Narinder Singh Punn
Atal Bihari Vajpayee Indian Institute of Information Technology and Management
0000-0003-1175-1865
About
My name is Narinder Singh Punn and I am currently working as an Assistant Professor in the Department of Computer Science and Engineering at Atal Bihari Vajpayee Indian Institute of Information Technology and Management Gwalior. Earlier, I worked as a Postdoctoral Fellow at the Machine Intelligence in Medical Imaging (MI2) lab, Mayo Clinic, Arizona, USA. I received Ph.D. in biomedical image segmentation from the Indian Institute of Information Technology Allahabad, Prayagraj, India, in April 2022I completed my Bachelor’s degree in computer science and engineering from the National Institute of Technology Hamirpur (NITH) in 2015. I have 2 years (2015-17) of experience as a software developer at Intellect Design Arena Ltd., Chennai, India.
I am always fascinated by the potential of machine learning and deep learning algorithms and hence follows my research interest. I have published papers in international journals, conferences and pre-print servers. My main research includes: Machine learning, Deep learning, Big data analytics and Data stream processing in healthcare domain. I have also gained outreach experience in delivering tutorial sessions and organizing several workshops and conferences on international platforms.
Employment
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Atal Bihari Vajpayee Indian Institute of Information Technology and Management Assistant Professor2023 - Present
Education
Education history is unavailable.
Projects & Funding
Projects & funding information is unavailable.
Publications (56)
- Hierarchical Attention Lightweight U-Net for Gastro-Intestinal Tract Segmentation Save
- DINOv2KAN: Kolmogorov–Arnold Network with DINOv2 Vision Transformer for enhanced characterization of Alzheimer’s Disease Save
- Enhancing robustness against adversarial attacks in biomedical image classification through squeezed quantized self-supervised contrastive learning Save
- LTM-UNet: Linear Transformer–Mamba with Attention-Based U-Net for Context-Aware Breast Ultrasound Image Segmentation Save
- EVC-Net: A Hybrid Deep Learning Network for Breast Cancer Classification from Histopathological Images Save
- KS-TMIL: A K-Stage Transformer approach with multiple instance learning model for ovarian cancer subtype classification Save
- CTAUNet: Improved retinal blood vessel segmentation with collaborative transformer attention U-Net Save
- Ensemble Meta-Learning using SVM for Improving Cardiovascular Disease Risk Prediction Save
- LWU-Net approach for Efficient Gastro-Intestinal Tract Image Segmentation in Resource-Constrained Environments Save
- Impact of the Composition of Feature Extraction and Class Sampling in Medicare Fraud Detection Save