Research Clusters

Data Processing and Computer Intelligence (DAPCI)

Director: Dr. Lina Karam

R&D in data science, AI/machine learning/deep learning, signal processing, multimedia, media processing and understanding, information representation, with applications in various areas including but not limited to robotics, construction, automated mobility, surveillance, forensics, assistive technologies, smart cities.

Recent advances in sensing, data acquisition, and storage platforms resulted in an explosion of data. This data explosion was further accentuated by the accessibility of compact and low-cost sensors on the go and by a growing interest in robotics, automated mobility, assistive technologies, and smart cities. The availability of large amount of data coupled with advances in computing pushed forward rapid advances and a growing interest in AI/machine learning for a variety of applications. However, there are still many challenges that need to be addressed to enable the deployment of smart data-driven technologies in the real-world. Such challenges include the complex, imprecise, and/or heterogenous nature of the acquired data, the complexity, accuracy, and sensitivity of AI/machine learning systems, and the need for domain-agnostic robust systems that can work effectively with multimodal data and under a variety of real-world conditions. The R&D performed under this cluster aim to address these challenges for a variety of application domains

Energy Engineering Research Group (EERG)

Welcome to the Energy Engineering Research Group at the Lebanese American University. This website describes our research activities. Our group has a broad range of research interests, from deep understanding of basic flow physics associated with simple and complex configurations, to contributing towards the creation of efficient and eco-friendly energy conversion systems by incorporating renewable energy sources and increasing system efficiency. Our interests additionally lie in tackling environmental and geophysical turbulent flows. In order to achieve reliable results with time-saving and cost-effective techniques, our research methodologies rely on using both experimental and numerical tools.

An overview of our recent and ongoing research endeavors is provided under this webpage. However, we highly encourage and look forward to stimulating further communication, as well as initiating new collaboration venues with researchers at other institutions.


Future Intelligent Dependable Networks (FIDNet)

Environmental concerns and an increasingly digital society have presented the electric power grid with new challenges. The grid will need to meet an increased power demand while reducing carbon dioxide emissions and meeting higher reliability, efficiency, and power quality requirements. To this end, national and international initiatives towards sustainable development have resulted in an increase in the integration of renewable energy into the power system. While the integration of renewable energy provides ample opportunities to improve the efficiency of the network, it also causes several technical challenges to its operation. To make optimal use of the opportunities provided and be able to deal with the technical challenges, the grid will have to undergo a major evolution, relying on greater levels of sensing, control and communication, to become what is known in literature as the smart grid.

The FIDNet cluster is a multidisciplinary team of faculty and students working together under the umbrella of smart grid research. The main areas of interest of the cluster include but are not restricted to:

  1. Smart Grid Security
  2. Power System State Estimation
  3. Power System Optimization
  4. Renewable Energy Integration.



Safe Mobility Research (SMR)

We are pleased to introduce the Safe Mobility Research (SMR) group, which is focused on enhancing driver safety by deepening our understanding of the social and behavioral issues important to the transportation of people and goods, mostly within the Lebanese context. The main focus of the research cluster is to investigate social, behavioral, and cognitive factors related to transportation engineering and driver psychology/behavior. The research cluster is targeting simulation scenarios that expand our knowledge of the social and behavioral factors related to high-risk aggressive driving. The research team additionally aims to evaluate the effects of public policy programs that promote safe driving and verify the latter’s benefits through controlled and simulated driving environments.

Housed in the Engineering Lab and Research Center, the full-scale driving simulator will be utilized to simulate real-life driving scenarios to test drivers (of various backgrounds) to assess driver behavior, aggressiveness, reaction, and interaction with certain design or guidance triggers. The scenarios will test current versus proposed interventions, with an ultimate goal of applying such measures to the Lebanese community through proposed regulations or actual implementations. The research cluster is led by transportation engineering faculty from the Civil engineering department in collaboration with faculty from Psychology department, data analytics and media/marketing.


Telemedicine and Health Informatics

Telemedicine and health informatics technologies including but not limited to R&D in data processing and communications with a focus on improving the diagnostic quality and the quality of experience (QoE) for patients and doctors; health data processing and AI; mobile on-the-go medical technologies; medical wearables; recommendations for telemedicine/health informatics technologies standardization efforts. Dr. Lina Karam; Dr. Roula Husni Samaha; Dr. Zahi Nakad; Dr. Madona Azar; Dr. Sola Bahous.

Telemedicine and health informatics are transdisciplinary fields encompassing several areas including but not limited to medical sciences, sensing, signal processing, multimedia, telecommunications, human-computer interfaces, computer engineering (software and hardware), AI/machine learning and data analytics, to name a few.

Telemedicine services are especially needed during pandemics to decrease the transmission of contagious diseases. They provide access across the globe to expert medical advice in a timely manner without any travel-related delays and expenses, in addition to much needed medical support in remote and underserved areas. The literature is clear that telemedicine has been very useful in Europe and the Americas. There is a need to develop and evaluate this technology further and expand its use in Lebanon and the MENA region, while augmenting it with health informatics capabilities, to reach out safely to all in need of care without compromising the quality of care.

In order to effectively deploy telemedicine services, several R&D challenges need still to be addressed. First, there is a need to develop low-power cost-effective telemedicine technologies that can be deployed on mobile portable devices as well as in the cloud, while providing an enhanced QoE, improved diagnosis and treatment, as well as patient-centered medical education.  For this purpose, R&D is needed in health informatics, data processing, compression and transmission technologies that are optimized for telemedicine applications, telemedicine-optimized edge and cloud computing, biomedical sensing, wearable health devices, low-cost mobile/at-home monitoring and diagnostic technologies, as well as  developing objective methodologies to assess and optimize the Quality of Service, Quality of Experience, and Diagnostic Quality.