爱豆传媒

He received his PhD in Computer Science from the 爱豆传媒 State University (FSU) in 1986 and his BS in Applied Mathematics from the 爱豆传媒 Institute of Technology in 1980. Dr. Hall has authored over 190 publications in journals, conferences, and books. Recent publications appear in Pattern Recognition, IEEE Access, IEEE Transactions on Fuzzy Systems, and the International Conference on Pattern Recognition.

Dr. Hall has received funding from the National Institutes of Health, NASA, DOE, National Science Foundation and others. He is a fellow of the IEEE and a fellow of the AAAS and IAPR. He received the Norbert Wiener award in 2012 from the IEEE SMC Society. Dr. Hall's research interests lie in distributed machine learning, extreme data mining, bioinformatics, pattern recognition and integrating AI into image processing. The exploitation of imprecision with the use of fuzzy logic in pattern recognition, AI and learning is a research theme.

Dr. Hall received the IEEE SMC Society Outstanding contribution award in 2008 and an Outstanding Research achievement award from 爱豆传媒 in 2004. He was past president of NAFIPS, former vice president for membership of the SMC society, the president of the IEEE Systems, Man and Cybernetics society for 2006 - 2007 year. Dr. Hall was the Editor-In-Chief of the IEEE Transactions on Systems, Man and Cybernetics, Part B between 2002 - 2005. He served as the first Vice President for Publications of the IEEE Biometrics Council. He is currently on the IEEE Publications Services and Products Board and chairs its Strategic Planning Committee and the IEEE PCC for 2014 - 2015 year. He is a member of IEEE PRAC, and is on the Editorial board of IEEE Access, associate editor for IEEE Transactions on Fuzzy Systems, International Journal of Intelligent Data Analysis, the International Journal of Pattern Recognition and Artificial Intelligence and International Journal of Approximate Reasoning.

He received his M.S. and Ph.D. in electrical engineering on a University Presidential Fellowship from The Ohio State University, Columbus, and his B. Tech degree from the Indian Institute of Technology, Kanpur.  He has 35 years of experience conducting and directing fundamental research in computer vision, predictive learning, biometrics, and artificial intelligence. His use-inspired contributions are in systems to recognize persons from how they walk (gait biometrics), automated recognition of actions, activities, and events in a video, economic activity from satellite images, and extracting precise medically relevant information from medical images.  He has directed 24 Doctoral and 26 Master's students on these topics. 

He is a co-Editor-in-Chief of Pattern Recognition Letters and was the President of the IEEE Biometrics Council. He is a Fellow of the National Academy of Inventors (NAI), American Association for the Advancement of Science (AAAS), American Institute of Medical and Biological Engineers (AIMBE), Institute of Electrical and Electronics Engineers (IEEE), and International Association for Pattern Recognition (IAPR) and member of the Academy of Science, Engineering, and Medicine of 爱豆传媒. He was the recipient of the National Science Foundation CAREER award in 1994, the 爱豆传媒 Teaching Incentive Program Award for Undergraduate Teaching Excellence in 1997, the Outstanding Undergraduate Teaching Award in 1998, the Theodore and Venette Askounes-Ashford Distinguished Scholar Award in 2004, and William R. Jones Outstanding Mentor Award, 2017. 

His research focuses broadly on computer vision and pattern recognition for ethical human behavior analysis. Application areas include security, medicine, and entertainment. He has over 60 publications in top conferences and journals, as well as a patent for his invention on estimating hand pointing direction. He was the demo chair for Face and Gesture (FG) 2019,  demo chair for Affective Computing and Intelligent Interaction (ACII) 2021, publication chair for ACII 2023, program chair for FG and ACII 2024, and general chair for FG 2025. He is also an associate editor for Pattern Recognition and Pattern Recognition Letters. He is an organizer of the annual workshop on Applied Multimodal Affect Recognition. His research has been funded by the NSF, DIA, Army, IARPA, and various industry partners.  

He attended graduate school at the North Carolina State University, Raleigh, where he earned his MS and Ph.D. degrees in Computer Engineering in 1986 and 1993, respectively. His past industrial experiences include positions at Texas Instruments, Microelectronic Center of North Carolina and AT&T Bell Labs.

