جستجوی استاد راهنمای دانشگاهی

Henri Hurkmansمشاهده پروفایل

پژوهشگر

• Rehabilitation Medicine
• Stroke Rehabilitation
• Orthopedic Rehabilitation
• +۷ مورد دیگر

Dr. Henri Hurkmans is an active Researcher at Erasmus University Medical Center in Rotterdam, Netherlands, affiliated with the Erasmus School of Medicine and the Department of Orthopedics and Sports Medicine. His research program focuses on developing and validating technological interventions for rehabilitation, particularly in stroke recovery and orthopedic rehabilitation settings. Dr. Hurkmans' research interests center around the application of sensor technology and feedback systems to improve rehabilitation outcomes. His work spans multiple domains including stroke rehabilitation where he has pioneered mirror therapy protocols, orthopedic rehabilitation with focus on weight-bearing techniques, and sensor-based monitoring of patient movements in hospital settings. His research demonstrates how technological innovations can provide objective measurements and real-time feedback to enhance patient recovery. Analysis of his publication history reveals a clear progression from foundational work on mirror therapy and visual illusions for stroke patients (2012-2015) toward more recent applications of wearable sensor technology for monitoring hospitalized patients (2023-2024). His research consistently bridges clinical rehabilitation practice with technological innovation, with particular emphasis on validating measurement tools and developing practical clinical applications. Dr. Hurkmans has established productive collaborations with key researchers including Bussmann, Verhaar, Selles, and Ribbers across multiple publications. His work has demonstrated significant impact, with his 2015 mirror therapy article accumulating 59 Scopus citations and his 2014 visual illusion study receiving 47 citations, indicating substantial influence in the neurorehabilitation field.

Chuang Ganمشاهده پروفایل

استادیار

• Computer Vision
• Graph Deep Learning
• Multimodal Learning
• +۵ مورد دیگر

Chuang Gan is a distinguished researcher holding dual positions as a Principal Research Staff Member at the MIT-IBM Watson AI Lab and an Assistant Professor at the University of Massachusetts Amherst. His work bridges academic research and industrial applications in artificial intelligence, with particular focus on advancing the frontiers of computer vision and multimodal learning systems. Dr. Gan's research interests span multiple interconnected domains within artificial intelligence. He specializes in video understanding, with deep expertise in representation learning, neural-symbolic visual reasoning, audio-visual scene analysis, and embodied intelligence. His work frequently integrates graph deep learning techniques with neuro-symbolic approaches to create more interpretable and robust AI systems. The recurring themes across his research portfolio include developing models that can understand physical dynamics from visual inputs, creating systems capable of embodied reasoning, and building bridges between symbolic and neural approaches to artificial intelligence. His publications reveal a strong trend toward increasingly sophisticated multimodal systems that integrate visual, auditory, and linguistic information. Over time, his work has evolved from basic video understanding tasks to complex embodied reasoning systems capable of physical simulation, 3D scene understanding, and multi-agent collaboration. A notable pattern is the progression from analyzing static scenes to understanding dynamic physical interactions and embodied agent behaviors in increasingly complex environments. Microsoft Fellowship Baidu Fellowship Dr. Gan's research has received significant recognition from major technology companies through prestigious fellowships and has been widely covered by leading media outlets including CNN, BBC, The New York Times, WIRED, Forbes, and MIT Tech Review. His work at the MIT-IBM Watson AI Lab provides him with access to substantial resources for cutting-edge AI research, while his academic position enables him to train the next generation of AI researchers. His collaborations with prominent researchers like Antonio Torralba demonstrate his integration within the top echelons of the computer vision and AI research community. At the MIT-IBM Watson AI Lab, Dr. Gan leads research initiatives focused on advancing video understanding and embodied intelligence. His work contributes to the lab's mission of developing AI systems that can perceive, reason about, and interact with the physical world in more human-like ways. His research group likely focuses on developing novel architectures for multimodal learning, creating benchmarks for physical reasoning, and building systems that can transfer knowledge between simulation and real-world environments.

