جست‌وجوی استاد و پژوهشگر

• Computer Vision
• Image Processing
• Pattern Recognition
• +۵ مورد دیگر

Prof Qiang Wu is a Professor and Deputy Head of School (Research) at the School of Electrical and Data Engineering, University of Technology Sydney. He is a core member of the Global Big Data Technologies Centre. His research focuses on computer vision, image processing, pattern recognition, and machine learning, with applications in video surveillance, biometrics, and human-computer interaction. He holds a B.Eng. and M.Eng. from Harbin Institute of Technology and a Ph.D. from UTS. Prof Wu has led industry collaborations with organizations like Meat & Livestock Australia, Canon, and Westpac Bank. He has authored over 300 publications, including works on pedestrian detection, virtual clothing fitting, and gait recognition patented in the U.S. He serves as an Associate Editor for IEEE Transactions on Multimedia and is a Senior IEEE Member. His research has been funded by grants from bodies like the Australian Egg Corporation and the Australian Research Council. He advises on PhD and Master’s students in computer vision and related areas.

• Bioinformatics
• Health Informatics
• Affective Computing
• +۵ مورد دیگر

Dr. Stamos Katsigiannis is an Associate Professor in the Department of Computer Science at Durham University, specializing in bioinformatics, health informatics, affective computing, and GPU computing. His research bridges machine learning with medical applications, including EEG-based biometrics, emotion recognition, and medical imaging analysis. He holds a PhD in Computer Science from the National and Kapodistrian University of Athens (Greece) and previously held roles at the University of the West of Scotland and the University of Athens. Education: BSc (Hons.) in Informatics and Telecommunications (National and Kapodistrian University of Athens), MSc in Computer Science (Athens University of Economics and Business), PhD in Computer Science (National and Kapodistrian University of Athens). Research focuses on applying AI to healthcare, including biometric identification via EEG signals, remote physiological monitoring, and automated tutoring systems. Recent work involves deep learning for medical image analysis (e.g., chest X-rays, masonry façade cracks) and AI ethics governance (e.g., contributions to UK parliamentary inquiries on AI regulation). Publications span IEEE journals and conferences, emphasizing interdisciplinary applications of machine learning in health, education, and security. Active supervision of postgraduate students in AI-driven health technologies and computer vision.

Daniela Oramas Moraمشاهده پروفایل

استادیار

• Racial and Ethnic Disparities
• Criminal Justice System
• Prosecutorial Discretion
• +۵ مورد دیگر

Daniela Oramas Mora is an Assistant Professor in the Department of Criminology, Law and Society at George Mason University. Her research focuses on racial and ethnic disparities in the criminal justice system, prosecutorial discretion, sentencing practices, and policy evaluation, employing quantitative methods. She holds a Ph.D. from Arizona State University, an M.A. from the University of South Florida, and dual B.A./B.S. degrees from the University of Florida. Education: Ph.D., Criminology and Criminal Justice, Arizona State University (2024) M.A., Criminology, University of South Florida (2020) B.A., Criminology, University of Florida (2018) B.S., Psychology, University of Florida (2018) Research Interests: Dr. Oramas Mora’s work examines systemic inequities in policing and sentencing, courtroom dynamics, and the impact of progressive prosecutorial policies. She also investigates driving behavior and safety through quantitative frameworks, bridging criminology with transportation studies. Publications: Her recent work includes analyses of police use of deadly force, racial disparities in sentencing, and the efficacy of prosecutorial reforms. She has also contributed to transportation safety research, exploring driver perception and algorithmic bias in facial recognition systems. Affiliations: Teaches courses such as Introduction to Criminal Justice and Capstone in Criminology, Law and Society. Active in academic publishing across disciplines like criminology, law, and transportation safety.

