جست‌وجوی استاد و پژوهشگر

Senem Velipasalarمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Wireless Smart Camera Networks
• +۸ مورد دیگر

Senem Velipasalar is a Professor in the Department of Electrical Engineering and Computer Science (EECS) at Syracuse University, affiliated with the Smart Vision Systems Laboratory and the Aging Studies Institute. She holds a Ph.D. and M.A. from Princeton University, an M.S. from Brown University, and a B.S. from Bogazici University. Her research focuses on machine learning, computer vision, and wireless smart camera systems, with applications in human activity classification, driver behavior analysis, and defense against adversarial attacks. Her honors include the NSF CAREER Award (2011), 2021 IEEE Technological Innovation Award, and multiple doctoral prizes for her advisees. She leads grants totaling over $4M, including ARPA-E projects on occupancy detection and DOE-funded research on aerial energy modeling. Research interests span embedded vision, distributed multi-camera tracking, and energy-efficient algorithms. Her lab develops technologies like wearable camera-based fall detection and autonomous UAV navigation. Notable publications include works on adversarial attacks, fNIRS brain activity analysis, and thermal pedestrian detection.

Jing Zhangمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Generative AI
• +۵ مورد دیگر

Dr. Jing Zhang is a Lecturer in the School of Computing at the Australian National University (ANU) , within the ANU College of Systems & Society . Previously, he served as a Research Fellow at ANU (2021–2022) and earned his PhD in 2021 under the supervision of Nick Barnes. His academic journey includes a Master’s (2010) and Bachelor’s (2007) from Northwestern Polytechnical University . Education: PhD, Australian National University, 2021 (Supervisor: Nick Barnes) Master’s Degree, Northwestern Polytechnical University, 2010 Bachelor’s Degree, Northwestern Polytechnical University, 2007 Research Interests: Jing Zhang’s research focuses on computer vision and machine learning , with a particular emphasis on generative AI . His work addresses challenges in image, video, and audio generation/editing; explainable model adaptation; out-of-distribution detection; and adversarial attacks/defenses. He explores techniques to enhance model robustness and generalization across diverse domains. Awards & Recognition: CVPR 2020 Paper Award Nominee for “UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders” Teaching & Supervision: Jing Zhang teaches COMP8536: Advanced Topics in Computer Vision (Semester 2, 2024) and ENGN4528/6528: Computer Vision (Semester 1, 2025). He currently supervises 4 PhD students as their primary advisor, focusing on cutting-edge research in computer vision and AI. Professional Contributions: Co-organizer of tutorials on salient object detection (ACCV 2019) and uncertainty estimation (ICCV 2021) Regular reviewer for top venues: CVPR, ICCV, ECCV, TPAMI, IJCV, and others Research Groups: While not explicitly stated, his work is likely affiliated with ANU’s computer vision research groups, focusing on generative AI and robust machine learning systems.

Shimi Naurin Ahmadمشاهده پروفایل

دانشیار

• Online Consumer Behavior
• Online Marketing and Sales
• Text Mining
• +۳ مورد دیگر

Dr. Shimi Naurin Ahmad is an Associate Professor of Business Administration at Morgan State University's Earl G. Graves School of Business and Management. Her research focuses on Online Consumer Behavior and Text Mining of Online Word-of-Mouth, with a particular emphasis on leveraging large unstructured datasets to uncover behavioral patterns. Dr. Ahmad holds a Ph.D. in Business Administration from Concordia University's joint doctoral program with McGill, HEC, and UQAM, alongside an M.Sc. in Electrical Engineering from Concordia and a B.Sc. from Rajshahi University of Engineering and Technology. Research Interests: Online Consumer Behavior Text Mining Techniques Online Pricing Strategies Cross-Cultural Marketing Social Commerce Dynamics Her work has been published in top-tier journals such as the Journal of Marketing Analytics and International Journal of Information Management . Notably, her 2023 Journal of Marketing Analytics paper earned the Most Popular Article Award. She has secured grants including the Provost Innovation Grant and Transform Morgan Grant, supporting her research initiatives. Awards & Recognition: 2023 Most Popular Article Award (Journal of Marketing Analytics) Competitive Research Grants from Morgan State University Dr. Ahmad's research bridges technical disciplines like data mining with business applications, contributing to both academic and practical insights in consumer behavior and digital marketing strategies.

