Integrating hardware and embedded systems with IoT/IIoT technologies, focusing on efficient hardware design, encryption, and authentication methods.
Establishing secure connectivity by integrating security measures with image processing, AI algorithms, and hardware and embedded security solutions.
Advance human-centric computing through the integration of Lifelong Machine Learning (LLM), graph theory, and heterogeneous data integration techniques.
Addresses ethical financial reporting by employing encryption and edge intelligence technologies, integrating IoT and digital twin concepts, and utilizing AI-based financial modeling approaches.
Advance autonomous vehicles through the enhancement of robotics and communication technologies, optimization of hardware efficiency, and the prioritization of safety and quality measures.
Anomaly detection by employing lightweight algorithms, integrating multisensor data fusion techniques, leveraging Industrial Internet of Things (IIoT), and implementing digital twin technologies
Enhance security through the integration of authentication methods with biometrics and AI, within the framework of the Internet of Battlefield Things (IoBT).
Utilizing disease modeling techniques alongside multimodal data processing on smart cloud platforms, integrated with Brain-Computer Interface (BCI) technology.
Developing predictive behavioral models through genomic analysis, employing machine learning (ML), deep learning (DL), and language learning models (LLM), and fostering human-machine teaming through generative AI and neural link technologies.
Addressing intellectual disabilities in children through image processing and content mining techniques, utilizing machine learning (ML), deep learning (DL), natural language processing (NLP), and natural language
modeling (NLM), with a focus on promoting inclusive quality education as per Sustainable Development Goal 4 (SDG4).
The research pathway aims to enhance educational skill assessment through the use of graphical models and community engagement strategies, leveraging reinforcement learning techniques and collaborative intelligence methodologies.
Enhancing health through the utilization of learning algorithms, incorporating human-machine training/learning paradigms, and integrating generative AI with digital twin technology.
Detect corporate fraud by employing natural language processing (NLP), reinforcement learning (RL), or limited memory learning (LLM) algorithms, within the context of financial technologies, while exploring the potential of brain-computer interface technology and text filling
grammatics.
Early childhood development through the integration of heterogeneous data analytics, leveraging edge intelligence in conjunction with large multimodal systems.
Support neurodiversity through the implementation of assistive technology, utilizing super large multimedia AI systems, and enhancing community engagement with the assistance of generative AI technologies.
Safeguard vulnerable communities through bio-inspired analysis and design, leveraging Internet of Things (IoT) and Geographic Information Systems (GIS) technologies, as well as integrating 6G connectivity and large-scale AI models.