Nexus for research, innovation and technology development and transfer
As part of the ACG 150 strategic plan, the Research, Technology & Innovation Network (RTIN) seeks to combine the in-house research and innovation (R&I) potential stemming from ACG’s faculty, schools, departments, institutes, centers, programs and labs with an external network of collaborators and innovation players (corporations, investors, start-up clusters and incubators, funding agencies, innovation and market fora and think-tanks, venture capital funds, standardization and regulatory authorities, legal counsels, sponsors and donors).
Virtually unlimited in theme and scope, the Network’s activities track the evolution of many science and technology (S&T) disciplines that shape our world. Some current areas that are addressed through the activities of current Deree and ALBA faculty include: information and communication technologies (next generation networks including the Internet-of-Things, data science, artificial intelligence, cyber security, etc.), optimization and operations research, economics and finance, marketing, business and management, biomedical science and e-health, psychology and cognitive science, visual arts, literature, philosophy, history and journalism.
The RTIN has access to a number of ACG facilities and collaborates with the corresponding teams for its research & technology-oriented innovation activities. It participates in a number of collaborative research projects which are conducted jointly with external partners and funding. RTIN's innovation activities are aimed in two directions: developing our own innovation capacity based on in-house expertise and generated intellectual property (IP), which acting as an innovation hub for external partners who seek innovation-oriented partnerships and support.
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RTIN’s Artificial Intelligence Research Area covers research activities related to the study, design, analysis, modeling, and prototyping of artificial intelligence for many applications, most notably related to autonomous intelligent agents and multi-agent systems. This includes (but is not limited) to the analysis of intelligent agents for a number of applications such as online trading and resource allocation, allocation and contracting of services, energy management and usage. A number of AI techniques are useful for this research, such as game and decision theory, optimization, simulations and modeling, search algorithms and algorithmic design. In addition, we are more recently interested in AI applied to games and (to a lesser degree) game creativity and game design.
The Biomedical Science Research Team Area (BMSR) covers research activities related to subject areas ranging from molecular and cell biology, protein-DNA interactions and gene expression, microbiology, virology, structural biology/molecular biophysics and bioinformatics, cancer research, genetic diseases, and rare diseases, chemical biology, neuroscience, pharmacology, drug development, and research on environmental health issues, on big data analytics in bioinformatics, medicine, health, and healthcare. The aim of this research area is to bridge internal and external research collaborations in biomedical science. Most of the activities are centered around the recently fully renovated Deree labs (the Biology lab, the Chemistry & Cell and Molecular Lab, and the Physical Sciences lab), which feature state-of-the-art infrastructure for science teaching and basic science research and host several researchers that work on a variety of research projects and studies either individually or collaboratively as part of a team.
Biostatistics is the application of statistical methodologies and data analytics to the fields of biological sciences and medicine. In an era of emerging data sets, from genome sequencing to electronic medical records, new statistical tools are often needed to interpret massive amounts of data and detect correlations, patterns and causations.
RTIN’s Biostatistics Research Area covers activities related to genome-wide association studies and next-generation sequencing, statistical genetics, missing data, integration of analytic tools, Bayesian methods, and computationally-intensive methods. Areas of application include bioinformatics, computational biology, the environment, genetics, transcriptomics, among other areas.
Future directions of interest include sampling-based designs and analysis approaches for generalizing the results of case-control and cohort studies, sampling for disease screening or prevalence estimations, development and validation of models for minority populations, and evaluating the potential utility of genetic and other biomarkers in specific pathologies.
The entrepreneurship management research area addresses topics related to cognitive, organizational and socio-economic aspects of nascent entrepreneurship and technological innovation. In particular, the research focuses on organizational and socio-economic implications of technological change and the study of the entrepreneurial mindset with an emphasis on the cognitive processes that explain decisions and subsequent behavior of nascent entrepreneurs.
The NEURO-HCI XR Research Team at the American College of Greece, funded by USAID, is dedicated to pioneering research at the intersection of neuroscience and human-computer interaction within extended realities. Leveraging advanced tools such as VR/AR/XR headsets, eye-tracking systems, EEG, ECG, and GSR, our team drives innovation and fosters interdisciplinary collaboration to enhance understanding and practical applications in cognitive neuroscience, neuropsychology, and educational technology.
The overarching goal of our research program has been focusing on studying and building efficient and secure networks and systems to enable fast, reliable, private, and secure delivery and processing of information. The Smart Wireless Future Technologies (SWiFT) Lab hosts both theoretical and experimental work aimed at advancing state-of-the-art wireless technology and showcasing corresponding findings. The involved research areas include: cybersecurity; communication system design; signal processing and machine learning techniques; constrained optimization; communication theory; adaptive filtering; wireless channel modelling and estimation; spectrum sensing and sharing; positioning techniques; interference management; cooperative communications; resource allocation; cross-layer optimization; wireless relaying and intelligent reflective surfaces; wireless access and backhauling; heterogeneous networks; hybrid terrestrial / satellite networks; multi-antenna and massive MIMO systems; cloud-RAN, cell-free MIMO; antenna design; hybrid analog / digital antenna arrays; cm and mmWave systems; net-zero energy networks and non-terrestrial networks, wireless network security and policy reinforcement, among others.