Lichao Sunمشاهده پروفایل

استادیار

• Artificial Intelligence Security
• AI Privacy
• Machine Learning
• +۷ مورد دیگر

Lichao Sun is an Assistant Professor of Computer Science and Engineering at Lehigh University. He holds a Ph.D. in Computer Science from the University of Illinois at Chicago (2020), and bachelor's and master's degrees in Computer Science and Engineering from the University of Nebraska-Lincoln. His research focuses on AI security and privacy, addressing vulnerabilities in AI systems, particularly in large language models and multimodal systems. He also explores data mining, federated learning, and reinforcement learning applications. His educational background includes: Ph.D., Computer Science, University of Illinois at Chicago (2020) M.S., Computer Science, University of Nebraska-Lincoln B.A., Computer Science and Mathematics, University of Nebraska-Lincoln Research interests emphasize mitigating security threats in AI, including adversarial attacks (backdoors, token-level vulnerabilities), robust watermarking, and privacy-preserving techniques in federated learning. His work integrates vision-language models, multimodal reasoning, and ethical AI safety. Recent studies highlight innovations in secure embedding aggregation, generative AI defenses, and strategic reasoning in LLMs. Publications (2025) reflect a focus on AI security, multimodal systems, and reinforcement learning applications, with contributions to conferences like CCS, NeurIPS, and AAAI. His research bridges theoretical advancements with practical cybersecurity solutions for modern AI architectures. No scientific awards explicitly mentioned in the provided text. His advising and grants details are not detailed here, though his prolific publication record suggests active research funding. No lab/teams explicitly referenced in the input data.

David Doermannمشاهده پروفایل

استاد

• Document Image Understanding
• Video Analysis
• Pattern Recognition
• +۹ مورد دیگر

David Doermann is a Professor and Department Chair of the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His research focuses on document image understanding, video analysis, pattern recognition, computer vision, media forensics, and artificial intelligence. Education: PhD in Computer Science, University of Maryland, College Park (1993) MS in Computer Science, University of Maryland, College Park (1989) BS in Computer Science/Mathematics, Bloomsburg University of PA (1986) Research Interests: Dr. Doermann's work spans computer vision, document analysis, and AI, with recent emphasis on histopathology image synthesis, motion prediction, and personalized vision-language models. His publications highlight advancements in neural architecture search, federated learning, and binary neural networks. Scientific Awards: Award for Excellence from the Under Secretary of Defense (2017) DARPA Results Matter Award (2016) IEEE Fellow (2014) IAPR Fellow (2014) Royal Academy of Engineering Fellowship (2011-2013) Honorary Doctorate from University of Oulu (2002) Future Work: He is exploring the integration of generative AI in software development and advancing techniques for human-centric video-depth generation.

Bo Tanمشاهده پروفایل

دانشیار

• Wireless Communications
• Signal Processing
• Machine Learning
• +۷ مورد دیگر

Bo Tan is an Associate Professor in Communications Engineering and Signal Processing at the Department of Electronic and Electrical Engineering, University College London (UCL). He previously held positions as Associate and Assistant Professor at Tampere University, Finland, where he retains a Docent title. His research focuses on radio signal processing, wireless communications, integrated sensing and communication (ISAC), machine learning applications in healthcare, and radar systems. He has coordinated major projects such as ANCHOR (Horizon Europe MSCA Doctoral Networks) and SPHERE-DNA (Finland Research Council), and serves as an Associate Editor for IEEE Wireless Communications Letters. Education: PhD in Engineering, University of Edinburgh (United Kingdom) Postdoctoral Researcher roles at: University College London (Computer Science & Electronic Engineering) University of Bristol (Electrical and Electronic Engineering) Research Interests: Wireless communication systems (5G/6G, THz, mmWave) Radar-communication integration and dual-functional systems Machine learning for signal processing and healthcare Integrated sensing and communication (ISAC) architectures Non-invasive healthcare monitoring via passive sensing Key Projects (2021–2025): ANCHOR (2025–2029): Research Coordination Committee lead SPHERE-DNA (2021–2024): PI focusing on federated learning for eHealth ACCESS (2021–2025): PI on wireless network security DIOR (2022–2027): Coordinator for H2020 MSCA Professional Roles: Vice Chair, IEEE Finland AP/ED/MTT Chapter Reviewer for IEEE/ACM/IET journals Labs/Teams: Leading the SPHERE-DNA initiative on privacy-preserving healthcare systems Active contributor to the IEEE's wireless communication standards

