REU Sites: Collaborative Research: Advances of Machine Learning in Theory & Applications (AMALTHEA)

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Title: REU Site: Collaborative Research: Advances of Machine Learning in Theory and Applications (AMALTHEA)PI: Georgios C Anagnostopoulos Institution: Florida Institute of TechnologyPI: Michael GeorgiopoulosInstitution: University of Central FloridaAMALTHEA is a collaborative effort between two closely-located universities, Florida Institute of Technology in Melbourne and University of Central Florida in Orlando, Florida. The project seeks to provide top quality educational experiences to a diverse community of learners through research participation in the area of Machine Learning (ML). Machine Learning is nowadays a high-importance, ever- expanding discipline that draws concepts from a variety of fields, including artificial intelligence, cognitive sciences, information theory, statistics, mathematics, physics, philosophy and biology among others. On the other hand, automatic target recognition, earthquake prediction, gene expression discovery, intelligent credit fraud protection and affectionate computing, to mention just a few, are examples of cutting-edge applications of ML in various technological and scientific domains. The project's thrust area is the theory of ML and how it can be integrated and applied to important real-life problems, thus exposing participants to both theory and applications.AMALTHEA involves ten undergraduate students annually in ML research over ten weeks in the summer. Overall, the project will impact a diverse group of 30 students, as well as 12 graduate students, which will participate in undergraduate teaching and mentoring activities. The undergraduate students perform supervised research on ML topics that have the potential to impact the field of ML itself, as well as how ML is applied to other scientific disciplines. REU research results are expected to be published in interdisciplinary conferences, and, potentially, technical journals. Additionally, these REU research advances are fed back and integrated into the teaching of ML-related courses at the partnering institutions.The project involves four faculty who have significant overall experience in ML research and education; they have mentored over 50 undergraduates in research and co-authored over 20 conference and journal papers with them. The project is also supported in its endeavors by an actively participating Advisory Board consisting of industry and government professionals with interest and expertise in ML.URL: http://my.fit.edu/amalthea