جست‌وجوی استاد و پژوهشگر

Matthias Weißمشاهده پروفایل

استاد

• Staged photography
• Performance art and its mediatization
• History and aesthetics of music video
• +۲ مورد دیگر

Matthias Weiß is a Professor of Art History (Modern Art) at the University of Salzburg, leading both the Department of Art History and the Department of Art, Music, and Dance Studies. His academic career includes roles at the Free University of Berlin, the Max Planck Institutes in Florence and Rome, and currently directs the research project 'Images of Europe outside Europe' at the Bibliotheca Hertziana. Education: Studied architecture at TU Munich and art history/theater studies at FU and TU Berlin. Completed his doctorate (2007) on music video quotation techniques and habilitation (2019) on Joseph Beuys's television campaigns, earning the Joseph Beuys Research Prize. Research focuses on staged photography, performance art mediatization, music video aesthetics, transcultural exchanges, and architectural heritage preservation. Recent publications include interdisciplinary studies on global art history and European cultural identity. Teaching: Current courses include 'Introduction to 19th Century Visual Arts' and 'Iconography.' Awards: 2019 Joseph Beuys Prize, German Photobook Award nomination (2012), Gerda Henkel Foundation Scholarship (2002–2004). Labs/Teams: Leads Max Planck-funded research on transnational art historiography.

Horst Bischofمشاهده پروفایل

استاد

• Computer Vision
• Medical Computer Vision
• Object Recognition
• +۴ مورد دیگر

Horst Bischof is a Professor at the Institute for Computer Graphics and Vision at Graz University of Technology, Austria, and serves as Vice Rector for Research. He holds an M.S. and Ph.D. from Vienna University of Technology and a Habilitation (venia docendi) in applied computer science. His research focuses on computer vision, medical image processing, and robot vision, with over 750 peer-reviewed publications. He has organized major conferences like CVPR 2015 and ECCV 2018, and serves on editorial boards of prestigious journals. Key awards include the Most Influential Paper over the Decade Award (MVA 2019), Jan Konderink Award (ECCV 2018), and the 29th Pattern Recognition Award (2002). His work spans object recognition, medical computer vision, and visual learning. He leads research teams in robot vision and collaborates with industry partners like Infineon Technologies. Current projects include LiDAR-based sensing systems, autonomous vehicle technologies, and medical imaging solutions like MedEyeTrack for eye tumor treatment. His research emphasizes practical applications in robotics, automotive, and healthcare sectors.

• Computer Vision
• Optimization Methods
• Medical Imaging
• +۵ مورد دیگر

Thomas Pock is a Professor at the Institute of Visual Computing at TU Graz. His research focuses on computer vision, optimization methods, and mathematical models in computer vision, with significant contributions to medical imaging and inverse problems. He leads projects integrating deep learning with traditional variational methods for applications in MRI reconstruction, microscopy, and cardiac signal analysis. His work emphasizes efficient sampling techniques, uncertainty quantification, and algorithmic optimization in computational imaging. Education and academic background are not explicitly detailed in the provided texts, but his extensive publication record indicates expertise in interdisciplinary areas such as biomedical engineering, signal processing, and machine learning. Key research themes include variational networks, total variation methods, and generative adversarial networks (GANs) for image reconstruction and segmentation. His research spans collaborations in both academic and clinical settings, addressing challenges in 3D reconstruction, particle flow estimation, and cardiac electrophysiology modeling. Notable projects include Total Deep Variation and inverse Eikonal methods for medical data analysis. He actively contributes to open-source tools and frameworks for variational optimization and deep learning integration.