Shiaofen Fangمشاهده پروفایل

استاد

• Data Visualization
• Visual Analytics
• Interactive Machine Learning
• +۲ مورد دیگر

Shiaofen Fang is Professor of Computer Science and Associate Dean for Research at Indiana University's Luddy School of Informatics, Computing, and Engineering. He holds a Ph.D. in Computer Science from the University of Utah and M.S./B.S. degrees in Mathematics from Zhejiang University. His research focuses on data visualization, medical image analysis, and interactive machine learning. Research interests span: Data visualization including healthcare analytics and neuroimaging tools Medical image analysis for FASD diagnosis and brain connectomics Interactive AI for explainable machine learning systems Volume graphics for 3D modeling and rendering Publications demonstrate strong focus on AI applications in healthcare and education, visualization techniques for biomedical data, and geometric modeling. Recent works increasingly address ethical AI and bias mitigation. Research funded by NSF, NIH, DoD, and NIJ. Collaborates extensively with biomedical researchers and healthcare institutions. Leads projects on neuroimaging visualization, healthcare data exploration, and 3D facial analysis.

Sanjiv Bhatiaمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Cyber Security
• +۷ مورد دیگر

Sanjiv Bhatia is a Professor of Computer Science at the University of Missouri-St. Louis, specializing in computer vision, image processing, and operating systems. He holds a PhD in Computer Science from the University of Nebraska-Lincoln and has extensive industry consulting experience in defense applications. His educational background includes: PhD in Computer Science, University of Nebraska-Lincoln (1991) MS in Computer Science, University of Arkansas at Fayetteville (1987) BE in Computer Science Engineering, Motilal Nehru National Institute of Technology (1983) Dr. Bhatia's research focuses on developing algorithms for computer vision applications including image indexing, object tracking, and multi-sensor fusion. His work bridges theoretical computer science with practical applications in defense systems and cloud computing. His publications demonstrate consistent focus on algorithm development for image processing and pattern recognition, with recent expansion into environmental modeling applications. Research trends show progression from core computer vision techniques to applied geospatial analysis and optimization methods. Awards include: Chancellor's Award for Excellence in Teaching (2015) He teaches courses in Operating Systems, Digital Image Processing, and Cloud Computing. His instructional approach emphasizes practical implementation and system-level programming skills, with curriculum materials including extensive programming assignments and open-book examinations.

Marian Machمشاهده پروفایل

دانشیار

• Symbolic Artificial Intelligence
• Evolutionary Computation
• Ontological Engineering
• +۵ مورد دیگر

Marian Mach is an Associate Professor at the Department of Cybernetics and Artificial Intelligence, Technical University of Kosice. He holds a Ph.D. (1992) and habilitation in Artificial Intelligence (2001). His research focuses on symbolic AI, evolutionary computation, knowledge modeling, and ontological engineering. He has led national and EU projects like Modermed (2023-2027) and DL4VISION (2022-2025), addressing toxic behavior detection and deep learning for image processing. Education: Ph.D. in Technical Cybernetics (1992), TU Kosice Habilitation in AI (2001), TU Kosice M.S. in Technical Cybernetics (1985), TU Kosice Research Interests: Evolutionary algorithms Constraint satisfaction problems Knowledge representation Machine learning applications in social media analysis Robotics and intelligent systems Teaching: Courses include Machine Learning II, Evolutionary Algorithms, and Application of Logic in Intelligent Systems. He has developed over 20 courses since 1987. Grants & Projects: EU-funded initiatives: VICINITY (2016-2019), PICASO (2016-2019) National grants: APVV-22-0414 (2023-2027), VEGA 1/0394/22 (2022-2025) Labs/Teams: Involved in AI Center at TU Kosice and collaborative projects on cloud-based robotics and semantic web technologies.

Peter Polakمشاهده پروفایل

دانشیار

• Information Systems
• Information Security
• Human-Computer Interaction
• +۲ مورد دیگر

