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Hybrid intelligent systems in driving autonomy

The project aims to develop an intelligent system for the manoeuvring of on-road autonomous vehicles. This project attempt to integrate learning-based AI and model-based predictive control strategies for improving the driving performance of autonomou

Integrated Photonic Artificial Neural Networks INPATIENT

The research proposal aims to investigate, design, and realize integrated photonic neural networks (PNNs) for all-optical neuromorphic computing. The main objectives include analyzing, designing, and modeling PNNs for AI-driven applications, designin

Integrated Sensing and Communication Systems ISAC Empowered by Machine Learning Techniques for 6G

The project aims to address challenges in Integrated Sensing and Communication (ISAC) technology for future wireless systems, such as balancing communication and sensing requirements and mitigating interference. It will conduct a comprehensive study,

Investigating Novel Lightweight Cryptographic Primitives in the Quantum Era from Design and Implementation Perspectives

The advent of quantum computing has significant implications on cryptography, affecting both public-key and symmetric-key cryptographic primitives. While quantum computers can completely break current public-key cryptography, they reduce the security

Investigation of power of Deep Neural Networks against various adversarial attacks and their applications to Cybersecurity

The project aims to analyze and review potential adversarial attacks on existing Deep Neural Networks (DNNs), design robust models for their detection, and conduct robustness analysis against these attacks. The project also studies adversarial attack

Machine Learning-Based Condition Monitoring at Constrained Edge Devices

In modern industrial systems, condition monitoring is essential for maintaining optimal process operation. Condition monitoring relies on real-time analysis and correlation of various sensor data, often with the need for preprocessing and feature ext

Manageable AI for scene understanding tasks from low light noisy images

Image and video acquisition and processing are crucial components of ICT, influencing consumer behavior, products, and services. This project aims to create manageable AI equipment that can be used with limited computational and energy resources, esp

Map Indoor Multi-user Localization, Navigation and Mapping using Millimeter Wave Sensing

The study proposes a novel approach to indoor navigation and mapping, combining millimeter-wave sensors with navigation algorithms. These sensors, operating in the 30 to 300 GHz frequency range, capture high-resolution data about the environment. The

Neuromorphic Computing and Neuro-optimizer Platforms Utilizing High-yield Passive RRAM Crossbar Arrays

This project aims to create a high-yield passive RRAM crossbar array, characterize its static and dynamic characteristics, develop a comprehensive compact model, explore advanced AI/ML algorithms and neuro-optimization algorithms, and hardware demons

NIDHI COE (Centre of Excellence) at T-Hub Foundation, Hyderabad, Telangana