Institute for Artificial Intelligence

AI+X Directors

Dr. Lawrence Hall

Dr. Lawrence Hall

Computer Science and Engineering

Dr. Lawrence Hall is a distinguished university professor of Computer Science and Engineering at University of South Florida (USF) in Tampa, FL. He received his PhD in Computer Science from the Florida State University (FSU) in 1986 and his BS in Applied Mathematics from the Florida 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 USF 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.

Dr. Sudeep Sarkar

Dr. Sudeep Sarkar

Computer Science and Engineering

Dr. Sudeep Sarkar is a professor and Department chair of Computer Science and Engineering and Associate Vice President for Research & Innovation at the University of South Florida (USF) in Tampa, FL. He received his MS and PhD degrees in Electrical Engineering, on a University Presidential Fellowship, from The Ohio State University. He is the recipient of the National Science Foundation CAREER award in 1994, the USF Teaching Incentive Program Award for Undergraduate Teaching Excellence in 1997, the Outstanding Undergraduate Teaching Award in 1998, and the Theodore and Venette Askounes-Ashford Distinguished Scholar Award in 2004. He is a Fellow of the American Association for the Advancement of Science (AAAS), Institute of Electrical and Electronics Engineers (IEEE), American Institute for Medical and Biological Engineering (AIMBE), and International Association for Pattern Recognition (IAPR); and a charter member and member of the Board of Directors of the National Academy of Inventors (NAI). He has 25 year expertise in computer vision and pattern recognition algorithms and systems, holds three (3) U.S. patents and has published high-impact journal and conference papers.

He has more than 25 years of experience conducting and directing fundamental and applied research in computer vision, image processing, and pattern recognition related topic. His research topics ranged from video image processing to biometrics and medical image analysis of burn scars. With series of funding from the National Science Foundation, he has made seminal algorithmic and theoretical contributions to the field computer vision, particularly in the problem of computing perceptual organization, sign language recognition, and more recently in event understanding using pattern theory.

With funding from DARPA HumanID at a Distance program, US Army and STS Intl., SOCOM (via USF-NSF I/UCRC Center), Unisys Corporation, CIA, and Raytheon Inc., he has made many seminal contributions to the field of biometrics, i.e. using physical and behavioral properties of humans to identify them. He is considered the world leader in gait biometrics and is frequently called upon to participate in world meetings regarding this topic. The benchmark developed by him is the defacto standard in the development of gait recognition algorithms.

AI+X Researchers

Dr. Shaun Canavan

Dr. Shaun Canavan

Computer Science and Engineering

Dr. Canavan received his PhD in Computer Science from Binghamton University. He is an Assistant Professor in the Computer Science and Engineering Department at the University of South Florida. His research focuses on Affective Computing, Human-Computer Interaction, Biometrics and VR/AR. He is a recipient of an AWS Machine Learning Research Award for studying multimodal human emotion analysis using deep neural networks. He has over 35 publications in top conferences and journals, as well as has a patent for his invention on estimating hand pointing direction. He was the demo chair for Face and Gesture 2019, and is currently the demo chair for Affective Computing and Intelligent Interaction 2021. He is also serving on multiple technical committees for conferences and journals. He is an organizer of the 1st workshop on Ubiquitous Emotion Recognition with Multimodal Mobile Interfaces at UbiComp 2018, as well as an organizer of the 1st workshop on Applied Multimodal Affect Recognition at Face and Gesture 2020.

Dr. Morris Chang

Dr. Morris Chang

Electrical Engineering

Morris Chang is a professor at the University of South Florida, Tampa. He received his BS degree in Electrical Engineering from Tatung University,Taiwan, in 1983. 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.

Dr. Sriram Chellappan

Dr. Sriram Chellappan

Computer Science and Engineering

Sriram Chellappan is a Professor in The Department of Computer Science and Engineering at University of South Florida, where he directs the SCoRe (Social Computing Research) Lab. 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 USF, he was a faculty member in the Computer Science Dept. at Missouri University of Science and Technology. Sriram received the PhD degree in Computer Science and Engineering from The Ohio-State University in 2007. Sriram received the NSF CAREER Award in 2013. He also received the Missouri S&T Faculty Excellence Award in 2014, the Missouri S&T Outstanding Teaching Commendation Award in 2014, and the Missouri S&T Faculty Research Award in 2015.

