Email: nspunn1993@gmail.com
Experience: Worked as: 1) Consultant for 2 years (2015-17) in Intellect Design Arena Ltd., Chennai, industry; 2) Postdoctral Research Fellow at Mayo Clinic, Arizona, USA
Address:
Room No. 207, Department of CSE, Block IV, ABV-IIITM Gwalior, 474015 (M.P)
Personal Web Page: https://punndeeplearningblog.com
Dr. Narinder Singh Punn is an Assistant Professor at the Department of Computer Science and Engineering ABV- Indian Institute of Information Technology Gwalior. Office: Block-D, 207, Email: nspunn@iiitm.ac.in, Number of PhD Students Graduated: 00, Number of M. Tech. Graduated:06, Number of Publications: 09 (Journals), 19 (Conferences), h-index: 18, i10 index: 22, Number of Projects: 02, Number of Keynote/Invited Talks Delivered: 19, Number of Committee Memberships: 01
Area of Specialization: Computer vision, Biomedical image processing, Image classification, Image segmentation, Object detection
Number of M. Tech. Graduated:06,
Number of Publications: 09 (Journals), 19 (Conferences),
h-index: 18, i10 index: 22, Number of Projects: 02,
Number of Keynote/Invited Talks Delivered: 19,
Number of Committee Memberships: 01
Office: 207, Block-V, ABV-IIITM
|
Degree |
Year |
Subject |
University/Institution |
|
PhD |
2022 |
Information Technology |
Indian Institute of Information Technology Allahabad, Uttar Pradesh, India |
|
M. Tech. |
2019 |
Software Engineering |
Indian Institute of Information Technology Allahabad, Uttar Pradesh, India |
|
B. Tech. |
2015 |
Computer Science and Engineering |
National Institute of Technology Hamirpur, Himachal Pradesh, India |
Deep Learning, Medical Image Analysis, Bioinformatics, Quantum Machine Learning, Big Data Analytics
1.Rajpopat, Subodh, Sunil Kumar, and Narinder Singh Punn. “Cerebral palsy detection from infant using movements of their salient body parts and a feature fusion model.” The Journal of Supercomputing 81.1 2025: 106, https://doi.org/10.1007/s11227-024-06520-z.
2.Tanay, Mogalluru Chidhvilas, Rahul Rathnam, Pamba Vamshi Krishna, Mrinal Devnath, and Narinder Singh Punn. “Enhanced QSAR Modeling for Drug Discovery: Leveraging Advanced Computational Tools and Techniques.” In 2024 IEEE Region 10 Symposium (TENSYMP),pp.1-6.IEEE,2024. https://doi.org/10.1109/TENSYMP61132.2024.10752307.
3.Punn, Narinder Singh, Bhavik Patel, and Imon Banerjee. “Liver fibrosis classification from ultrasound using machine learning: a systematic literature review.” Abdominal Radiology 49, 2024: 69-80, https://doi.org/10.1007/s00261-023-04081-y.
4.Punn, Narinder Singh, and Sonali Agarwal. “BT-Unet: A self-supervised learning framework for biomedical image segmentation using Barlow Twins with U-Net models.” Machine Learning 111, 2022: 4585-4600, https://doi.org/10.1007/s10994-022-06219-3.
5.Punn, Narinder Singh, and Sonali Agarwal. “CHS-Net: A Deep Learning Approach for Hierarchical Segmentation of COVID-19 via CT Images.” Neural Processing Letters 54, 2022: 3771-3792, https://doi.org/10.1007/s11063-022-10785-x.
6.Punn, Narinder Singh, and Sonali Agarwal. “Modality specific U-Net variants for biomedical image segmentation: a survey.” Artificial Intelligence Review 55, 2022: 5845–5889, https://doi.org/10.1007/s10462-022-10152-1.
7.Punn, Narinder Singh, and Sonali Agarwal. “RCA-IUnet: a residual cross-spatial attention-guided inception U-Net model for tumor segmentation in breast ultrasound imaging.” Machine Vision and Applications 33, no. 2, 2022: 27, https://doi.org/10.1007/s00138-022-01280-3.
8.Punn, Narinder Singh, and Sonali Agarwal. “Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks.” Applied Intelligence 51, no. 5, 2021: 2689-2702, https://doi.org/10.1007/s10489-020-01900-3.
9.Punn, Narinder Singh, and Sonali Agarwal. “Multi-modality encoded fusion with 3D inception U-net and decoder model for brain tumor segmentation.” Multimedia Tools and Applications 80, no. 20 2021: 30305-30320, https://doi.org/10.1007/s11042-020-09271-0.
10.Punn, Narinder Singh, and Sonali Agarwal. “Inception u-net architecture for semantic segmentation to identify nuclei in microscopy cell images.” ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM) 16, no. 1, 2020: 1-15, https://doi.org/10.1145/3376922.
|
Sl |
Grant (Project/ Consultancy) |
Funding Agency |
PI/Co-PI |
|
1 |
A multimodal analysis for mental disorder recognition to improve mental health and well-being (MODEST) |
UPCST |
Co-PI |
|
2 |
Robust Defense Mechanism Against Adversarial Attacks in Medical Imaging Systems |
FIG |
PI |
|
SN |
Title |
Period |
Sponsoring Organization |
Venue |
|
|
|
|
From |
To |
|
|
|
1. |
FDP - Towards AI Enabled Computer Vision |
15/07/2024 |
19/07/2024 |
Self |
ABV-IIITM Gwalior |
|
2. |
Advancements in Medical Image Analysis: Theory and Hands-on Workshop on Cutting Edge Technologies |
20/04/2024 |
21/04/2024 |
TIIC |
ABV-IIITM Gwalior |
|
3 |
Advanced Workshop on Deep Learning Applications in Imaging Systems |
17/07/2023 |
23/07/2023 |
SERB |
ABV-IIITM Gwalior |
|
4 |
High End Workshop on Machine Learning applications for Medical Imaging |
10/07/2023 |
16/03/2023 |
SERB |
ABV-IIITM Gwalior |