Peter Polak is an Associate Professor in the Department of Information Systems and Business Analytics at Florida International University's College of Business. He teaches courses including Business Application Development, Business Statistics and Analysis, Data Base Applications, Information Security and Compliance, and Systems Analysis and Design. His educational background includes: Ph.D. in Business Administration from University of Pittsburgh Master in Management from Comenius University, Bratislava Master of Business Administration from Wichita State University Master of Financial Management from Comenius University, Bratislava Bachelor of Business Administration from Wichita State University Polak's research focuses on human aspects of information systems, with primary interests in Information Security, Human-Computer Interaction, and Knowledge Management. His work examines user behavior in security contexts, environmental influences on work performance, and organizational knowledge-sharing mechanisms, often employing experimental methodologies to analyze cognitive and behavioral responses. His publications from 2004-2015 reveal consistent investigation into security behavior motivated by fear appeals, music's impact on system design tasks, knowledge-sharing dynamics, and user reactions to online advertising and website performance. These studies demonstrate interdisciplinary approaches bridging information systems, psychology, and organizational behavior. Scientific Awards: No awards were mentioned in the provided information. Advising and Grants: The available text does not specify student advising roles or research grants. Labs and Teams: No research labs or specialized teams are described in the source material.

Larry Tangمشاهده پروفایل

استاد

• Statistical Methodology
• Forensic Science
• Diagnostic Medicine
• +۴ مورد دیگر

Dr. Larry Tang is a Professor in the Department of Statistics & Data Science at the University of Central Florida (UCF), affiliated with the National Center for Forensic Science and the NIH Clinical Center. He previously held positions at George Mason University (2007-2019) and completed postdoctoral training in Biostatistics at the University of Washington. His research focuses on statistical methodology applied to forensic science, diagnostic medicine, clinical trial design, and criminology, with funding from the National Institute of Justice and National Institutes of Health. Education: B.S. in Finance, University of Science and Technology of China (2000) M.S./Ph.D. in Statistics, Southern Methodist University (2003/2005) Postdoctoral Fellow, University of Washington (2005-2007) Research Interests: Dr. Tang develops statistical methods for evaluating forensic evidence, diagnostic tests, and criminological studies. Key areas include ROC curve analysis, group sequential designs, algorithmic bias detection, and biometric recognition systems. His work bridges theoretical statistics with practical applications in criminal justice and healthcare. Grants & Collaborations: Active research is supported by federal grants focusing on forensic methodology and mental health outcomes. He collaborates with the NIH Clinical Center on disability assessment studies and the National Center for Forensic Science on fire debris analysis and latent fingerprint evaluation.

Michael L. Myrickمشاهده پروفایل

استاد

• Optical Spectroscopy
• Environmental Science
• Forensic Spectroscopy
• +۳ مورد دیگر

Michael L. Myrick is a Professor of Chemistry at the University of South Carolina's McCausland College of Arts and Sciences, Department of Chemistry and Biochemistry. He has held academic roles since 1991, including President of the Coblentz Society (2011–2013) and Chief Scientist at Ometric Corporation (2004–2011). His research focuses on optical spectroscopy, phytoplankton community analysis, forensic infrared imaging, and particle/film spectroscopy. Education: B.S. in Chemistry from North Carolina State University (1985), Ph.D. in Physical Chemistry from New Mexico State University (1988). Postdoctoral work at LLNL (1989–1990). Research interests span optical spectroscopy applications in environmental and forensic contexts. He collaborates with Professors Shaw and Richardson on phytoplankton studies and develops forensic imaging tools with Dr. Morgan. His work addresses challenges in heterogeneous sample analysis, such as phytoplankton species classification and blood detection on fabrics. Awards include the Gerald S. Birth Award (2012), Army Research Office Young Investigator Award (1992), and NSF Graduate Fellowship (1986). He holds over 20 patents, including innovations in multivariate optical computing and chemical sensors. Labs: GSRC 223 (office), SMWALT 108/109A/110 (labs). His teams include graduate students and postdoctoral researchers in spectroscopic instrumentation and environmental chemistry.