Dr. Jack Drobisz

Dr. Jack Drobisz

Behavioral and Community Sciences

Dr. Drobisz received his MS in Computer Science and a PhD in Secondary Education from University of South Florida in 2017. He is currently a researcher and resident software architect at College of Behavioral and Community Sciences. His research interests include educational frameworks and exploration of novel approaches to learning based on digital innovations (e.g. artificial intelligence and machine learning). Before receiving his doctorate degree, Dr. Drobisz has pursued a commercial software engineering career in information technology, telecom and defense industries, and engaged in a number of research and development projects, including three start-up companies in computer hardware, networking and educational software. Most recently he has been working on an intelligent software platform for Multi-Tiered System of Supports (MTSS) Electronic Data Management and Expert Decision Making (EDM 2 ) in early literacy & teacher professional development. His work involves exploration of ways to adapt new machine learning approaches to educational software and social-behavioral research.

Dr. Alessio Gaspar

Dr. Alessio Gaspar

Computer Science and Engineering

Dr. Alessio Gaspar is an associate professor in the Department of Computer Science and Engineering at the University of South Florida (USF) in Tampa, FL. He leads the USF Computing Education Research & Adult Learning group, and serves as coordinator for the USF BSIT Linux Technologies specialization track. He received his PhD in Computer Science in 2000 from the University of Nice Sophia-Antipolis (France). Before joining USF, 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.

Dr. Dmitry Goldgof

Dr. Dmitry Goldgof

Computer Science and Engineering

Dmitry B. Goldgof has received the M.S. degree in Computer and Systems Engineering from the Rensselaer Polytechnic Institute and the Ph.D. degree in Electrical Engineering from the University of Illinois at Urbana-Champaign. He is currently Professor and Vice Chair in the Department of Computer Science and Engineering at the University of South Florida Department of Oncological Sciences, USF Health. 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.

Dr. Ming Ji

Dr. Ming Ji

Biostatistics

Dr. Ming Ji was trained in mathematics, control theory, and statistical sciences. He studied all the modern mathematics graduate courses for Math PhD including measure theory, functional analysis, differential manifolds, numerical analysis, optimization theory and partial differential equations. 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’s 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.

Dr. Autar Kaw

Dr. Autar Kaw

Mechanical Engineering

Autar Kaw is a professor of mechanical engineering at the University of South Florida. He is a recipient of the 2012 U.S. Professor of the Year Award (doctoral and research universities) from the Council for Advancement and Support of Education and the Carnegie Foundation for Advancement of Teaching. His primary scholarly interests are engineering education research, adaptive, blended, and flipped learning, open courseware development, composite materials mechanics, and higher education's state and future. His work in these areas has been funded by the National Science Foundation, Air Force Office of Scientific Research, Florida Department of Transportation, and Wright Patterson Air Force Base. Funded by National Science Foundation, under his leadership, he and his colleagues from around the nation have developed, implemented, refined, and assessed online resources for open courseware in Numerical Methods (http://nm.MathForCollege.com). This courseware annually receives 1M+ page views, 1.6M+ views of the YouTube lectures, and 90K+ visitors to the "numerical methods guy" blog. This body of work has also been used to measure the impact of the flipped, blended, and adaptive settings on how well engineering students learn content, develop group-work skills, and perceive learning environment. He has written over 120 refereed technical papers, and his opinion editorials have appeared in the Tampa Bay Times, the Tampa Tribune, and the Chronicle Vitae.

Dr. Gene Louis Kim

Dr. Gene Louis Kim

Computer Science and Engineering

Gene Louis Kim is an Assistant Professor in the Department of Computer Science and Engineering at the University of South Florida (USF). His research aims to integrate the benefits of neural and symbolic methods for modeling language meaning which supports automatic parsing and computer reasoning while being informed by semantic analysis from Linguistics. 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.

Dr. Seungbae Kim

Dr. Seungbae Kim

Computer Science and Engineering

Seungbae Kim is an assistant professor at the Department of Computer Science and Engineering at the University of South Florida (USF). His research focuses on developing applicable AI methods using multimodal inputs to solve societal problems in an interdisciplinary manner. More specifically, He has expertise in graph neural networks (GNN) and multimodal learning which allows him to propose novel machine-learning frameworks in various domains including mental health, communication, and marketing. During his Ph.D. and postdoctoral fellowship, he collaborated with scholars in different fields, for example, he developed several machine learning models to detect depression symptoms using visual and acoustic features, to predict suicide risk levels using social relationships between mental health community users. After joining USF as an assistant professor in 2022, he initiated new research projects with experts in other fields at USF, including communication disorder, journalism, and psychology. He received a Ph.D. degree in the Department of Computer Science from the University of California, Los Angeles in 2020.

