I-CAIR

Innovative Computer Vision and Artificial Intelligence Research Group

A RESEARCH GROUP OF DR. SRICHETA PARUI, Assistant Professor, KIIT University

About Us

The ICAIR (Innovative Computer Vision and Artificial Intelligence Research) Group is a pioneering research and teaching laboratory focused on advancing the field of computer vision and artificial intelligence. Our mission is to explore innovative applications and methodologies that leverage the power of AI and computer vision to solve complex challenges and drive technological innovation. We specialize in EEG & brain-computer interfacing (BCI) research, strongly emphasizing multisensory BCI experiments. Our primary focus areas include auditory and tactile modality paradigms, and we are expanding into vision, olfactory, and gustatory paradigms to pioneer the future of "all-sensory-stimulus-based-BCI". We are at the forefront of developing signal processing techniques, particularly data-driven methods, for biomedical signal denoising, analysis, and classification.

TEAM LEAD

DR. SRICHETA PARUI

Assistant Professor (Senior Grade), Kalinga Institute of Industrial Technology-Deemed to be University, Bhubaneswar, India
PhD. In Computer Science and Engineering, Indian Institute of Industrial Technology Kharagpur (IIT Kharagpur), India
Masters in Engineering in Control System Engineering, Electrical Engineering Department, Jadavpur University, Kolkata, India
B.Tech. in Instrumentation and Control Engineering, Calcutta Institute of Engineering and Management (Gold Medalist)

Resume/CV

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Research Focus

AI in Healthcare

We focus on leveraging AI techniques to improve diagnostic accuracy, treatment planning, and patient care in healthcare settings. Our research spans medical imaging analysis, predictive modeling for disease prognosis, and personalized medicine applications.

Signal Processing

We specialize in developing advanced signal processing algorithms, particularly data-driven approaches, for biomedical signal denoising, analysis, and classification. Our work aims to enhance the reliability and interpretability of signals obtained from various healthcare monitoring devices.

Computer Vision

Our research in computer vision addresses challenges such as image and video understanding, object detection and recognition, and scene analysis. We explore the integration of computer vision with AI to automate tasks in healthcare diagnostics, monitoring, and treatment.

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