جست‌وجوی استاد و پژوهشگر

Tianshi Gaoمشاهده پروفایل

پژوهشگر

• Machine Learning
• Computer Vision
• Large-scale Systems
• +۳ مورد دیگر

Tianshi Gao is a research scientist at Facebook specializing in large-scale machine learning systems. He earned his Ph.D. in Electrical Engineering from Stanford University (2012) under Professor Daphne Koller, who co-founded Coursera. His bachelor's degree with honors comes from Tsinghua University (2007) in Electrical Engineering. Research Interests : Machine learning algorithms for computer vision and big data Hierarchical classification and few-shot learning Object detection with occlusion handling Cooperative systems in transportation and wireless communication Active learning and discriminative modeling Applications of output coding in multiclass boosting Publication Trends : His work from 2007-2012 spans computer vision, machine learning, and transportation systems. Key contributions include structured priors for efficient detection, hierarchical learning frameworks, and novel boosting algorithms. Scientific Awards : Best Poster Runner-up Award at CVPR 2011 Workshop Professional Service : He has served as a reviewer for top-tier journals including IEEE Transactions on Pattern Analysis and Machine Intelligence and Neural Information Processing Systems , plus organizing the Neural Information Processing Systems Workshop on Probabilistic Models for Big Data in 2013.

Francesca Nonisمشاهده پروفایل

استادیار

• Facial Expression Recognition
• Deep Learning
• Human-Computer Interaction
• +۶ مورد دیگر

Francesca Nonis is an Assistant Professor and Fixed-term researcher at Politecnico di Torino's Department of Management and Production Engineering (DIGEP). She is an invited member of both the College of Architecture and Design and the College of Mechanical, Aerospace, and Automotive Engineering. As part of the 3D LAB research group, she contributes to cutting-edge research in human-computer interaction applications and 3D data visualization. Dr. Nonis specializes in Facial Expression Recognition (FER) using Deep Learning techniques, with a focus on 3D data applications for human-computer interaction. Her research spans multiple domains including virtual reality, affective computing, and cultural heritage preservation. She has developed methodologies for real-time facial expression recognition and has contributed to building spontaneous 3D facial expression databases that have advanced the field of emotion recognition. Her recent publications reveal a strong trend toward interdisciplinary research that bridges computer science, psychology, and cultural applications. She has made significant contributions to metaverse platforms for cultural heritage preservation, user engagement studies using EEG in museum settings, and the development of affective virtual reality environments. Her work consistently applies advanced computer vision and deep learning techniques to solve real-world problems in human-computer interaction. Dr. Nonis has co-authored a national patent titled "Methodology for real-time facial expression recognition" with Federica Marcolin, Luca Ulrich, and Enrico Vezzetti. Her teaching portfolio includes Industrial Technical Drawing and Modeling Design courses across multiple engineering disciplines including Aerospace Engineering, Mechanical Engineering, Chemical and Food Engineering, and Design and Communication programs. As a core member of the 3D LAB research group, Dr. Nonis collaborates on projects involving facial morphology studies, innovative surgical guides, augmented reality applications, and e-learning solutions. The lab's work leverages 3D sensors, augmented and virtual reality, and machine learning techniques to develop applications for medical, security, and marketing domains.

Stella Grasshofمشاهده پروفایل

استادیار

• Machine Learning
• Computer Vision
• 3D Reconstruction
• +۵ مورد دیگر

Stella Grasshof is an Assistant Professor in Data Science at the IT University of Copenhagen , specializing in machine learning and computer vision applications. Her work spans 3D reconstruction, facial expression analysis, mental health diagnostics, and sports analytics. Research Areas : 3D trajectory estimation, diffusion models, underwater image segmentation, and technical drawing digitization. Key Collaborations : European Commission (REMARO), Danish National Research Foundation (Pioneer Centre for AI), Lundbeck Foundation (Automatic Analysis of Mental Disorders). Research Trends : Stella's recent publications focus on advancing generative models for interpretable latent space analysis, improving sim-to-real underwater segmentation, and applying synthetic data to 3D motion tracking. Her work bridges computer vision, machine learning, and real-world applications in sports and mental health. Scientific Awards : Best Student Paper Award at the 11th International Conference on Pattern Recognition Applications and Methods (2022). Projects & Grants : Active in multidisciplinary projects like REMARO (Trustworthy AI for marine robotics), Pioneer Centre for AI (Danish National Research Foundation), and TeamSPORTek (sports technology research). She has also developed datasets like MarinaPipe for marine robotics.

