Associate Professor, Electrical and Computer Engineering, Associate Professor, BIO5 Institute
Ali Akoglu is an Associate Professor in the Department of Electrical and Computer Engineering and the BIO5 Institute at the University of Arizona. He received his Ph.D. degree in Computer Science from the Arizona State University in 2005. He is the site-director of the National Science Foundation (NSF), Industry-University Cooperative Research Center on Cloud and Autonomic Computing regarding the design and development of architectures for achieving self-management capabilities across the layers of cloud computing systems. Dr. Akoglu is an expert in high performance scientific computing and parallel computing with a primary focus on restructuring computationally challenging algorithms for achieving high performance on parallel hardware architectures. His research projects have been funded by the National Science Foundation, Defense Advanced Research Projects Agency, Office of Naval Research, US Air Force, NASA Jet Propulsion Laboratories, Army Battle Command Battle Laboratory, and industry partners such as Nvidia and Raytheon.
Professor, BIO5 Institute, Professor, Management Information Systems, Regents Professor
Assistant Professor, Agricultural-Biosystems Engineering, Assistant Professor, BIO5 Institute, Assistant Professor, Genetics - GIDP, Assistant Professor, Statistics-GIDP, Clinical Instructor, Pharmacy Practice-Science
Our lab focuses on large-scale –omics datasets, high-throughput computing, and big data analytics. We leverage these technologies to answer questions related to the relationship between microbes, their hosts, and the environment. In particular, we focus on viral-host interactions and co-evolution given environmental factors (i) in aquatic systems and (ii) for phage treatment of diabetic foot ulcers.
Director, Cyber Innovation, Director, Data Science Institute
Professor, BIO5 Institute, Professor, Computer Science
Professor, BIO5 Institute, Professor, Computer Science, Professor, Management Information Systems, Professor, Remote Sensing / Spatial Analysis - GIDP
My research is on Machine Learning and Network Science based methods to harness the power of big data and analytics. I use these methods to develop prediction models both at the population and individual levels to help organizations and individuals make better-informed decisions about health care.