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Ghulam Mujtaba, Ph.D., is an Assistant Professor in the Department of Marketing and Data Sciences at Regis University, Denver, Colorado. He holds a Ph.D. in Computer Engineering from Gachon University, South Korea, earned with Summa Cum Laude distinction and the President's Award for Academic Excellence.
His research spans responsible AI, edge computing, computer vision, large language models, and multimedia retrieval. These interests are reflected in more than 20 peer-reviewed publications in leading venues, including IEEE Transactions on Big Data, IEEE Internet of Things, Information Fusion, and IEEE Access. Additionally, his doctoral work resulted in a granted U.S. patent for personalized semantic video streaming technology. He also serves as Guest Editor for a special section on Agentic AI in IEEE Transactions on Consumer Electronics.
His work has been recognized internationally through the ICCV 2021 Doctoral Consortium Fellowship, the Korea Transportation Safety Authority Chairman Award, and an Outstanding Research Award from Sungkyunkwan University (SKKU), South Korea.
Evan Gibson is Co-Founder of Soresu, a Colorado defense technology startup building distributed AI systems for national security missions. His background includes serving as Chief Data Scientist on multiple defense programs and leading machine learning, GEOINT, and data fusion efforts involving the NGA, NRO, DIA, the Air Force, and other defense customers.
He is a plank holder for DIA MARS and has served as a lead data scientist advising the Department of the Air Force Chief Data and AI Office. His applied imagery work has spanned EO, SAR, and other sensing modalities for ground and space applications, including object recognition and classification, change detection, and anomaly characterization. At Soresu, Evan’s current work focuses on SWIFT-A, a distributed inference and fusion system that helps sensors, models, and compute nodes coordinate when networks are degraded, intermittent, or unreliable.
Soresu is a Catalyst Accelerator alum and has worked with the SDA Tap Lab, the Air Force, the Space Force, and other partners on demonstrations involving resilient sensing, custody, and autonomous coordination. Evan’s work centers on a practical question for applied AI: how do we build systems that still work when the real world stops looking like the lab?
Ronald M. Summers, M.D., Ph.D., is a tenured Senior Investigator and Staff Radiologist in the Department of Radiology and Imaging Sciences at the NIH Clinical Center in Bethesda, Maryland. He leads the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory.
Dr. Summers is a Fellow of the Society of Abdominal Radiologists, the American Institute for Medical and Biological Engineering, and SPIE. His honors include the Presidential Early Career Award for Scientists and Engineers, the NIH Director’s Award, and the NIH Ruth L. Kirschstein Mentoring Award.
He serves on the editorial board of the Journal of Medical Imaging and previously served on the editorial boards of Radiology, Radiology: Artificial Intelligence, and Academic Radiology. He has co-authored more than 700 journal articles, reviews, book chapters, and conference proceedings and is a co-inventor on 17 patents.
His research interests include thoracic and abdominal imaging, large radiology image databases, and artificial intelligence.
In this talk, Dr. Summers will present examples of how multimodal language models can improve labeling efficiency in large clinical datasets, integrate clinical knowledge from text and images, and improve AI models for radiology diagnosis. Use cases involving the diagnosis of diabetes, liver disease, and organ failure will be presented, along with AI models for survival prediction.
Dr. Paul Cerkez is an Assistant Professor (Adjunct) in the Department of Computing Sciences at Coastal Carolina University. He completed his doctoral research focusing on artificial intelligence technologies in 2012 and was inducted as a member in 2007 into the UPE (Upsilong Pi Epsilon), the International Honor Society for Computing and Information Disciplines. His dissertation research focused on detecting hidden messages in the visual content of images and graphics (Automated Detection of Semagram Laden Images). He has been a committee member of the AIPR since 2013 in the role of chairman of Student Best Paper/Poster Awards. He was awarded the Innovative Application of Artificial Intelligence (IAAI) by the American Association of Artificial Intelligence (AAAI) on two occasions.
Dr. Cerkez is a retired United States Marine, serving from 1975 to 1997. He was a software developer and manager for DCS Corporation. His experience includes more than 28 years of direct computer experience in the development of custom software, more than 22 years of Naval Aviation avionics experience in the areas of general aviation electronics support and automated test equipment, as well as project manager/developer for multiple artificial intelligence logistics planning and configuration management software packages. Some of his past work included an Army Research Lab (ARL) project to develop the cognitive decision process model for a role-based modeling and simulation environment. From 2005 to 2011, he was the lead logistics Subject Matter Expert (SME) supporting the software development for onboard diagnostics and off-board analysis systems for the new CH-53K helicopter. He later worked with the Navy’s UH-60 helicopter program as a contracted software SME for NAVAIR. Most recently he has been active on the software engineering team for two programs. In one case, he led the logistics team in developing a plan for software development and software licensing of a wide variety of aircraft related software products. The other project involved developing an entire system, including the web front end and database back end, which allows analysis of sensitive data. He was an adjunct professor of computer science for Florida Institute of Technology. Since the award of his Ph.D. in 2012, he had been a dissertation committee member for multiple students at Nova Southeastern University. His future research goals are an extension of his dissertation work with a hybrid neural network (HNN).
Anticipated Keynote Speaker organizations include USGIF and Syntiant Corporation; more detailed information on the presentations by Keynote Speakers will come soon. We have space for other Keynote Speakers, and nominations and volunteers should reach out to us at program-chairs@aipr-workshop.org.
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