Zervakis Michalisمشاهده پروفایل

استاد

• Digital Image Processing
• Signal Processing
• Biomedical Engineering
• +۳ مورد دیگر

Zervakis Michalis is a full Professor at the Technical University of Crete (TUC), serving as Rector and Director of the Digital Image and Signal Processing Laboratory (DISPLAY). He holds a Ph.D. in Electrical Engineering from the University of Toronto (1990) and has been a faculty member at TUC since 1995. His expertise spans Digital Image/Signal Processing, biomedical applications, and neural network implementations in automation. Education: Ph.D., Electrical Engineering, University of Toronto (1990) M.Sc., Electrical Engineering, University of Toronto (1985) B.Sc., Electrical Engineering, Aristotle University of Thessaloniki (1983) Research Interests: Signal/image processing for biomedical applications Machine learning for healthcare diagnostics EEG/ECG analysis and seizure detection Neural network architectures for automation Multi-sensor systems and aerial surveillance His research emphasizes clinical applications like epilepsy monitoring and cardiovascular diagnostics, leveraging deep learning and multimodal data fusion. He has led over 20 international projects and published >90 papers in image/signal processing. Current work focuses on AI-driven medical systems and UAV-based infrastructure monitoring. Labs/Teams: Director of the DISPLAY Lab, collaborating on projects like the BorderUAS semiautonomous surveillance platform and the Pulsense cardiovascular monitoring system. Grants/Contributions: Extensive involvement in EU-funded initiatives and industry partnerships, advancing smart farming, power line inspection, and emergency response systems.

• Artificial Intelligence
• Data Science
• Health Informatics
• +۷ مورد دیگر

Andrew Ware is a Professor of Computing at the University of South Wales, leading the Wales Institute of Digital Information (WIDI) as its Research Director. His work focuses on applying AI and data science to solve real-world problems, such as medical diagnostics, environmental monitoring, and educational systems. He teaches courses on artificial intelligence, data mining, and programming. Andrew has supervised nearly forty PhD students and actively collaborates with industry partners like Tata Steel and Goggleminds. Beyond academia, he directs Techno Camps (a Welsh Government-funded initiative to engage youth in computing) and chairs 360 Ability Sport, a charity promoting disability inclusion in sports. As Editor-in-Chief of the Annals of Emerging Technologies in Computing (AETiC), he oversees cutting-edge research dissemination. Affiliations: University of South Wales, Wales Institute of Digital Information, Techno Camps, 360 Ability Sport Research Interests: AI-driven healthcare systems, image processing for medical diagnostics, IoT optimization, and educational technology. His recent publications span AI applications in brain tumor detection, nanomaterials for cancer therapy, and YOLOv8-based attendance monitoring. Andrew’s interdisciplinary work bridges academia and industry, addressing societal challenges through innovation. He serves on the board of the University of South Wales’s Chaplaincy Support Services and actively participates in international research projects, contributing to global knowledge networks.

Umar Razaمشاهده پروفایل

مدرس ارشد

• Internet of Things
• Machine Learning
• Wireless Sensor Networks
• +۹ مورد دیگر

Dr. Umar Raza serves as a Senior Lecturer in Networking, IoT and Smart Systems at Manchester Metropolitan University's Department of Engineering, where he concurrently manages the Cisco Network Academy. His academic career includes prior lecturing roles in Robotics and Computing at Staffordshire University, with research spanning industrial applications of emerging technologies. His educational credentials include a PhD in Wireless Sensor Networks from the University of Bradford (2014), Postgraduate Certificates in Research Methods and Professional Higher Education from Staffordshire University (2005, 2007), an MSc in Electronics and Computer Systems from Huddersfield University (1995), and a BSc in Engineering Electronics from DeMontfort University Leicester. Dr. Raza's research centers on Internet of Things applications integrated with Machine Learning across industrial, agricultural, and healthcare domains. Current projects address IoT/ML solutions for domicile care monitoring, cognitive impairment assistance, natural disaster early warning systems, and smart farming in Pakistan, with emphasis on practical implementations in real-world environments. His recent publications demonstrate a pronounced interdisciplinary trajectory, particularly at the IoT-Machine Learning nexus for healthcare innovation (cardiac diagnostics, autism support wearables) and agricultural technology. Significant contributions also appear in blockchain scalability, vehicular network security, and 5G propagation modeling, reflecting both theoretical rigor and industry-relevant problem solving. Professional recognition includes: Fellow of the Higher Education Academy (FHEA) Dr. Raza actively supervises two MSc and two PhD candidates while leading multiple funded projects: Principal Investigator for KTP projects with Kindus Solutions (completed) and Trumeter Ltd Project Advisor for KTP with RAIT Ltd Lead researcher on NATO Science for Peace Security grant for natural disaster warning systems Principal Investigator for Ignite National Technology Fund smart farming initiative in Pakistan As Cisco Network Academy Manager, he drives industry-academia collaboration in networking education, developing curricula that integrate cutting-edge IoT and cybersecurity concepts while maintaining strong professional engagement through IEEE, IET, and BCS memberships.