Yomna Abdelrahmanمشاهده پروفایل

استاد

• Human-Computer Interaction
• Thermal Imaging
• Usable Security
• +۶ مورد دیگر

Dr. Yomna Abdelrahman is a Professor of Usable Security and Privacy at the Bundeswehr University Munich . Her research focuses on thermal imaging for security and privacy , virtual reality usability, eye tracking , and biometric authentication . She collaborates with researchers like Florian Alt and Albrecht Schmidt on projects exploring how thermal sensing can enhance user identification and privacy awareness . Key Research Areas : Thermal Imaging, Human-Computer Interaction, Virtual Reality, Password Security, Biometric Authentication, Eye Tracking, Privacy Her recent publications address VR emotion detection , password usability , and privacy implications of thermal imaging . She has contributed to conferences like CHI, MUM, and INTERACT, often examining security-privacy trade-offs and non-invasive biometric systems . Notably, her work on thermal attacks reveals vulnerabilities in mobile authentication through thermal residue. She holds a PhD in Computer Science from the University of Stuttgart (2018), where her thesis, "Thermal Imaging for Amplifying Human Perception," laid the foundation for her later work on thermal-based interaction and cognitive load estimation . Her collaborations span diverse domains, from smart home notifications to industrial worker assistance , reflecting her interdisciplinary approach to usable security and interactive systems .

Jean Muhammadمشاهده پروفایل

دانشیار

• Software Engineering
• Computer Science Education
• Cyber Security Education
• +۲ مورد دیگر

Jean Muhammad serves as Chair and Associate Professor in the Department of Computer Science at Hampton University's School of Science, specializing in software engineering, cybersecurity education, and leadership management. Her academic journey spans Florida State University (Ph.D., 2005), Illinois Institute of Technology (M.S., 1991), and Chicago State University (B.S., 1984), complemented by industry roles at AT&T Bell Labs and Nokia. Howard University: Business Administration (1968-1970) District of Columbia Teachers College: Business Education (1973-1975) Chicago State University: Computer Science B.S. (1984) Illinois Institute of Technology: Computer Science M.S. (1991) Florida State University: Computer Science M.S. (1999) Florida State University: Computer Science Ph.D. (2005) Her research bridges software engineering pedagogy with practical cybersecurity applications, focusing on risk management frameworks and inclusive technology education. Key initiatives include developing curricula for underrepresented students and analyzing ethical implications of autonomous systems through interdisciplinary collaborations. Recent publications reveal strong trends in applied AI ethics (autonomous vehicles), healthcare technology integration, and cybersecurity awareness across demographics. Her work consistently addresses societal impacts of technology, with 70% of recent publications involving student co-authors in undergraduate research symposia. NPSC Fellowship Award (1996) As primary advisor for 15+ undergraduate/graduate researchers, she has secured $8.4M in grants including NSF S-STEM scholarships ($622K), ONR cybersecurity training ($250K), and Amazon Robotics funding ($500K). Her leadership extends to the HU GETS-IA CyberCorps program and Apple/HBCU C2 partnerships. She co-advises the CyberCorps Scholarship for Service cohort and leads the Chair's Graduate School Club, fostering industry placements through partnerships with Lockheed Martin, IBM, and Deloitte while directing Hampton's cybersecurity research infrastructure.

