About Me
I am a Researcher and currently an Assistant Professor at the CSE Department of Shiv Nadar University. My research interests lie in the fields of pattern recognition and machine learning. Specifically, I am interested in understanding 1-D signals and medical images and language models.
Education
- Ph.D. in Computer Science - IIT Bombay
- M.E. - IISc Bengaluru
- B.Tech - NIT Warangal
Experience
Assistant Professor Shiv Nadar Institute of Eminence Noida (2023-Present)
Senior Research Engineer at Philips Research (2021-2023)
Assistant Professor at LNMIIT Jaipur (2019-2021)
Member of Technical Staff, VMWare Soft. India Pvt. Ltd., Bengaluru (2013-2014)
Teaching
Introduction to Machine Learning (CSD361)
Undergraduate course covering supervised and unsupervised learning, neural networks, and optimization.
Computational Linear Algebra
Undergraduate and Graduate level course focusing on applications of Linear Algebra in Vision, NLP and Big data.
Selected Publications
ARMARecon: An ARMA Convolutional Filter Based Graph Neural Network for Neurodegenerative Dementias Classification
Venkata Sesha Satya Tejaswi Abburi,Ananya Singhal and Saurabh Shigwan, Nitin Kumar
IEEE 23rd International Symposium on Biomedical Imaging (ISBI) 2026 (To Appear)
UCDSC: Open Set UnCertainty aware Deep Simplex Classifier for Medical Image Datasets
Arnav Aditya, Nitin Kumar, Saurabh Shigwan
The IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026 (To Appear)
Multi-Feature Graph Convolution Network for Hindi OCR Verification
Shikhar Dubey, Krish Mittal, Sourava Kumar Behera, Manikandan Ravikiran, Nitin Kumar, Saurabh Shigwan, Rohit Saluja
Proceedings of the 1st Workshop on Benchmarks, Harmonization, Annotation, and Standardization for Human-Centric AI in Indian Languages (BHASHA 2025)
UnSegMedGAT: Unsupervised Medical Image Segmentation using Graph Attention Networks Clustering
A Mudit Adityaja, Saurabh J Shigwan, Nitin Kumar
IEEE 22nd International Symposium on Biomedical Imaging (ISBI) 2025, Houston, TX, USA
UnSeGArmaNet: Unsupervised Image Segmentation using Graph Neural Networks with Convolutional ARMA Filters
Kovvuri Sai Gopal Reddy, Saran Bodduluri, A. Mudit Adityaja, Saurabh Shigwan, Nitin Kumar, Snehasis Mukherjee
British Machine Vision Conference (BMVC) 2024, Glasgow, UK
SimSAM: Simple Siamese Representation-Based Semantic Affinity Matrix for Unsupervised Image Segmentation
Chanda Grover Kamra, Indra Deep Mastan, Nitin Kumar, Debayan Gupta
IEEE International Conference on Image Processing (ICIP) 2024, Abu Dhabi
Podium Presentation, Acceptance Rate 17%, Graduate Student Travel Award
Semi-Supervised Robust Mixture Models in RKHS for Abnormality Detection in Medical Images
Nitin Kumar, Suyash Awate
IEEE Transactions on Image Processing 2020
Semi-Supervised Robust One-Class Classification in RKHS for Abnormality Detection in Medical Images
Nitin Kumar, Ajit Rajwade, Sharat Chandran, Suyash Awate
IEEE International Conference on Image Processing (ICIP)-2019, Taipei, Taiwan
Kernel Generalized-Gaussian Mixture Model for Robust Abnormality Detection
Nitin Kumar, Ajit Rajwade, Sharat Chandran, Suyash Awate
MICCAI 2017, Quebec City, Quebec, Canada
Kernel generalized-Gaussian mixture model for robust abnormality detection
Nitin Kumar, Ajit Rajwade, Sharat Chandran, Suyash Awate
IEEE International Conference on Image Processing (ICIP) 2017, Beijing, China
Best Paper Finalist
Text Simplification for Enhanced Readability
Siddhartha Banerjee, Nitin Kumar and C.E. Veni Madhavan
IC3K-KDIR/KMIS 2013, Vilamoura, Algarve
Research Projects
Open Set Recognition
Developing neural networks to model compact inlier and outlier classification on vision data
Machine Learning Healthcare
Image Segmentation
Segmenting regions of images in the framework of unsupervised and self-supervised learning
Machine Learning Computer Vision