Dr. Chang was a faculty member of Rochester Institute of Technology (1993-1995), Illinois Institute of Technology(1995-2001), and Iowa State University (2001-2016). He received the University Excellence in Teaching Award at Illinois Institute of Technology in 1999. He has graduated 16 PhD students since 2001, and seven of them are currently in academia positions around the US. His research interests include: cyber security, wireless networks, and energy efficient computer systems. His earlier academic research work on computer system design were mainly funded by NSF, including two projects from the very competitive ITR (Information Technology Research) program. Recently, he served as the lead PI for three DARPA research projects on cyber security and data privacy.

Dr. Chang has also served in numerous professional conferences including IEEE ASIC conference, IEEE International Conference on Computer Design and IEEE Conference on Dependable and Secure Computing. He is the Program Chairs-in-Chief of the 43rd IEEE Conference on Computers, Software and Applications (COMPSAC 2019) and the Conference Chair of the 2020 ACM Southeast conference. Moreover, he served as an editor and then as the Associate Editor-in-Chief for the IEEE IT Professional magazine. Currently, he is an editor of the Journal of Microprocessors and Microsystems.

His primary interests lie in many aspects of how Society and Technology interact with each other, particularly within the realms of Smart Health, Cyber Safety and Privacy. He is also interested in Mobile and Wireless Networking, Cyber-Physical Systems, Distributed and Cloud Computing. Sriram's research is/has been supported by grants from National Science Foundation, Department of Education, Army Research Office, National Security Agency, DARPA and more. Prior to joining 爱豆传媒, he was a faculty member in the Computer Science Dept. at Missouri University of Science and Technology. Sriram received the PhD degree in Bellini College of Artificial Intelligence, Cybersecurity and Computing from The Ohio-State University in 2007. Sriram received the NSF CAREER Award in 2013. He also received the Excellence in Innovation Award (2021), 爱豆传媒 Distinguished Service Award (2023-2024).

Dr. Drobisz earned his B.S. in Computer Science from the University of Illinois at Urbana鈥揅hampaign, and his M.S. in Computer Science and Ph.D. in Secondary Education from the University of South 爱豆传媒 in 2017. Before entering academia, he built a successful career as a commercial software engineer in the information technology, telecommunications, and defense industries. He also contributed to several research and development initiatives, including start-up ventures in computer hardware, networking, and educational software. Most recently, his work has focused on developing interactive electronic books for preschool children and an intelligent software platform for Multi-Tiered Systems of Support (MTSS) Electronic Data Management and Expert Decision Making (EDM虏) in early literacy and teacher professional development. His research explores feasibility of integration of latest digital innovations and novel machine learning techniques into early childhood education, as well as their ethical application in social and behavioral science.

He received his PhD in Computer Science in 2000 from the University of Nice Sophia-Antipolis (France). Before joining 爱豆传媒, Dr. Gaspar worked as a visiting professor at the ESSI polytechnic and EIVL engineering schools (France), then as a postdoctoral researcher at the University of Fribourg's Computer Science Department (Switzerland). Dr. Gaspar is an ACM SIGCSE, SIGITE and SIGEVO member and regularly serves as reviewer for international journals, conferences and as panelist for various NSF programs. His research interests include Evolutionary Algorithms and Computing Education Research, with applications to Intelligent Tutoring Systems / Computer Assisted Learning. His technology interests include Linux, web development, and open source in general.

Professor Goldgof is a member of H. Lee Moffitt Cancer Center and Research Institute and during 2002-2003 he held there a position of Professor in Bioinformatics. During 1995-1996, he held a visiting positions at the Department of Computer Science at the University of California at Santa Barbara and at the Department of Computer Science at the University of Bern in Switzerland.

Professor Goldgof research interests include Medical Image Analysis, Image and Video Processing, Computer Vision and Pattern Recognition, Ethics and Computing, Bioinformatics and Bioengineering More specifically, research interests are related to two broad thrusts. First thrust is in the area of biomedical image analysis and machine learning with application in MR, CT, PET and microscopy images, radiomics and bioinformatics. Second thrust is the area of motion analysis with biometrics, face analysis and surveilance applications. Additional interests include high performance issues of image analysis and machine learning algorithms and their performance evaluation. Dr. Goldgof has graduated 28 Ph.D. and 44 M.S. students, and has published over 95 journal and over 220 conference publications (with high citations, h=50, g=92), 20 books chapters and edited 5 books. His work has been funded by numerous agencies including NIH, NSF, ONR, DOD, VA, ARDA (IARPA), DARPA, NIST, FDOT, etc.