Gerald Zaunerمشاهده پروفایل

استاد

• Image Processing
• Thermography
• Non-Destructive Testing
• +۵ مورد دیگر

Gerald Zauner is a Professor at FH Wels (University of Applied Sciences Wels) specializing in image processing, thermography, and non-destructive testing. His research primarily focuses on railway infrastructure, computer vision, and artificial intelligence applications in engineering contexts. His research interests include: Image Processing and Computer Vision for industrial applications Thermography and Non-Destructive Testing techniques Railway infrastructure monitoring and maintenance systems Artificial Intelligence applications in engineering Heat treatment processes and energy harvesting Professor Zauner's recent research has focused on developing AI-powered systems for railway infrastructure analysis, including automatic object detection in radargrams, high-speed rolling mark detection, and track maintenance technologies. His work bridges the gap between theoretical computer vision techniques and practical engineering applications, particularly in the railway sector. He has been involved in several significant research projects: FLARE - Fast and reliable human-centered-AI for high-rate non-destructive evaluation (2025-2027) as Co-Investigator BF-Energie aus Abwärme - Energy Harvesting with Thermoelectricity (2016-2018) as Principal Investigator BiKoPla (Biozide Kunststoffoberflächen mittels Plasmaabscheidung) (2013-2017) as Principal Investigator Professor Zauner has made significant contributions to the field with over 100 research outputs, including patents, journal articles, and conference papers. His work has been cited over 300 times, demonstrating its impact in the engineering and computer vision communities.

Raif BAYIRمشاهده پروفایل

استاد

• Robotics
• Hybrid and Electric Vehicles
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Dr. Raif Bayır is a Turkish academic at Karabük University's College of Engineering, Department of Mechatronics Engineering. With a career spanning 2000-2024, he has held continuous full-time faculty positions from Assistant Professor to Professor. His research focuses on Robotics, Hybrid/Electric Vehicles, and Artificial Intelligence. Doctorate: Gazi University (2005) - Electronics & Computer Education Postgraduate: Gazi University (1998) - Electronics & Computer Education Undergraduate: Gazi University (1995) - Electronics & Computer Education His work integrates Artificial Intelligence techniques into Electric Vehicle systems, Robotics, and Agricultural Engineering applications. Recent publications emphasize Deep Learning for Mask Detection, Real-Time Battery Monitoring, and Autonomous Navigation Systems. Scientific awards include: 2017 METU Line-Following Robot 1st Prize 2016 TÜBİTAK Domestic Product Award 2015 TÜBİTAK Electromobil Best Design Prize He has advised over 20 graduate theses on topics spanning Electric Vehicle Components, Beehive Monitoring Systems, and Intelligent Control Applications. His research teams have developed multiple TÜBİTAK-supported projects including Automotive Test Stands and Battery Management Systems.

Tim Chenمشاهده پروفایل

مدرس ارشد

• Human-Computer Interaction
• Computer Graphics
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Tim Chen is a Senior Lecturer at the School of Computer Science, University of Adelaide, with research focused on augmenting human capabilities through human-centered AI systems. He leads interdisciplinary teams in projects like the Augmenting Ability CRC and the IMAGENDO Project , which received the Eureka Prize and NHMRC Idea Grant. Affiliation: University of Adelaide Collaborators: Prof. Patrick Baudisch (HPI), Prof. Takeo Igarashi (U of Tokyo), Prof CT Lin (UTS), Dr. Li-Yi Wei (Adobe Research) Research Interests: Human-AI interaction paradigms ( AI as Assistant, Collaborator, Oracle ), virtual reality training, contrastive learning, and data visualization. His work bridges AI/ML, computer graphics, and human-computer interaction to empower knowledge workers. Recent Achievements: Two CHI 2025 papers on VR learning, SIGGRAPH 2025 jury committee role, and ARC DP analysis website development. Funding includes NHMRC (~$2M) and AEA Ignite grants. Scientific Awards: Eureka Prize-winning leadership NHMRC Idea Project Grant AEA Ignite Grant (~$500k)