Georg Eckmayrمشاهده پروفایل

مدرس

• Digital Art
• Digital Culture
• Media Theory
• +۵ مورد دیگر

Georg Eckmayr is a multidisciplinary Lecturer at the University of Vienna , Department of Theatre, Film and Media Studies. He operates at the intersection of digital art, media theory, and algorithmic research, focusing on the entanglement of physical and machine-based realms. Doctorate under Peter Weibel on technical images Supervised academic programs at University of Applied Sciences St. Poelten Research Interests include: Digital culture and knowledge systems Algorithm-based sensuality and synthetic perception Media theory for post-identity societies Cross-disciplinary approaches (systems theory, feminist epistemology) Artistic Practice spans networked sculptures, robotic performances, and digitally signed objects, exploring contradiction as a productive force. His 2025 exhibition RAW MATERIAL & DATA GESTURES examines algorithmic politics. Scientific Recognition : 2006 Editorial Award, Vienna, @ KUNSTRAUM NOE Featured in RGBMTL 2025 (Montreal) and Hereafter The Art Project Academic Contributions include 15 recent articles on digital operative space, AI perception systems, and decentralized authorship, with keywords spanning Computer Science , Media Studies , and Artificial Intelligence . Collaborations with institutions like objkt.com and Studio Offbeat highlight his work.

Mislav Grgicمشاهده پروفایل

استاد

• Image Processing
• Biometrics
• Digital Video Communications
• +۵ مورد دیگر

Mislav Grgic is a Full Professor at the University of Zagreb's Faculty of Electrical Engineering and Computing (FER), where he has been working since 1997. He currently serves as President of the Deans' Club - Association of Deans of Croatian University Faculties (2022-present) and as the 10th Grand Master of The Society of Brethren of the Croatian Dragon (2021-present). Previously, he was Dean of FER (2014-2018), the youngest ever elected to this position, and served as Special Advisor to the Rector of University of Zagreb (2015-2022). His educational background includes B.Sc. (1997), M.Sc. (1998), and Ph.D. (2000) degrees in electrical engineering, all from University of Zagreb's Faculty of Electrical Engineering and Computing. He was a visiting researcher at University of Essex, United Kingdom (1999-2000). Professor Grgic's research focuses on image processing, biometrics, digital video communications, and medical imaging applications. His work spans digital mammography for breast cancer detection, face recognition systems, image compression, and computer-aided diagnosis. He has published over 200 papers in books, journals and conference proceedings, with significant contributions to the field of image quality assessment and medical imaging analysis. His recent publications demonstrate continued leadership in image processing, with emphasis on image quality assessment, medical imaging applications, and educational outreach. His work bridges theoretical research with practical applications, particularly in healthcare technology and engineering education. Among his numerous honors and awards are: Croatian State Science Award for 2018 for popularization of technical sciences Order of the Croatian Star with the Effigy of Rudjer Boskovic IEEE Croatia Section Distinguished Service Award Fran Bosnjakovic Award - highest award in technical sciences of University of Zagreb Multiple Josip Loncar medals from FER Professor Grgic has been actively involved in professional service, including as Chair of IEEE Croatia Section (2013-2016) and as a full member of the Croatian Academy of Engineering since 2012. He has served as a guest editor for special issues in prestigious journals focusing on facial image processing and pattern recognition-based methods for biometric re-identification.

Shohei Moriمشاهده پروفایل

پژوهشگر

• Mediated Reality
• Augmented Reality
• Diminished Reality
• +۴ مورد دیگر

Dr. Shohei Mori is a Junior Research Group Leader at the Visualization Research Center (VISUS) of the University of Stuttgart, Germany, and a Guest Associate Professor at Keio University, Japan. His research focuses on computational Mediated Reality, combining Augmented and Diminished Reality to address human-centered visual computing challenges. Key applications include education, entertainment, and cinematography. He has received numerous awards, including the IEEE ISMAR 2023 Best Journal Paper Award, IEEE VR 2022 Best Journal Paper Award, and multiple presentation/demonstration awards. His work spans grants such as the FWF-funded 3DDR project and collaborations with institutions like TU Graz, NTT Laboratories, and AVL List GmbH. Mori has taught courses on topics like Neural Rendering, Mixed Reality, and Computer Vision at institutions including TU Graz and FH Salzburg. His teaching emphasizes practical assignments and student research presentation management. His research interests include 3D reconstruction, light field displays, and perceptual aspects of mixed reality. He actively contributes to conferences like IEEE VR and ISMAR as a reviewer, chair, and committee member.