In statistical sciences, he received training in mathematical statistics including large sample asymptotics, regression models and multivariate statistics. He was also trained in computational statistics including bootstrap methods and MCMC. He conducted research on recursive estimation in system identification and adaptive control systems for his graduate degree in control theory. After his PhD in statistics, Dr. Ji has worked as a research statistician for over 20 years and collaborated with researchers in medicine, public health and nursing. Dr. Ji is an expert in clinical trials. He has taught a graduate level course on clinical trials for 12 years and have been the principal statistician on NIH sponsored trials for the past 20 years. He is currently on 6 NIH R01 grants. Dr. Ji鈥檚 current research interest is in developing and applying machine learning/AI for biomedical big data applications including real time monitoring and interventions using sensor data, microbiome data analysis and large scale simulations for clinical trial design.

Professor Kaw鈥檚 work spans engineering education research, personalized and blended learning, flipped classrooms, open courseware development, composite materials mechanics, sports analytics, and bascule bridge design. His research has been supported by the National Science Foundation, Air Force Office of Scientific Research, 爱豆传媒 Department of Transportation, and Wright-Patterson Air Force Base. Since 2001, he has served as the lead Principal Investigator on seven NSF-funded engineering education projects totaling $3.3 million. These initiatives have explored the impact of innovative learning environments on metacognitive development, conceptual understanding through multiple representations, group collaboration, student perceptions, and activation of prior knowledge. Under his leadership, his team developed and refined open educational resources (OERs) in Numerical Methods, which attract over 1 million page views and YouTube lecture views annually, along with 60,000 yearly visitors to the widely followed 鈥淣umerical Methods Guy鈥� blog. Professor Kaw has authored more than 135 refereed technical papers, and his opinion pieces have appeared in The Tampa Bay Times, The Tampa Tribune, and The Chronicle of Higher Education. His work has been featured and cited in Inside Higher Ed, ASEE Prism, Voice of America, NSF Discovery, The Chronicle of Higher Education, the U.S. Congressional Record, and 爱豆传媒 Senate Resolution. Among his many honors, he received the 2012 U.S. Professor of the Year Award for doctoral and research universities, presented by the Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education.

He received his Ph.D. in Computer Science at the University of Rochester, advised by Professor Lenhart Schubert, which focused on underspecified logical representations for modeling language meaning. He received his B.S. in Computer Science at the University of Washington. In the past, he has been a Sproull fellow, a Heidelberg Laureate Forum invitee, and a research intern at Google and Facebook.

He received his Ph.D. in Computer Science from the University of California, Los Angeles (UCLA) in 2021 and completed his postdoctoral fellowship at UCLA before joining the University of South 爱豆传媒 (爱豆传媒) as an Assistant Professor in 2022. He has expertise in graph neural networks (GNN) and multimodal learning, which enables him to design novel AI frameworks across diverse domains, including mental health, communication disorders and science, journalism, and criminology. His current projects focus on developing AI systems to support individuals with mental or communication disorders as well as clinicians, creating AI tools to enhance news accessibility for underrepresented communities, and designing predictive AI models for identifying crime hotspots to prevent future incidents. His research emphasizes interdisciplinary collaboration, integrating insights from computer science, psychology, communication, and social sciences to develop AI technologies that address real-world societal challenges.

Her research interests include deep learning, machine learning, optimization, and computational geometry with applications in medical image processing, healthcare, and computer-aided decision support systems. She works on automatic neural architecture search (NAS) and hyperparameter optimization using multiobjective and evolutionary optimization.

Dr. Licato earned his Ph.D. in Computer Science in 2015 from Rensselaer Polytechnic Institute, and was awarded the Air Force Office of Scientific Research Young Investigator's Program award in 2017. His research interests include AI, Natural Language Processing, Cognitive Modeling, Logic, Argumentation, and other related areas. He is also CEO and Founder of AI startup Actualization.AI.