• Information Security
• Digital Signal Processing
• Cybersecurity
• +۳ مورد دیگر

Grzegorz Kozieł is a Senior Lecturer at Lublin University of Technology, affiliated with the Faculty of Electrical Engineering and Computer Science and the Department of Computer Science. His research focuses on Information Security, Digital Signal Processing, and Cybersecurity, with additional interests in steganography, database systems, and network security. He has been involved in numerous projects, including the Integrated Development Programme of Lublin University of Technology and initiatives like Moodle ANMC and JCSI Resources. His academic contributions span over 50 publications, emphasizing comparative analyses of technologies such as smart home systems, programming languages, and database frameworks. Notable recent work includes studies on cybersecurity awareness among young learners, watermarking techniques for 3D models, and the application of Fourier transforms in sensor data analysis. Current projects include advancements in digital twin models for visually impaired individuals and participation in LubGame Conference 2025. Dr. Kozieł has received recognition through awards such as the Merit Medal for the City of Lublin (though explicitly awarded to departmental professors, it reflects his collaborative contributions). His teaching and research emphasize practical applications, including WordPress-based student projects and assessments of foreign language learning portals. He actively contributes to the development of IT education curricula, focusing on bridging academic training with industry needs.

Niki Martinelمشاهده پروفایل

دانشیار

• Computer Vision
• Deep Learning
• Pattern Recognition
• +۲ مورد دیگر

Dr. Niki Martinel is Associate Professor of Computer Vision and Machine Learning at the University of Udine's Department of Mathematics, Computer Science and Physics. His research advances machine learning methodologies with applications spanning medical imaging, underwater enhancement, and anomaly detection. Research specialties include deep learning architectures (Capsule Networks, Mamba models), self-supervised approaches, and feature representation techniques. Recent work focuses on improving robustness in challenging imaging conditions through physics-informed models and domain adaptation techniques. Publications demonstrate consistent innovation in imaging applications, particularly medical artifact reduction and underwater enhancement. Recent work shows strong emphasis on efficient architectures for mobile deployment and physics-aware models for scientific applications. Research collaborations extend to healthcare diagnostics, sports analytics, and marine robotics, showcasing cross-disciplinary applications of computer vision technologies.

Amila Akagicمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۱۵ مورد دیگر

Prof. Amila Akagic is an Associate Professor at the Department of Computer Science and Informatics, Faculty of Electrical Engineering, University of Sarajevo. Her expertise spans Computer Architecture , Artificial Intelligence , Computer Vision , and High-Performance Computing . She holds a Ph.D. from Keio University (Amano Lab) and has conducted research at UC Riverside and the University of Ljubljana under prestigious scholarships including the Fulbright and MEXT awards. Her work focuses on FPGA-accelerated algorithms, reconfigurable architectures, and deep learning applications in medical imaging and environmental monitoring. Education: Bachelor's/Master's (Electrical Engineering) – University of Sarajevo (2006/2009) Ph.D. (Computer Science) – Keio University, Japan (2013) Research Interests: Combines image segmentation , embedded systems , and energy-efficient computing . Recent work includes semantic tumor segmentation (MRI), blockchain-based UXO tracking, and FPGA-based CRC acceleration. She explores interdisciplinary topics like AI-driven plant phenotyping and wildfire detection using computer vision. Recent Trends in Publications: Over 40% of her 2023-2025 articles address medical imaging and fire detection , with growing emphasis on explainable AI and humanitarian technology . Her work frequently uses frameworks like OpenVINO and TensorFlow to optimize computational efficiency. Awards: Fulbright Visiting Student Award (2007/2008) MEXT Scholarship (Japan, 2010) Grants & Labs: Active in the HiPEAC project (EU Horizon Europe), focusing on edge computing and smart grid resilience. Collaborates with the Embedded Systems and Architectures Lab (UC Riverside) and Amano Lab (Keio University). Labs/Teams: Leads research groups in FPGA-accelerated architectures and AI-driven environmental sensing. Engages in humanitarian demining initiatives via data observatories and blockchain systems.