Horst Posseggerمشاهده پروفایل

پژوهشگر

• Computer Vision
• Autonomous Systems
• Multiple Object Tracking
• +۳ مورد دیگر

Horst Possegger is a Computer Vision researcher at the Institute of Computer Graphics and Vision at Graz University of Technology, Austria. He holds a BSc and MSc in Software Development and Business Management (2011, 2013) and a PhD in Computer Science (2018), all from Graz University of Technology. His research focuses on multiple object tracking/detection, human behavior analysis, and video analysis with applications in autonomous systems, LiDAR data processing, and robotics. Key projects include trajectory prediction, 3D object detection, and domain adaptation techniques for real-world scenarios. Recent work emphasizes cross-modal learning (e.g., vision-language models for LiDAR data), robust localization in challenging environments, and lightweight motion prediction models. He contributes to the Learning, Recognition & Surveillance (LRS) group and has published extensively in top-tier venues like IEEE/CVF CVPR and IROS. Publications span autonomous driving benchmarks, UWB-based localization, and warehouse automation. His work often bridges theoretical advancements with practical implementations in robotics and surveillance systems.

Chellappa Ramaمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Rama Chellappa is the Bloomberg Distinguished Professor at Johns Hopkins University (JHU), holding primary appointments in the departments of Electrical and Computer Engineering and Biomedical Engineering, under the Whiting School of Engineering and School of Medicine, respectively. He is affiliated with the Center for Imaging Science, Center for Language and Speech Processing, Institute for Assured Autonomy, and Mathematical Institute for Data Science. Previously, he spent 29 years at the University of Maryland as a College Park Professor and held roles at the University of Southern California and Purdue University. His research focuses on computer vision, machine learning, artificial intelligence, pattern recognition, and biometrics, with applications in smart cars, forensics, 2D/3D facial modeling, and medical diagnostics. Notable contributions include work on Markov random fields, 3D structure recovery, deep learning for face recognition, and gait recognition. He has published over 900 papers, achieving an h-index of 140. Rama Chellappa has been honored with prestigious awards, including the US National Academy of Engineering membership (2023), IEEE Jack S. Kilby Medal (2020), and K.S. Fu Prize (2012). He is a Fellow of multiple organizations, including IEEE, IAPR, and AAAS. His current collaborations at JHU School of Medicine involve applying computer vision to analyze facial expressions for monitoring stroke/dementia patients, autism detection in children, and digital pathology.

• Computer Science
• Multimedia Systems
• Medical Informatics
• +۲ مورد دیگر

Manfred Jürgen Primus is affiliated with the Faculty of Technical Sciences at the University of Klagenfurt , specifically within the Institute of Information Technology . His research focuses on Computer Science and Medical Informatics , particularly in Endoscopic Video Analysis and Human-Computer Interaction . Research themes: Medical video datasets, smoke detection in surgical footage, collaborative video retrieval systems Key technologies: Computer vision, machine learning, real-time image processing Applications: Surgical workflow optimization, medical education support Recent publications (2016-2018) demonstrate his work at the intersection of multimedia systems and healthcare, including advanced video analysis tools for laparoscopic surgery and endoscopic procedures. Despite a lack of explicit awards or student advisement records in the provided data, his contributions to Medical Imaging and Human-Computer Interaction are evident through technical publications and interdisciplinary collaborations.