Dr. Susana Lai-Yuen

Dr. Susana Lai-Yuen

Industrial and Management Systems Engineering

Susana Lai-Yuen is an Associate Professor of Industrial and Management Systems Engineering at the University of South Florida. She received her Ph.D., M.S., and B.S. (Summa Cum Laude) degrees in Industrial Engineering from North Carolina State University. 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. John Licato

Dr. John Licato

Computer Science and Engineering

Dr. John Licato is an Assistant Professor in the Department of Computer Science and Engineering, and Director of the Advancing Machine and Human Reasoning (AMHR) lab, whose mission is to not only make AI better at reasoning, but to help people reason better as well. 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.

Dr. Shyam S. Mohapatra

Dr. Shyam S. Mohapatra

Internal Medicine

Shyam S. Mohapatra, PhD, MBA has had a distinguished career in academia in research, teaching, and service at USF since 1996. He is currently, the Director of Translational Medicine at the Department of Internal Medicine and Research Career Scientist at the James A Haley VA Hospital, Tampa, FL.

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 USF 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 Florida Inventors Hall of Fame. Since 2014, he has served as Associate Dean of Graduate Programs at the USF 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, Florida Association for Nanobiotechnology (>200 members), which encompasses all academic and industry institutions in the State of Florida 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.

Dr. Peter R. Mouton

Dr. Peter R. Mouton

Stereology

Peter R. Mouton, Ph.D. is a neuroscientist, stereologist, inventor, entrepreneur and founder of SRC Biosciences based in Tampa, Florida. He earned bachelor degrees in Biology and Chemistry at the University of South Florida (USF, Tampa campus), masters and doctoral degrees at USF, the Karolinska Institute (Stockholm, Sweden) and the Johns Hopkins University School of Medicine (Baltimore, MD), and completed postdoctoral studies in neuropathology at the Johns Hopkins Department of Pathology, the University of Copenhagen (Denmark) and the Instituto de Ramon y Cajal (Madrid, Spain). 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 100 peer-reviewed books, book chapters and research articles in 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 ETTN-11) “Drug Discovery for Aging, Neuropsychiatric and Neurologic Disorders;” 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 applications of automatic stereology to biological objects and cancer. In 2014 Florida High Tech Magazine named Dr. Mouton one of the top 12 Scientist-Entrepreneurs in the state.

In recent years Dr. Mouton has served as principal investigator (PI) together with co-PIs Profs. Dmitry Goldgof and Larry Hall at the USF Department of Computer Sciences & Engineering on 8 federal and state research grants to develop and commercialize the first deep learning-based computerized systems for automatic stereology of stained tissue sections.

Dr. John Murray-Bruce

Dr. John Murray-Bruce

Computer Science and Engineering

John Murray-Bruce, PhD is an Assistant Professor in the Department of Computer Science and Engineering, University of South Florida, Tampa. He received both the MEng with honors (2012) and the PhD (2016) degrees in Electrical and Electronic Engineering (EEE) from Imperial College London, UK, where he was awarded the Maurice Hancock Prize in 2008, and the Institute of Engineering and Technology (IET) Prize for 'best all-round performance' in 2012. 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. Tempestt Neal

Dr. Tempestt Neal

Computer Science and Engineering

Dr. Neal is an assistant professor and principal investigator of the Cyber Identity and Behavior Research Lab in the Computer Science and Engineering Department at the University of South Florida. She earned a Ph.D. in computer engineering from the University of Florida. Her research focuses on behavioral biometric authentication for IoT and mobile device users, applications of ubiquitous sensing, and authorship analysis and stylometry. She was awarded the Delores Auzenne Dissertation Award from the University of Florida and selected as a NSF CyberCorp Fellow for her dissertation work focused on the feasibility of mobile device usage data as a biometric modality. Dr. Neal currently serves as the IEEE Biometrics Council Liaison for IEEE Women in Engineering and Associate Editor for the IEEE Biometrics Council Newsletter. She was the Local Arrangements Chair for the 2019 IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) and served as a Session Chair at the 2019 IAPR International Conference on Biometrics (ICB). She is co-organizer of the First Workshop on Applied Multimodal Affect Recognition to be held at the IEEE International Conference on Automatic Face and Gesture 2020 and Identity for Social Good at IJCB 2020.

