Description: Digital Twin solutions refers to the creation of a virtual representation or replica of physical objects, environments, or systems that can be used to enhance accessibility and support individuals with disabilities. This concept involves integrating real-time data, simulations, and predictive analytics to improve the functionality, personalization, and effectiveness of assistive systems

Faculty: Dr. Pramit Mazumdar, Dr. Ajay Nath

Description: Visual Quality Assessment (VQA) aims to evaluate the perceived quality of visual content (images, videos, or 3D models). The task involves developing methods to measure and predict how humans perceive the quality of visual media, taking into account factors such as distortion, resolution, color accuracy, sharpness, and artifact presence. The task is to develop objective (computational) framework which can accurately estimate the visual quality without human intervention.

Faculty: Dr. Pramit Mazumdar

Description: "Drowsiness is characterized by reduced attentiveness, commonly occurring during the transition from wakefulness to sleep. It significantly impairs alertness, increasing the risk of accidents in critical activities such as driving, crane operation, mining, and industrial machinery handling. Effective drowsiness detection is essential for accident prevention in such scenarios.In this research, a model is proposed to detect human drowsiness by analyzing EEG signals. The focus is on single-channel EEG due to its advantages, including low cost, ease of configuration, user convenience, simplified signal acquisition, and compatibility with portable and mobile devices. The research contributions include channel selection, signal processing, feature extraction, feature selection, and machine learning-based analysis to enhance drowsiness detection accuracy"

Faculty: Dr. Venkata Phanikrishna B

Description: Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by challenges with social interaction, communication, and restricted or repetitive behaviors. Early detection of ASD is critical because it enables timely intervention, which can significantly improve outcomes for individuals with the condition. We are working towards developing computer vision-based approaches for early detection of ASD in children.

Faculty: Dr. Pramit Mazumdar

Description: Conversational Recommender Systems are AI-driven systems designed to engage users in interactive, natural language conversations to recommend items, services, or information. Unlike traditional recommender systems, CRSs actively involve the user in the recommendation process by asking questions, clarifying preferences, and refining suggestions based on user feedback during the interaction.

Faculty: Dr. Pramit Mazumdar

Description: It focuses on leveraging advanced technologies and sustainable practices to optimize urban transportation systems. It encompasses eco-friendly mobility solutions, intelligent traffic management, renewable energy integration, and data-driven planning to reduce environmental impact and enhance efficiency. This research domain aims to create cleaner, smarter, and more accessible transit options for urban areas, promoting sustainable urban development and improved quality of life.

Faculty: Dr. Naveen Kumar

Faculty: Dr. Pratikkumar Parimal Shah

Description: Cybersecurity research focuses on protecting digital systems, networks, and data from unauthorized access, damage, or attacks. It encompasses developing technologies, methodologies, and protocols to ensure confidentiality, integrity, and availability of information. Key areas include cryptography, secure authentication, threat detection, network security, incident response, and risk management. Advanced topics explore the use of AI/ML, blockchain, and quantum cryptography for enhanced security. The domain also addresses emerging threats like insider risks, IoT vulnerabilities, and cyber-physical systems, making it critical for safeguarding modern digital infrastructure.

Faculty: Dr. Naveen Kumar