Andrew Dunnمشاهده پروفایل

مدرس ارشد

• Perception
• Memory
• Attention
• +۷ مورد دیگر

Dr. Andrew Dunn is a Senior Lecturer in Psychology at Nottingham Trent University's School of Social Sciences. He specializes in perception, memory, and attention with a focus on evolutionary psychology, developmental psychology, and perceptual illusions. His research explores how humans process facial, vocal, and bodily cues in social and environmental contexts. Education: BSc Psychology (Hons) from University of York (1996-1999) PhD in Psychology from University of York (1999-2002), focusing on vision for action and perception Research Interests: Person perception (faces, voices, bodies) Evolved mechanisms in social cognition Contextual effects on perception Body shape preferences and mate choice Spatial memory and exclusivity effects Publications: Over 40 articles spanning perception, cognition, and evolutionary psychology. Recent work includes studies on body dissatisfaction, forensic voice discrimination, and the integration of multisensory cues in mate selection. Awards & Grants: Visual Sciences Society Travel Grant (2002) QR Ref Funding for facial/voice databases (2018) BPS Summer Student Bursary (2018) Advising & Leadership: Supervised 13 PhD students Programme leader for MSc/MRes Psychological Research Methods Chair of School Research Ethics Committee External Roles: Editor of Journal of Evolutionary Psychology and Culture and Evolution External examiner at Sheffield, Northampton, and Strathclyde Universities Member of British Psychological Society's Cognitive Section committee

Malek Adjouadiمشاهده پروفایل

استاد

• Pattern Recognition
• Medical Imaging
• Biometrics
• +۲ مورد دیگر

Malek Adjouadi serves as Ware Professor and Director of the Center for Advanced Technology and Education (CATE) in the Department of Electrical and Computer Engineering at Florida International University, where he has been a Full Professor since 2007 and previously served as Acting Department Chair from 1997-2001. His academic foundation includes: Ph.D. in Electrical Engineering, University of Florida (1985) M.S. in Electrical Engineering, University of Florida (1981) B.S. in Electrical Engineering, Oklahoma State University (1978) Adjouadi's research bridges Pattern Recognition with critical medical and security applications. His primary focus involves Medical Imaging analysis for pediatric epilepsy using fMRI and EEG data, where he develops advanced classification algorithms for language network mapping and seizure detection. This work extends into Biometrics through thermal imaging authentication systems and iris recognition, while also encompassing Signal Processing techniques for neurological data and contributions to Cryptography through biometric security frameworks. His interdisciplinary approach consistently applies computational methods to solve complex problems in neuroscience and security domains. Analysis of his 14 publications from 2006-2013 reveals a dominant medical neuroscience trajectory focused on pediatric epilepsy diagnostics, with significant contributions to biometric security emerging around 2011-2012. The medical works predominantly employ machine learning for brain imaging analysis, while his security publications introduce novel approaches to facial authentication and geospatial data management. As Director of CATE, Adjouadi leads technology education initiatives while teaching advanced courses including Digital Image Processing, Computer Vision, and Neural Systems. His professional service includes representation at State University System of Florida meetings and Board of Regents presentations, demonstrating ongoing institutional leadership.

Richard J. Radkeمشاهده پروفایل

استاد

• Computer Vision
• Human-Scale Occupant-Aware Environments
• Video Analytics
• +۶ مورد دیگر

Richard J. Radke is a Full Professor in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI). He holds a B.A./M.A. in Computational and Applied Mathematics from Rice University and M.A./Ph.D. in Electrical Engineering from Princeton University. His research focuses on computer vision, human-scale occupant-aware environments, smart lighting systems, and medical imaging applications. He is affiliated with the NSF Engineering Research Center for Lighting Enabled Systems and Applications (LESA), DHS Center of Excellence ALERT, and Rensselaer's Cognitive and Immersive Systems Laboratory (CISL). Radke's work includes designing systems for group meeting facilitation, video analytics in camera networks, and LiDAR integration. He has received the NSF CAREER Award (2003) and the IEEE Signal Processing Society Regional Distinguished Teacher Award (2023). His textbook Computer Vision for Visual Effects (Cambridge University Press, 2012) bridges academic research and Hollywood visual effects. He advises numerous graduate students and collaborates on projects such as the Rensselaer Augmented and Virtual Environment (RAVE) lab. His research also involves medical applications like IMRT treatment planning optimization and robotics for manufacturing. Radke teaches courses on signal processing, image processing, and computational creativity, emphasizing video lectures and interactive learning tools. Education: B.A./M.A., Computational and Applied Mathematics, Rice University M.A./Ph.D., Electrical Engineering, Princeton University His research labs and initiatives include the Smart Conference Room for occupancy-aware lighting and the CRAIVE-Lab for immersive environments. He has authored over 100 publications and patents in vision, robotics, and medical imaging.