Dr. Xinming (Simon) Ou

Dr. Xinming (Simon) Ou

Computer Science and Engineering

Xinming (Simon) Ou 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. He has studied various forms of logical techniques in security analysis of complex systems, which led to the MulVAL network security analyzer, and the SnIPS intrusion analysis tool.

More recently he has been studying the problem of incident response/forensics analysis to understand how this process can benefit from systematic modeling and automation, grounded on sound theories of reasoning under uncertainty. In this effort we are adopting an inter-disciplinary approach, where we work with our anthropology colleague to conduct ethnographic fieldwork at real security operation centers. This provides a means for researchers to access the "tacit knowledge" of security analytics, which is critical to formulating the right models and algorithms. He is also interested in cloud computing and am investigating a new cloud service architecture that offers both security and manageability benefit, using the idea of moving-target defense. Another area of my current research is security of mobile computing systems such as Android, and how to combine static analysis and policy enforcement to achieve desired security properties. He is also working on cyber-physical system (CPS) security with a focus on designing a framework for ensuring security/safety properties of different types of CPSes through a unified secure real-time operating system (RTOS) platform.

Papers about his research can be found at his publications page. More information about his research will be added to this page. Meanwhile you are welcome to visit the website of his research group Argus. He is always looking for capable, dedicated, and hard-working students who want to solve real-world cybersecurity problems.

Dr. Mauricio Pamplona Segundo

Dr. Mauricio Pamplona Segundo

Computer Science and Engineering

Mauricio Pamplona Segundo received the bachelor's degree in Computer Science (2004-2007), master's degree in Informatics (2008-2010) and doctoral degree in Computer Science (2010-2013) from the Federal University of Paraná (UFPR), Brazil. While completing the doctorate, he was a visiting research scholar at the University of South Florida (USF). 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 USF 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.

Dr. Dayane Reis

Dr. Dayane Reis

Computer Science and Engineering

Dr. Dayane Reis is an assistant professor in the Department of Computer Science and Engineering, University of South Florida (USF) in Tampa, FL. Dr. Reis received her Ph.D. in Computer Science and Engineering from the University of Notre Dame in 2022, under the direction of Dr. Xiaobo Sharon Hu and Dr. Michael Niemier. 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’s 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 30 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’18) for her paper “Computing in memory with FeFETs”, and a recipient of the Cadence Women in Technology (WIT) Scholarship 2018/2019, in recognition to her efforts toward the inclusion of women in STEM fields.

Dr. Ankit Shah

Dr. Ankit Shah

Industrial and Management Systems Engineering

Dr. Ankit Shah is an Assistant Professor of Industrial and Management Systems Engineering at the University of South Florida. His research interests lie at the intersection of Computer Science, Operations Research, and Information Technology with a focus on cybersecurity issues of societal concern. Dr. Shah’s research focuses on the development of AI-based decision support systems that assist decision-makers in the process of analyzing collected data, identifying critical information such as cyber vulnerabilities and threats, and prescribing optimal mitigation actions.

He uses combinatorial optimization, approximate dynamic programming and deep reinforcement learning methodologies for decision-making under uncertainty.

Dr. Yu Sun

Dr. Yu Sun

Computer Science and Engineering

Yu Sun is a Professor and Associate Chair of Graduate Affairs in the Department of Computer Science and Engineering at the University of South Florida (2009-2015 Assistant Professor, 2015-2020 Associate Professor). He was a Visiting Associate Professor at Stanford University from 2016 to 2017.

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. Mingxiang Teng

Dr. Mingxiang Teng

Moffitt Cancer Center

Mingxiang Teng is an Assistant Member of Biostatistics and Bioinformatics at the Moffitt Cancer Center. He received his PhD in Computer Application Technology from Harbin Institute of Technology. He had his postdoctoral training in Biostatistics and Computational Biology at Dana-Farber Cancer Institute and Harvard School of Public Health. His current research focuses on developing methodology, tools and software to address data challenges posed by modern biological studies.