• Cognitive Psychology
• Neuroscience
• Linguistics
• +۳ مورد دیگر

Karin Stromswold is a Professor in the Department of Psychology at Rutgers University - New Brunswick, affiliated with the Rutgers Center for Cognitive Science (RUCCS). She holds a PhD in Cognitive Science from MIT (1990) and an MD from Harvard Medical School (1991). Her research focuses on the cognitive and neural bases of language, addressing questions about language acquisition, processing, and genetic influences. Dr. Stromswold employs multidisciplinary approaches: cross-linguistic studies of language development, behavior genetic analyses, investigations into perinatal risk factors, and neuroimaging studies of sentence processing. Her work bridges心理学, neuroscience, and linguistics, with a particular emphasis on innate vs. learned aspects of language and the role of biological factors in linguistic development. Her research is supported by grants from the National Science Foundation (e.g., BCS-0446850) and the National Institutes of Health (e.g., HD37818). She directs the Language Acquisition and Processing Lab , which actively seeks undergraduate researchers to contribute to ongoing projects.

• Audio Signal Processing
• Music Information Retrieval
• Deep Learning
• +۳ مورد دیگر

Alexander Schindler is an External Lecturer at the Department of Information Systems Engineering at Technische Universität Wien. His research focuses on audio signal processing, music information retrieval, and deep learning applications in multimodal analysis. He coordinates the approacH project (2010–2013) funded by the European Commission, exploring audio-visual search engines. His academic background includes a Dipl.-Ing. in Technical Engineering and a Dr.techn. from TU Wien. Key research areas include acoustic scene classification, deepfake detection, and music video analysis. He has supervised students on topics like bird song identification and machine outage prediction. Notable publications span from unsupervised cross-modal learning (2020) to multi-modal MIR frameworks (2019). He holds a Bakk.techn. and advanced technical qualifications. Recent work includes advancements in deepfake audio detection (2025) and audio-visual surveillance systems (2024). His projects bridge theoretical research with practical applications in forensic analysis and industrial predictive maintenance. He contributes to international conferences like ACM SAC and DCASE, focusing on neural network architectures for audio analysis.

• Decision support systems
• Computational intelligence
• Recommender systems
• +۴ مورد دیگر

Distinguished Professor Jie Lu is Associate Dean (Research Excellence) in the Faculty of Engineering and Information Technology at the University of Technology Sydney (UTS), where she also serves as Director of the Australian Artificial Intelligence Institute (AAII). With over two decades of academic service at UTS, she has held progressively senior roles including Professor since 2007, Head of School of Software (2011-2014), and Director of the Centre for Artificial Intelligence (2017-2020) before assuming her current leadership positions. Professor Lu earned her PhD from Curtin University in 2000 and joined UTS the same year. Her academic journey progressed from Lecturer (2000-2001) to Senior Lecturer (2002-2004), Associate Professor (2005-2007), and ultimately Professor (2017-present). Professor Lu's research spans computational intelligence with particular expertise in decision support systems, fuzzy transfer learning, concept drift, and recommender systems. Her work bridges theoretical innovation with practical applications across transportation, telecommunications, healthcare, and education sectors. She has pioneered approaches in data-driven decision making that deliver tangible economic benefits and risk management solutions for industry partners. Her recent publications demonstrate continued leadership in AI research, with a focus on addressing challenges in non-stationary environments, out-of-distribution detection, cross-domain recommendation, and healthcare applications. Her work increasingly integrates large language models with specialized domain knowledge for enhanced decision support. Officer of the Order of Australia (2022) 2023 NSW Premier's Prize for Excellence in Engineering or Information & Communication Technology Australian Laureate Fellow (2019) IEEE Fellow for contributions to fuzzy machine learning and decision making (2018) Fellow of International Fuzzy Systems Association (2017) Australia's Most Innovative Engineer Award (2019) Multiple IEEE Transactions Outstanding Paper awards Professor Lu has supervised over 50 PhD students to completion, with half pursuing academic careers and half working in industry. She has secured over A$10 million in research funding as lead Chief Investigator, including 10 highly competitive ARC Discovery Projects. Her industry collaborations include significant projects with Optus, Sydney Trains, Domain Holdings, and healthcare organizations. As Director of the Australian AI Institute, Professor Lu leads Australia's largest AI research hub with over 250 researchers and PhD students. Under her leadership, AAII has secured 47 ARC grants and over 110 industry projects since 2017. She also serves as Editor-in-Chief of Knowledge-Based Systems, a leading journal in the field.

