NU IoT research group
The Internet of Things research group is led by Prof. Dimitrios Zorbas. Its purpose is to conduct research on and develop modern Internet of Things communication and sensing systems. The topics of interest include but are not limited to communication protocols, embedded programming, smart sensing systems, machine learning for IoT, and prototype development.

Circular Economy Indexing in Construction Industry Using Big Data and AI
This research aims to utilize state-of-the-art Artificial Intelligence (AI) techniques to develop a novel Circular City Indexing (CCI) method for construction job site management and operation. Creating circularity indexes for cities is a new research area. CCI typically involves Big Data Analysis (BDA) and provides a concise measurement of the factors extracted from the data related to urban performances supporting local, national, and international green policies. This project focuses on a novel contribution to the built environment part of the circular developments in cities. Thus, it will facilitate the development of a CCI for the built environment, focusing on construction activities.

The project will deliver a significant, open-source, and meticulously annotated dataset for construction sites from cities worldwide and develop a novel CCI with actions and strategies enabling support for circular and sustainable construction site management strategies and planning of investments. These outcomes may particularly impact enabling factors of the green transition that may differ across territories. It will help policymakers promote a smooth and fair transition by fostering municipalities’ preparedness to address the challenge. The development of circularity measures can help to improve local urban management.

Bioengineering research group
Our bioengineering research group is dedicated to advancing healthcare through innovative applications of engineering and computational techniques. Our diverse projects include developing patient-specific approaches for breast cancer screening using machine learning, creating diagnostic tools for coronary artery disease through the integration of medical imaging and simulations, exploring the biomechanics of the spine, studying nasal aerodynamics, and investigating hemodynamics and blood-vessel interactions in the cardiovascular system. Through a multidisciplinary approach, we aim to contribute to the understanding and improvement of various aspects of human health, pushing the boundaries of bioengineering research.

Energy Research Group
This research group focuses on advancing computational methodologies for optimizing various engineering designs across multiple disciplines. Their primary expertise lies in aerodynamics and fluid-structure interactions, with applications ranging from aerospace to
energy systems. By developing and implementing advanced computational fluid dynamics (CFD) techniques, such as URANS/VLES and discrete two-way Fluid-Structure Interaction (FSI), they aim to enhance the efficiency, performance, and reliability of engineering
systems. Additionally, they explore multidisciplinary design optimization approaches to address complex engineering challenges, ultimately contributing to the advancement of various industries, including aerospace, energy, and materials science.