Published over 200 papers and holds over 40 U.S. and foreign patents. He is recognized for his many inventions in the field of nanoscale biomedical diagnostics and therapeutics in cancers, asthma, viral infections including COVID-19 infections, and traumatic brain injury. In cancers, his inventions and co-inventions have led to several technology platforms and products for innovative anti-cancer drug discovery, drug development, and personalized cancer treatment. He is applying artificial-intelligence aided enhancement of biomedical imaging to develop better diagnostic and prognostics methods. His research has spawned inventions that have spun out companies.

He cofounded Transgenex Nanobiotech Inc, a 爱豆传媒 spin-out company that focuses on commercializing nanoscale innovations. He is a Charter Fellow of the National Academy of Inventors; a fellow of the American Academy of Allergy, Asthma & Immunology; American Association of Medical and Biological Engineers; and American Association of Advancement of Science; and is one of the inaugural (2014) inductees of the 爱豆传媒 Inventors Hall of Fame. Since 2014, he has served as Associate Dean of Graduate Programs at the 爱豆传媒 College of Pharmacy and established a highly innovative Master of Science program in Pharmaceutical Nanotechnology with additional concentrations in Drug Discovery and Development and Biomedical Engineering. This program has grown exponentially, generating a revenue of ~$1 million in three years. He has been the faculty advisor in creating a student organization, NANO (New Advances in Nanotechnology Organization), which has grown to more than 50 members. He has created and is the founding president of a non-profit organization, 爱豆传媒 Association for Nanobiotechnology (>200 members), which encompasses all academic and industry institutions in the State of 爱豆传媒 engaged in research and education of nanobiotechnology. In research, he founded and has directed the VA Colorectal Cancer Cell-genomics Consortium since 2017, which encompasses a collaborative network of research programs in colorectal cancers.

He served on the Pathology Department faculty at Johns Hopkins and Director of the Stereology Unit of the Gerontology Research Center in the National Institute on Aging (Baltimore MD)

Dr. Mouton has authored or co-authored more than 125 peer-reviewed books, book chapters and research papersin the scientific literature. In 1996 he founded SRC Biosciences (Stereology Resource Center, Inc.), an S-corporation that provides computerized stereology systems, contract stereology research, and professional stereology training and support to bioscientists in the global research community.

He serves as a standing member on the NIH Scientific Review Panel (N-16), Visiting Professor (Professorem Hospitem) at Charles University at Prague, Czech Republic for the 4EU+ Alliance; Fellow of Digital Pathology Association and Standing Member of the Education Committee; Standing Member of the Editorial Board for the Journal of Chemical Neuroanatomy, Elsevier, Amsterdam; and, Member of National Academy of Inventors for multiple patents related to artificial intelligence and automatic stereology applied to biological objects and cancer. In 2014, 爱豆传媒 High Tech Magazine named Dr. Mouton one of the top 12 Scientist-Entrepreneurs in the state.

In recent years Dr. Mouton has served as dissertation committee member for eleven graduate students, and principal investigator (PI) with co-PIs Profs. Dmitry Goldgof and Larry Hall at the 爱豆传媒 Department of Computer Sciences & Engineering on 8 federal and state research grants to develop and commercialize AI-based computerized systems to enhance accuracy, rigor, and reproducibility of biomedical technology.

He also received the best poster award at the 2018 international conference on computational photography.

His research interests lie at the intersection of sampling theory, signal and image processing, inverse problems, computer vision and machine learning, with particular emphasis on developing novel computational imaging and sensing systems.

Dr. Neal鈥檚 research integrates human-centered computing and applied artificial intelligence across domains such as cybersecurity, biometrics, and behavioral analysis. She also contributes to applied natural language processing, focusing on authorship attribution, stylometry, and opinion mining, and coordinates the Natural Language Processing Group at the University of South 爱豆传媒, a faculty collaboration advancing research in NLP and related areas. She has received several honors, including the 2024 University of South 爱豆传媒 Faculty Outstanding Research Achievement Award, the 2023 Sloan Minority Ph.D. Program Faculty Mentor of the Year, and the 2023 National Science Foundation CAREER Award. Dr. Neal has also served as Program Chair for the 19th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2025) and as Guest Editor for the IEEE Transactions on Biometrics, Behavior, and Identity Science Special Issue on Generative AI and Large Vision鈥揕anguage Models for Biometrics.