Dr. Yicheng Tu

Dr. Yicheng Tu

Computer Science and Engineering

Yi-Cheng Tu is a full professor in the Department of Computer Science & Engineering at University of South Florida. His research interest is in database management systems, and high performance computing, and the application of such systems in big data and AI. He received a CAREER award from US National Science Foundation (NSF) in 2013.He is a senior member of IEEE and ACM.

Dr. Triparna de Vreede

Dr. Triparna de Vreede

School of Information Systems and Management

Dr. Triparna de Vreede is an Assistant Professor and the Associate Director of the School of Information Systems and Management, Muma College of Business, University of South Florida. She is also the Director of the Management Program (Masters and Undergraduate) at the Muma College of Business. She earned her Ph.D. in Industrial/Organizational Psychology from the University of Nebraska at Omaha, where she also received a Master's in Management Information Systems. Additionally, she holds an MBA in Human Resource Management from Osmania University.

Dr. de Vreede’s expertise lies in Behavioral AI and employee thriving in organizations. With a specific focus on Human-AI interaction, Dr. de Vreede explores the potential of AI in enhancing employee well-being and performance factors such as engagement, satisfaction, and burnout prevention. She is especially interested the circular and interactive relationship between design, perception, interaction, and implementations of AI agents in organizations.

In addition to her expertise in Behavioral AI, Dr. de Vreede is an avid collaboration researcher. She concentrates on the role of leaders as facilitators in orchestrating meaningful conversations and effective decision-making in teams. Her training modules on facilitation are designed to help leaders achieve efficient and high-quality outcomes from team interactions. A cornerstone of her collaboration research is the reduction of cognitive load, enabling teams to focus and converge on issues that are critical to organizational success.

Dr. de Vreede's areas of research include behavioral AI, Human/AI interaction, people analytics, collaboration, creativity, and employee well-being. Her work has been published in leading journals, including Information Systems Research, Journal of Management Information Systems, Computers in Human Behavior, and Information & Management. Her work also has been presented at numerous international conferences like International Conference for Information Systems (ICIS), Hawaiian International Conference for System Sciences (HICSS), Americas Conference on Information Systems (AMCIS), and Group Decision and Negotiation (GDN). She received over $7M in competitive funding as serving as Principal Investigator (PI) and Co-Principal Investigator (Co-PI) on various grants.

Dr. Jing Wang

Dr. Jing Wang

Computer Science and Engineering

Jing Wang, PhD, is a Professor of Instruction and Director of Broadening Participation in Computing in the Department of Computer Science and Engineering. She received her PhD in 2005 from Vanderbilt University. Throughout her career, Dr. Wang has been actively involved in the important mission of broadening participation in computing. She serves as the faculty advisor of Women in Computer Science and Engineering student organization since 2013 and has created multiple programs for mentoring and outreach. Dr. Wang has disseminated her work through national conferences, and has published in multiple peer-reviewed journals. She is a recipient of 2011 USF Outstanding Undergraduate Teaching award and 2020 USF Women in Leadership & Philanthropy Dr. Katherine Moore Faculty Excellence Award.

Dr. Alfredo Weitzenfeld

Dr. Alfredo Weitzenfeld

Computer Science and Engineering

Dr. Alfredo Weitzenfeld is a Professor at the Department of Computer Science and Engineering in the College of Engineering at the University of South Florida. Dr. Weitzenfeld is the director of the BioRobotics Laboratory and the USF RoboBulls RoboCup team.

Dr. Weitzenfeld is one of the main developers of the Neural Simulation Language (NSL) and the Abstract Schema Language (ASL), described both in The Neural Simulation Language NSL: A System for Brain Modeling (coauthors M. Arbib and A. Alexander) published in 2002 by MIT Press.

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 ACM member, an IEEE Senior Member. His main research areas are biorobotics, multi-robot systems and robot cognition.

Dr. Yasin Yilmaz

Dr. Yasin Yilmaz

Electrical Engineering

Dr. Yasin Yilmaz received the Ph.D. degree in Electrical Engineering from Columbia University, New York, NY, in 2014. He is currently an Assistant Professor of Electrical Engineering at the University of South Florida, Tampa. His research interests include machine learning and statistical signal processing, and their applications to computer vision, cybersecurity, cyber-physical systems, IoT networks, intelligent transportation systems, energy systems, and communication systems.