• Machine Learning
• Health Informatics
• Human Computer Interaction
• +۳ مورد دیگر

Prithwi Raj Chakraborty is a Lecturer in the Department of Information Technology at Southern Cross University's Faculty of Science and Engineering. He holds a PhD in affective computing, emotion analysis, and machine learning from Queensland University of Technology (QUT). His academic career began as a Research Fellow at QUT before transitioning to SCU. Active collaborations include partnerships with Sydney University, Griffith University, QLD Health, and QCH. His research focuses on machine learning applications in health informatics, human-computer interaction, and affective computing. Education: PhD in Computer Science from Queensland University of Technology (QUT). Key research areas include cognitive load modeling, wearable sensor analytics, and mHealth solutions like the myPainPal chronic pain management app. He has published impactful work on fall risk detection for the elderly and biometric-based video analysis. Current projects involve optimizing high-performance office environments and generic viewer interest modeling. Professional affiliations include Southern Cross University's Faculty of Science and Engineering, with past experience as a Casual Academic in the School of Business and Tourism. His work bridges computational methods with real-world human behavior analysis in healthcare and workplace settings.

• Signal Processing
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Mahesh Banavar is an Associate Professor in the Department of Electrical and Computer Engineering at Clarkson University, affiliated with the Coulter School of Engineering & Applied Sciences and the Institute for STEM Education. He directs the CoSiNe Lab and focuses on research in signal processing, machine learning, complex networks, and STEM education. His work addresses cybersecurity, behavioral biometrics, and continuous authentication. Education: B.E. in Telecommunications Engineering from Visvesvaraya Technological University (2005) M.S. and Ph.D. in Electrical Engineering from Arizona State University (2007, 2010) Research interests span signal processing applications in security and biometrics, machine learning for healthcare and autonomous systems, and innovative STEM education strategies. Notable awards include the Clarkson University Outstanding Advisor Award (2019), HKN Outstanding Teaching Award (2015-2016), and a Graduate Teaching Excellence Award (2008-2009). His publications emphasize localization algorithms, biometric authentication, and educational technology innovations. Labs/Teams: Director of the CoSiNe Lab, developing interdisciplinary research in signal processing and education.

Jakub Gałkaمشاهده پروفایل

مدرس پاره‌وقت

• Digital Signal Processing
• Multimedia Processing
• Machine Learning
• +۶ مورد دیگر

Jakub Gałka serves as an Associated Part-time Lecturer at the Institute of Electronics, AGH University of Kraków, where he leads research in digital signal processing, machine learning, and deep learning for speech/audio applications. His dual career bridges academia and industry through co-founding Techmo sp. z o.o.—a voice technology commercialization spin-off—and providing R&D consultancy to multiple tech firms, driving innovation in voice biometrics and spoken dialogue systems. His research integrates wavelet analysis with modern deep learning techniques to solve real-world challenges in cross-gender voice conversion, speaker identification, and sign language processing. Key focus areas include audio security (replay attack detection), multimodal human action recognition, and accessibility technologies for the deaf community, demonstrating consistent translational impact from theoretical signal processing to market-ready solutions. Analysis of his recent publications reveals a strategic shift toward deep adversarial learning for voice conversion and robust biometric security systems, while maintaining foundational work in wavelet-Fourier transform compositions. His output consistently targets applied outcomes, particularly in commercial voice technologies and assistive systems for sign language processing. Scientific recognition includes: Graduate of Stanford University’s selective Top 500 Innovators internship program As an academic-industry liaison, Gałka mentors students through Techmo collaborations and directs R&D projects spanning voice authentication, music processing, and emergency call center speaker identification. His grant portfolio includes national and international initiatives focused on voice biometrics commercialization and sign language technology development. He actively contributes to the Signal Processing Group at AGH University, fostering partnerships that transform academic research—particularly in speech segmentation and neural network architectures—into deployable voice solutions for corporate and healthcare applications.