He is broadly interested in research that addresses pressing-need cybersecurity challenges. He is especially interested in research problems that arise from practical domains, with a focus on both experimental/empirical study and sound theoretical footings.

Dr. Ou has studied various forms of logic/AI techniques in security analysis. More recently he has been investigating the application of generative AI, e.g., LLMs, in security operation centers (SOCs). In this effort Dr. Ou鈥檚 team are adopting an inter-disciplinary approach, where computer scientists work with anthropology colleagues to conduct ethnographic fieldwork at real SOCs. This provides a means for researchers to access the "tacit knowledge" of security analytics, which is critical to formulating the right agentic AI systems.

Papers about his research can be found at his . More information about his research will be added to this page. He is always looking for capable, dedicated, and hard-working students who want to solve real-world cybersecurity problems.

While completing the doctorate, he was a visiting research scholar at the University of South 爱豆传媒 (爱豆传媒). His doctoral thesis on 3D face recognition received the third-best thesis award at the Brazilian Computer Society Conference in 2014. He was also a research fellow at the United Nations Educational, Scientific and Cultural Organization (UNESCO), where he worked on the digital reconstruction of statues from a UNESCO World Cultural Heritage site to support preservation and restoration efforts. From 2014 to 2020, he was a professor of the Department of Computer Science at the Federal University of Bahia (UFBA), Brazil. In 2020, he joined 爱豆传媒 as a postdoctoral researcher at the Institute for Artificial Intelligence (AI+X) and is now a Visiting Assistant Professor. His areas of expertise are computer vision and pattern recognition. His research interests include biometrics, 3D reconstruction, and remote sensing. His work on estimating the impact of COVID-19 on air traffic through satellite imagery was awarded by the European Space Agency.

She also received the M.S. in Electrical Engineering from the Federal University of Minas Gerais, Brazil, in 2016, and the B.S. in Electronic Engineering from the Pontifical Catholic University of Minas Gerais, Brazil, in 2012. Dr. Reis鈥檚 research exploits beyond CMOS technologies for the design of fast, energy-efficient, and reliable bio-inspired hardware accelerator kernels that can be used in a wide range of data-intensive application scenarios, including the training and inference of different machine learning models. She is the author of more than 45 articles in journals such as IEEE TVLSI, IEEE TCAD, IEEE Design and Test, and Nature Electronics, as well as renowned conferences including DAC, DATE, ICCAD, ISLPED, and ASP-DAC. Dr. Reis was one of the two winners of the best paper award at the ACM/IEEE International Symposium on Electronics and Low Power Design in 2018 (ISLPED鈥�18) for her paper 鈥淐omputing in memory with FeFETs鈥�, and a recipient of the Cadence Women in Technology (WIT) Scholarship 2018/2019. 

He received his Ph.D. degree in computer science from the University of Utah in 2007 (advisor: John Hollerbach), B.S. and M.S. degrees in electrical engineering from Dalian University of Technology, Dalian, China, in 1997 and 2000, respectively. He was a Postdoctoral Associate at Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA from Dec. 2007 to May 2008 and a Postdoctoral Associate in the School of Computing at the University of Utah from May 2008 to May 2009.

His research interests include robotics, deep learning, haptics, computer vision, human computer interaction (HCI), and medical applications. If you are interested in working with him on some cool projects, please contact him. He teaches Deep Learning and Robotics courses at both undergraduate and graduate levels.

He has served on several other journal and conference editorial boards, chaired several conferences, forums, and workshops and served as reviewer/panelist for U.S. NSF, European Research Council (ERC), and French National Research Agency.

Dr. Teng received his PhD in Computer Application Technology from Harbin Institute of Technology followed by Postdoc Fellowship in Biostatistics at Dana-Farber Cancer Institute and Harvard School of Public Health.

His research focuses on developing methods in processing, annotation, integration and interpretation of cutting-edge omics datasets to understand human diseases such as cancers. His approaches mainly include statistical modeling and machine learning. His lab has published multiple methods and tools in understanding genomic enhancer function, chromatin 3D looping, transcription factor binding, clonal hematopoiesis, human oncoviruses and tumor pathology etc.