Jiebo Luoمشاهده پروفایل

استاد

• Computational social science
• Natural language processing
• Digital health
• +۴ مورد دیگر

Jiebo Luo is a Professor of Computer Science at the University of Rochester, where he has been since 2014. Prior to this, he spent over 15 years at Kodak Research Laboratories, rising to Senior Principal Scientist. His research spans computer vision, natural language processing, machine learning, and computational social science. BS and MS in Electrical Engineering from University of Science and Technology of China (USTC), 1989 and 1992 PhD in Electrical Engineering from University of Rochester, 1995 Dr. Luo's work focuses on bridging computer vision with social science through multimedia analysis, social media modeling, and digital health. His research includes innovative approaches to unsupervised learning, event recognition in videos, and multi-label classification. His publications highlight trends in deep learning for medical imaging, social media as sensors, and video analytics. Key subfields include semantic understanding, attention mechanisms, and multimodal fusion. 2021 ACM SIGMM Technical Achievement Award 2018 IEEE Region 1 Technological Innovation in Academic Award 2004 Eastman Innovation Award Fellowships: ACM, AAAI, IEEE, IAPR, SPIE Dr. Luo serves as Editor-in-Chief for IEEE Transactions on Multimedia (2020-2022) and has held leadership roles in multiple IEEE Technical Committees. He is a Data Science CoE Distinguished Researcher at the Goergen Institute for Data Science and a Board Member of the Greater Rochester Data Science Industry Consortium.

Stephen Maybankمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Camera Calibration
• +۵ مورد دیگر

Stephen Maybank is a Professor of Computer Science and former academic at Birkbeck, University of London (2004–2020). He holds visiting professorships at the Chinese Academy of Sciences' Institute of Automation and multiple Chinese universities, including Northwestern Polytechnical University and Zhongyuan University of Technology. His research focuses on computer vision, image processing, and statistical methods, with contributions to camera calibration and applications of the Fisher-Rao metric. Education: BA (Mathematics, 1st class, King's College Cambridge, 1976); PhD (Computer Science, Birkbeck, 1988). Research interests include visual surveillance, tracking, filtering, and projective geometry applications. He led EU projects like Advisor (video surveillance) and Anfas (flood analysis data fusion). Over 200 publications and one authored book highlight his prolific output. Awards include the IEEE Fellowship and ECCV's Koenderink Prize (2008). Grants: EU projects IST-1999-11287 (Advisor), IST-1999-11676 (Anfas). Advising: Supervised 12 PhD students; external examiner at Oxford, Imperial College, and others. Labs/teams: Collaborations span UK and China, including the National Laboratory of Pattern Recognition (CAS Beijing) and Wenzhou University.

• Deep learning
• Multimedia
• Applied statistics and mathematics
• +۸ مورد دیگر

Dacheng Tao is a Professor of Computer Science at the University of Technology Sydney (UTS), where he has been employed since 2010 and holds an ARC Future Fellowship since 2013. His work bridges statistics, mathematics, and advanced data analytics, with a focus on machine learning, computer vision, and multimedia technologies. Research Interests : Deep learning, computer vision, image processing, data mining, pattern recognition, geoinformatics, and video surveillance. Academic Contributions : Author of one monograph and over 400 publications in prestigious journals and conferences, with multiple best paper awards, including the 2014 ICDM 10 Year Highest Impact Paper Award. Honors and Recognition : 2015 ESI Highly Cited Researchers in Engineering and Computer Science. 2015 Australian Scopus-Eureka Prize, ACS Digital Disruptors Award (Gold Disruptor), and UTS Vice-Chancellor’s Medal for Exceptional Research. Fellowships in IEEE, IAPR, SPIE, OSA, IET, and BCS. Leadership and Service : Guest editor for 10+ special issues, editor for 10+ journals (including 7 IEEE Transactions), 4 conference keynote speeches, 60+ conference chairmanships, and service on 150+ major conferences and 60+ international journals.