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Artificial Intelligence<\/h2>\n\n\nResearch in the Monmouth University Computer Science and Software Engineering Department falls into the following areas:<\/p>\n\n\n
Artificial Intelligence<\/h2>\n\n\nAI can be described as the study of systems that process data that are usually non-numeric, such as text and images, in such a way that we can extract patterns and information (meanings) from them. We use techniques in natural language processing, information retrieval, information extraction, machine translation, machine learning, data mining, cognitive science, and the semantic web, to name a few.<\/p>\n\n\n\n
Associated faculty:<\/p>\n\n\n\n
According to the American Medical Informatics Association, biomedical informatics is an emerging and interdisciplinary field that studies the effective uses of biomedical data, information, and knowledge to improve human health. Research in the department is focused on biomedical ontologies, which are controlled vocabularies of well-defined terms connected by relationships. Biomedical ontologies are developed to express data in ways that computers can understand the meanings, in order to facilitate biomedical data sharing and knowledge discovery, thus improving healthcare and biomedical research.<\/p>\n\n\n\n
Associated faculty:<\/p>\n\n\n\n
Cybersecurity encompasses the measures and practices implemented to protect systems, networks, data, and individuals from unauthorized access, misuse, and potential threats. It involves a combination of technological safeguards, such as encryption, firewalls, and intrusion detection systems, alongside procedural strategies like access controls, user authentication, and regular audits. Effective security ensures the confidentiality, integrity, and availability of critical information, defending against cyber-attacks, data breaches, and other malicious activities. Penetration testing will be used to detect potential vulnerabilities of systems. Additionally, program analysis can also protect the security.<\/p>\n\n\n\n
Associated faculty:<\/p>\n\n\n\n
Nowadays, huge amounts of digital data are generated in many domains (social networks, urban environments, scientific fields, business domains) and their volumes are growing faster than ever before. According to several studies, by the year 2020 about 1.7 MegaBytes of new information will be created every second for every human being on the planet. Such huge volume of data (i.e., Big Data) can be analyzed and exploited by data analytics algorithms to discover hidden and valuable information (i.e., predictive and descriptive models, patterns, regularities) concerning human dynamics and behaviors, and leading to useful applications in both business and scientific fields.<\/p>\n\n\n\n
Associated faculty:<\/p>\n\n\n\n
In computer science, the theories and methods that relate to the storage and retrieval of large collections of data continues to be a fertile area of research. Database research in the department is focused in the areas of database management <\/em>and information retrieval.<\/em><\/p>\n\n\n\n Associated faculty:<\/p>\n\n\n\n Emergency management is a process by which all individuals, groups, and communities manage hazards in an effort to avoid or ameliorate the impact of disasters resulting from the hazards. It involves four phases: mitigation, preparedness, response, and recovery. Mitigation efforts attempt to prevent hazards from developing into disasters altogether, or to reduce the effects of disasters when they occur. In the preparedness phase, emergency managers develop plans of action for when the disaster strikes, and analyze and manage required resources. The response phase executes the action plans, which includes the mobilization of the necessary emergency services and dispatch of first responders and other material resources in the disaster area. The aim of the recovery phase is to restore the affected area to its previous state. Effective emergency management relies on thorough integration of emergency plans at all levels of government and non-government involvement.<\/p>\n\n\n\n Associated faculty:<\/p>\n\n\n\n A formal method is a mathematic method that uses formal language in the specification, design, construction, and verification of computer systems and software. Formal languages include logic, Petri nets, finite state machines, statecharts, and so on. The development of a formal specification provides insights and an understanding of the software requirements and software design. Since software specifications are mathematical entities and may be analyzed using mathematical methods.<\/p>\n\n\n\n Associated faculty:<\/p>\n\n\n\n The area of computer science that focuses on the study of multiple computer systems that are connected together using a telecommunication system for data and resource sharing and communication. Networks research in the department is focused in the areas of wireless communications<\/em>, telecommunications<\/em>, network security<\/em>, and network algorithms<\/em>.<\/p>\n\n\n\n Associated faculty:<\/p>\n\n\n\n Quantum computing is an emerging technology that uses the\u00a0principles of quantum mechanics to help solve problems that our current computers are unable to solve. It uses qubits, the basic quantum unit of information that can be 0, 1, or a superposition of both, to be able to generates solutions to complex problems faster than current computers will ever be able to achieve. Quantum computing is poised to revolutionize a huge variety of fields including cybersecurity, medicine, artificial intelligence (AI) and machine learning (ML), and finance. Quantum practitioners stand at the forefront of what is possible for knowledge development. At Monmouth, all students beginning freshman year can do real-world hands-on research with this exciting new technology that has global excitement.<\/p>\n\n\n\n Associated faculty:<\/p>\n\n\n\n\n
Emergency Management<\/h2>\n\n\n
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Formal Methods<\/h2>\n\n\n
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Networks<\/h2>\n\n\n
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Quantum Computing<\/h2>\n\n\n