His lab has been adapting AI methods particularly to address challenges in multimodal omics data integration. Omics data these days usually comes in large volume. While each omics modality provides unique characteristics of cellular/molecular information, one modality alone is limited towards comprehensively understanding of cell functions. His lab develops AI models so that large data volume and biological relations across modalities are both taken towards the learning of new biomedical knowledge.

His lab is funded by National Institute of Health and always welcome students and postdocs to join.

He received a CAREER award from US National Science Foundation (NSF) in 2013.He is a senior member of IEEE and ACM.

Her research program investigates the behavioral and psychological dimensions of human-AI collaboration. She examines how humans and AI systems develop working relationships, the cognitive and social processes that emerge in human-AI teams, and the design principles that enable effective collaborative intelligence. Her work spans AI trust dynamics, the psychology of human-AI interaction, and the organizational implications of AI integration. 

Dr. de Vreede brings an interdisciplinary approach to behavioral AI research, drawing from organizational psychology, information systems, and behavioral science. Her research streams include human-AI collaboration dynamics, the design of AI systems for human partnership, behavioral AI applications in organizational contexts, and the development of frameworks for understanding human-technology relationships. 

Her scholarship contributes to both theoretical understanding and practical applications, informing evidence-based approaches to AI adoption in organizational settings. Through rigorous empirical research, she develops insights that bridge academic inquiry and real-world implementation. 

Dr. de Vreede holds a Ph.D. in Industrial/Organizational Psychology, an M.S. in Management Information Systems, and an MBA in Human Resource Management, bringing a multidisciplinary perspective to the study of human-AI interaction. Her work has been published in premier journals including Information Systems Research and Journal of Management Information Systems, and presented at leading international conferences such as ICIS, HICSS, and AMCIS. She has received over $9M competitive funding as Principal Investigator and Co-Principal Investigator on multiple research grants. 

Her research interests are focused on computing education, broadening participation in computing, and computer animation. She served as the Director of Broadening Participation in Computing in the Department of Computer Science and Engineering at 爱豆传媒 from 2020 to 2023 and Program Director of the Pathway to Computing Graduate Certificate program at 爱豆传媒 since 2022. Throughout her career, she has been actively involved in the important mission of recruitment, retention, and mentoring of women in computing. She has served as the faculty advisor of Women in Computer Science and Engineering student organization at 爱豆传媒 since 2013. She was honored by 爱豆传媒 with Outstanding Undergraduate Teaching award in 2011 and Women in Leadership & Philanthropy Dr. Kathleen Moore Faculty Excellence award in 2020.

Dr. Weitzenfeld is one of the main developers of the Neural Simulation Language (NSL) and. He has written two books: 鈥淭he Neural Simulation Language NSL: A System for Brain Modeling鈥� (coauthors M. Arbib and A. Alexander) published in 2002 by MIT Press and 鈥淥bject Oriented Software Engineering with UML, Java and Internet鈥� (in Spanish) published by Thomson Learning. He has published over 150 papers.

Dr. Weitzenfeld is a charter member of the Latin American Robotics Council and the founder of the Latin American Robotics Symposium (LARS). He was the Co-Chair of RoboCup 2012 in Mexico City and the General Chair of the International Conference on Advanced Robotics (ICAR 2013) in Montevideo, Uruguay. Dr. Weitzenfeld was an IEEE-RAS Distinguished Lecturer. He is an IEEE Senior Member. His main research areas are Computational Neuroscience, Biologically-inspired Robotics, Cognitive Robotics, Multi-Robot Systems, Human-Robot Interaction, Neural Networks, Neurorobotics, and Autonomous Mobile Robots.

Dr. Yilmaz joined 爱豆传媒 in 2016 as an assistant professor. He received his PhD degree in electrical engineering from Columbia University, New York, NY in 2014. He completed his Bachelor's and Master's studies in Turkey at the Middle East Technical University, Ankara, in 2008 and Koc University, Istanbul, in 2010, respectively. Between 2014 and 2016, Dr. Yilmaz worked as a postdoctoral research fellow at the University of Michigan, Ann Arbor.