Shounak Roychowdhuryمشاهده پروفایل

دانشیار

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Shounak Roychowdhury is an Associate Professor of Practice at the School of Information, University of Texas at Austin. He holds a PhD in Computer Engineering from the University of Texas at Austin (2013) and an MS in Computer Science from the University of Tulsa (1997). His teaching focuses on foundational and advanced topics such as Computer Vision, Database Management, Programming, and Data Science. Recent courses include INF 385T: Special Topics in Information Science: Computer Vision (2025) and I 320D: Topics in Human-Centered Data Science: Database Design (2024). Roychowdhury's research spans Computer Science , Machine Learning , and Software Engineering , with a focus on probabilistic methods, fuzzy systems, and medical informatics. His work explores areas like fault localization in software, data clustering optimization, and applying generative models to healthcare analytics. He has also contributed to fuzzy logic applications in decision-making and pattern recognition. His publications highlight interdisciplinary approaches, including Alzheimer’s disease modeling with GANs and color space analysis in art through probabilistic divergences. While no scientific awards are listed, his work reflects sustained contributions to theoretical and applied computing. Roychowdhury advises no listed students but maintains an active teaching role. No specific grants or labs are mentioned, though his research aligns with computational and data-driven methodologies.

Michael Blumensteinمشاهده پروفایل

استاد

• Artificial Intelligence
• Pattern Recognition
• Computer Vision
• +۳ مورد دیگر

Professor Michael Blumenstein is Pro Vice-Chancellor at UTS with a distinguished career in artificial intelligence applications. His research develops computer vision systems for environmental monitoring and document analysis. Notable innovations include: SharkSpotter AI for marine safety CrocSpotter wildlife monitoring Pattern recognition for handwritten text analysis His team's SharkSpotter technology received the 2018 AI Innovation of the Year Award and is deployed at 50+ Australian beaches. Research spans video analytics, text detection algorithms, and signature verification systems with 300+ publications.

Tomasz Woloszynskiمشاهده پروفایل

مدرس

• Biomechanics
• Medical Imaging
• Tribology
• +۲ مورد دیگر

Tomasz Woloszynski is a Lecturer in the School of Civil and Mechanical Engineering at Curtin University. His research focuses on medical image analysis of knee joints and numerical optimization of wear surfaces. He holds dual PhDs in Electronic Engineering from Wroclaw University of Technology and Mechanical Engineering from the University of Western Australia. Research areas include automated classification of wear patterns, surface texture analysis, and computational methods for diagnosing osteoarthritis from medical images. His work develops innovative approaches to characterize tribological surfaces and predict joint degeneration through advanced imaging techniques. Publication analysis shows consistent focus on tribology, surface engineering, and medical diagnostics. Recent work develops automated systems for wear surface classification while maintaining an ongoing research thread in osteoarthritis prediction using bone texture analysis and machine learning methods.

Roberto Solis-Obaمشاهده پروفایل

استاد

• Algorithm Design
• Approximation Algorithms
• Data Structures
• +۹ مورد دیگر

Overview Roberto Solis-Oba is a Professor in the Department of Computer Science at the University of Western Ontario. He holds a Ph.D. from Purdue University (supervised by Prof. Greg Frederickson) and completed a postdoctoral fellowship at the Max Planck Institute for Informatics under Prof. Kurt Mehlhorn. His research focuses on algorithm design, particularly approximation algorithms for NP-hard optimization problems, with applications in networks, scheduling, packing, and computational biology. Education & Background Ph.D., Computer Science, Purdue University (1990s) Postdoctoral Fellowship, Max Planck Institute for Informatics Research Interests His work spans algorithm design, including approximation algorithms, data structures, parallel/distributed/online/randomized algorithms. Key application areas include networks, scheduling, packing optimization, computational biology, and data mining. He co-founded the Workshop on Approximation and Online Algorithms (WAOA), held annually since 2003. Awards & Recognition Faculty Scholar Award, University of Western Ontario USC Teaching Award, University of Western Ontario Professional Contributions Prof. Solis-Oba has served on program committees for major algorithm-focused conferences and contributed to research in scheduling, packing, and graph theory. His work emphasizes practical and theoretical advancements in algorithmic efficiency and optimization.

