. J. Tumor Res. 1 J Tumor Res, 8, 1000165.
19. Kumar, S., Dhir, R., & Chaurasia, N. (2021, March). Brain tumor detection analysis using CNN: a review. In 2021 international conference on artificial intelligence and smart systems (ICAIS) (pp. 1061-1067). IEEE. DOI: 19.1109/ICAIS50930.2021.9395920
20. Mollah, S., Kumar, S., & Chavan, S. (2021). Design of Innovative LED Mirror by Using Product Design Principles. International Journal of Electrical Machines & Drives, 7(1), 39-48p.
21. Singh, D., Pazhanisamy, S., Kumar, S., Kumar, A., & Reddy, S. L. (2020). Bio-efficacy of different herbicides in broad spectrum weed management for chickpea. International Journal of Current Microbiology and Applied Sciences, 9(3), 2313-2317.
22. Kumar, S., Ratnoo, S., & Bala, R. (2020). Enhanced decision tree algorithm for discovery of exceptions In advanced computing and intelligent engineering.
23. Shandilya, S., Kumar, G., & Kumar, S. K-means clustering algorithm to improve website performance.

🌐 Socials:

📍 Contact:

• Name: Sunil Kumar
• Position: Research Scholar
• Email: sunilk.217cs010@nitk.edu.in sunilit.iimtgn@gmail.com
• Office: Room No. 506, Dr. B.R. Bhowmik Lab (BRICS), 5th Floor (Right Wing), Department of CSE, National Institute of Technology Karnataka (NITK), Surathkal, Mangalore – 575025, India