Asst. Professor, Dept. of EE, IIT Kanpur
Adjunct Faculty, Dept. of CSE, IIIT-Delhi
Email: kotesrj AT iitk DOT ac DOT in
Tel: +91 512 259 2483
Add: #302, ACES Building, IIT Kanpur
ORCID : 0000-0002-3507-3731
IRINS : 153811
Asst. Professor, Dept. of EE, IIT Kanpur
Adjunct Faculty, Dept. of CSE, IIIT-Delhi
Email: kotesrj AT iitk DOT ac DOT in
Tel: +91 512 259 2483
Add: #302, ACES Building, IIT Kanpur
ORCID : 0000-0002-3507-3731
IRINS : 153811
Koteswar is an Assistant Professor in the Electrical Engineering Department at the Indian Institute of Technology Kanpur (IIT Kanpur). He is also an Adjunct Faculty member in the Department of Computer Science and Engineering at the Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), where he previously served as a full-time faculty member. He holds a PhD from Nanyang Technological University (NTU), Singapore, and a BTech from the Indian Institute of Technology Roorkee (IIT Roorkee). His research interests span Computer Vision, Multimedia, and AI/ML, with several publications in leading conferences and journals, including CVPR, ICCV, ECCV, TIP, TMM, and TCSVT. For more details, please refer to his Curriculum Vitae (CV).
Koteswar's research group, Visual Intelligence and Multimodal Signals (VIMS) Lab, is seeking motivated PhD, Master's, and BTech students interested in Computer Vision and Machine Learning. Interested candidates should send their CVs to vims.iitk@gmail.com. Preference will be given to those with strong coding abilities and effective communication skills.
Computer Vision and Image Processing
Multimedia Computing and Systems
Artificial Intelligence and Machine Learning
Medical Imaging and Informatics
RESEARCH TOPICS:
Co-/Salient Object Detection and Co-/Segmentation
Customizing/Adapting Foundation Models
Interactive Image/Video Generation
Complex-valued Neural Networks
Web/Data Mining & Analytics
Intelligent Transportation Systems
Federated Learning in Computer Vision
Light-weight Face Recognition and Biometrics
Nature-inspired Adversarial Attacks and Defences
Vision-based Diagnostic and Rehabilitation Systems