• Computer Vision
• Medical Imaging
• Deep Learning
• +۳ مورد دیگر

Yu Huang is a Researcher in the Department of Mathematical and Statistical Sciences at Clemson University's College of Science. His work focuses on advancing computational methods in medical imaging, computer vision, and deep learning applications. His research includes developing multimodal models for ophthalmology, enhancing 3D graphics rendering, and improving biomedical image analysis through active learning frameworks. Notable projects involve generative models for retinal imaging and shadow removal techniques in computer vision. His research interests span computational ophthalmology, neural rendering, and AI-driven biomedical solutions. Recent efforts emphasize scalable diffusion models for high-resolution synthesis and robust medical image segmentation using test-time augmentation. Yu Huang's publications reflect a strong emphasis on interdisciplinary research at the intersection of computer science and healthcare. His work addresses challenges in both foundational AI methodologies and their practical applications in clinical settings.

Colin Wilderمشاهده پروفایل

دانشیار

• History of European classical liberalism
• Digital History
• German legal and political thought
• +۷ مورد دیگر

Colin Wilder is an Associate Professor in the Department of History at the University of South Carolina's College of Arts and Sciences. He joined the History Department as an assistant professor in 2016 and was promoted to associate professor with tenure in 2024. Prior to joining the History Department, he served as associate director of the Center for Digital Humanities from 2012, where he was a member of the Library faculty. Dr. Wilder's educational background includes: B.A. in Philosophy from Yale University M.A. in History from the University of Chicago Ph.D. in History from the University of Chicago Before joining USC, Dr. Wilder held postdoctoral fellowships at Brown University and the University of Wisconsin-Madison. Dr. Wilder's research focuses on two primary areas: the history of European classical liberalism, particularly in seventeenth and eighteenth century Germany, and Digital History. His work in German history centers on the Hessian and Rhine-Main region around Frankfurt am Main, examining ideas about freedom, law, constitutionalism, and republicanism. His Digital History research involves applying computational methods like 'distant reading' to early modern historical questions, particularly around liberalism and property law. His scholarship demonstrates a unique interdisciplinary approach that bridges traditional historical research with cutting-edge digital methodologies. Dr. Wilder's recent scholarly output shows a strong trend toward interdisciplinary work that combines historical research with computational methods. His publications span traditional historical scholarship on German legal and political thought as well as innovative applications of digital tools to historical problems. This dual focus is evident in his monograph Property and the German Idea of Freedom (2024) alongside technical papers on curve pattern recognition in archaeological artifacts. His work demonstrates how digital methods can enhance traditional historical research and open new avenues for understanding historical phenomena. Dr. Wilder is actively engaged in teaching and service at USC. He teaches courses on Digital History, German History (HIST 338), Modern European History (HIST 102), the History of Constitutionalism and Republicanism (HIST 467, 469), and the History of Capitalism and Business (HIST 370, 377, 778). He is developing extracurricular mini-seminars focused on great works from the history of classical liberal political thought and organizes visiting lectures for Constitution Day commemorations.

Ruba Al Omariمشاهده پروفایل

استادیار

• Cybersecurity
• Machine Learning in Security
• Information Security
• +۴ مورد دیگر

Ruba Al Omari is an Assistant Professor, Teaching Stream in the Department of Electrical Engineering & Computer Science at York University. She holds a PhD in Computer Science from Ontario Tech University, where she earned the Doctoral Excellence Award. Her research focuses on cybersecurity, machine learning applications in security, and the intersection of brain-computer interfaces (BCIs) with password memorability and user behavior analysis. Dr. Al Omari has over 15 years of industry experience in IT roles spanning network management and security. Her teaching portfolio includes graduate and undergraduate courses in cybersecurity, network security, applied cryptography, malware analysis, and machine learning. Notable courses include 'Attack and Defense Special Topics in IT: AI in Cybersecurity' and capstone projects in computer security. Research interests emphasize leveraging EEG signals and neural networks to predict password memorability, studying user behavior in password usage, and exploring BCI applications for facial recognition and image tagging. Her work bridges cognitive science, neuroscience, and computational security systems. Publications consistently address themes of password security, BCI-driven biometric authentication, and cognitive aspects of cybersecurity. Awards include the Doctoral Excellence Award from Ontario Tech University (exact year not specified in text). Previous roles included program coordinator for AI and Cybersecurity programs at Durham College, alongside teaching experience at Ontario Tech University. Industry background includes user support and network management roles, providing practical insights into IT security challenges.