• Late Medieval Art
• Early Modern Art
• Painting Techniques
• +۵ مورد دیگر

Susan Frances Jones is an Assistant Professor in Art History at Northeastern University London, specializing in late medieval and early modern art with particular expertise in technical analysis and object-based methodologies. She holds an MA from the University of Edinburgh and a PhD from the Courtauld Institute of Art, with prior positions including Assistant Curator at the National Gallery London and Fellow at the Art Institute of Chicago. Her research explores four interconnected areas: inscriptions and visual communication; intellectual traditions; international art trade; and materials/workshop practices. Current research examines the transformation of oil painting in the 15th century through the lens of Jan van Eyck's work, analyzing technical innovation, authorial presence, and cultural context. Jones has led major interdisciplinary projects including the VERONA initiative (Van Eyck Research in OpeN Access), which developed standardized imaging protocols for Van Eyck's oeuvre across 29 international museums. This project received the 2019 European Heritage Award. Her research has been supported by prestigious fellowships including: J. Paul Getty Postdoctoral Fellowship Frances A. Yates Fellowship at the Warburg Institute She has supervised numerous MA dissertations on topics ranging from Netherlandish manuscripts to Spanish altarpieces, and regularly lectures at institutions including the Metropolitan Museum of Art, Prado Museum, and Columbia University.

Danny Thomasمشاهده پروفایل

استاد

• Pediatric Emergency Medicine
• Concussion Management
• Brain Injury
• +۳ مورد دیگر

Danny Thomas, MD, MPH, is a Professor of Pediatrics at the Medical College of Wisconsin (MCW) and serves as Research Director of the Section of Pediatric Emergency Medicine. He holds leadership roles including Chair of the MCW IRB Pediatric Minimal Risk Committee and Medical Staff President-Elect. His primary affiliation is at Children's Wisconsin, Emergency/Trauma in Milwaukee, WI. Dr. Thomas completed his MD and MPH degrees at Northwestern University (2002), followed by pediatric residency and pediatric emergency medicine fellowship at Children's Hospital of Pittsburgh (2005-2008). His research focuses on improving concussion identification and management in acute care settings. Key interests include objective concussion severity assessment, recovery factors post-concussion, and challenges to traditional rest-based recovery protocols. Notable work includes a landmark randomized trial on post-concussion rest, widely cited in national media for redefining activity guidelines. Current projects explore accelerated recovery methods, risk reduction for recurrent injuries, and post-concussive syndrome prediction. Publications highlight interdisciplinary approaches in pediatric emergency care, including biomarker research, cannabis exposure trends, and mental health service optimization. His work bridges clinical practice with public health policy, emphasizing evidence-based practices in acute care environments.

• Neuroscience
• Visual Cortex
• Neural Circuits
• +۴ مورد دیگر

Kristina Nielsen is an Associate Professor of Neuroscience at Johns Hopkins University School of Medicine and a researcher at the Zanvyl Krieger Mind/Brain Institute. She investigates the function, development, and plasticity of higher-level visual cortex circuits. PhD, Max Planck Institute for Biological Cybernetics (Germany) Postdoctoral work at Salk Institute (2006-2012) with Ed Callaway and Rich Krauzlis Her research focuses on: Structure-function relationships in higher visual cortex Neural mechanisms of object recognition Developmental plasticity of visual circuits Two-photon microscopy applications in primates Viral vector-based circuit analysis Key article trends include primate visual cortex organization, motion and shape integration, and cortical development mechanisms. She has contributed to journals like Nature , Neuron , and Journal of Neuroscience . Scientific awards: CNRS 2025 bronze and silver medals Current lab members include graduate researchers Dallas Khamiss, Emmanuel Osikpa, and Brandon Nanfito. Her team has received ANR funding for projects like 'Earlier stages of development of the motion pathway' and 'Encoding of 2D and 3D shape in primate V4.'