• Optimal Control
• Nonlinear Systems
• Differential Games
• +۳ مورد دیگر

Valery Afanasiev is a Tenured Research Professor at the School of Applied Mathematics, HSE Tikhonov Moscow Institute of Electronics and Mathematics (HSE MIEM) since 2012. His academic career spans over five decades, including roles at Moscow Institute of Electronics and Mathematics and part-time professorship at Moscow State University's Department of Physics since 2011. Doctor of Sciences in System Analysis, Management and Information Processing (1983) Candidate of Sciences (PhD) in Control Systems (1972) Master's Degree in Electronic Engineering (1966) His research focuses on optimal control and nonlinear systems , particularly through differential games and parametric optimization . Key contributions include viscosity solutions for Bellman-Isaacs equations and adaptive filtering algorithms for cosmic radiation parameters. Recent publications highlight his work on: Extended linearization methods for nonlinear systems Differential games with multiple pursuers and evaders Tracking problems under bounded disturbances Control of nonlinear systems with state-dependent parameters Scientific recognition includes: Best Teacher Award (2015) He supervises doctoral theses on control systems and has authored influential textbooks such as Mathematical Theory of Control Systems Design and Control of Uncertain Dynamic Objects .

Tuğrul TAŞCIمشاهده پروفایل

استادیار

• Artificial Intelligence
• Natural Language Processing
• Computer Vision
• +۳ مورد دیگر

Tuğrul TAŞCI serves as an Assistant Professor in the Department of Information Systems Engineering at Sakarya University's Faculty of Computer and Information Sciences, where he has maintained continuous academic service since 2001. His career progression includes Research Assistant positions across multiple university units before advancing to his current faculty role in 2016. His academic credentials include: Doctorate in Computer and Information Engineering (2014) from Sakarya University Institute of Science, thesis: Real-Time Motion Tracking with Particle Filtering Based on Data Fusing Master's degree in Computer and Information Engineering (2004) with thesis: Design of an Integrated Web-Based Distance Education System Bachelor's degree in Computer Engineering (2001) with thesis: Course Scheduling with Genetic Algorithms Dr. TAŞCI's research centers on Artificial Intelligence applications, particularly Natural Language Processing for Arabic text and Computer Vision . His work integrates particle filtering , data fusion , and optimization algorithms (e.g., Artificial Bee Colony, Firefly) to solve problems in text summarization, motion tracking, and image processing. Recent publications demonstrate expansion into deep learning for industrial defect detection and time series analysis. Analysis of his 2019-2024 publications reveals three dominant research trajectories: (1) Arabic NLP with focus on extractive summarization using PageRank and word embeddings, (2) Computer vision systems for motion tracking and text detection leveraging particle filters and curvature features, and (3) Hybrid optimization techniques applied to diverse domains from emergency management to customer churn prediction. Current academic advising activities and research grant details are not publicly documented in available sources. Similarly, no institutional laboratories or research teams are explicitly associated with his profile in the provided materials.

Severin Fowlesمشاهده پروفایل

استاد

• Critical Indigenous Studies
• Collaborative Archaeology
• Settler Colonialism
• +۴ مورد دیگر

Severin Fowles is a Professor of Anthropology and American Studies at Barnard College, where he chairs the Anthropology Department and directs the Archaeology Track. His scholarship merges archaeological methods with Critical Indigenous Studies, Art History, Religious Studies, and New Materialist Philosophy to reimagine the history of the American West. He has directed excavations at sites spanning ten thousand years—from early forager camps to 1960s hippie communes—and conducted landscape surveys like the Rio Grande del Norte National Monument rock art project and agricultural system research with Picuris Pueblo. PhD in Anthropological Archaeology, University of Michigan (2004) BA in Anthropology, Dartmouth College (1993) Fowles' research centers on Indigenous ontologies , collaborative archaeology with descendant communities (notably Picuris Pueblo, Comanche Nation, and San Antonio del Embudo's Indo-Hispano community), and visual culture as historical text. His recent articles explore multispecies archaeology (wolves in settler colonialism), rock art as counter-archives , and long-term visual culture trends in the Southwest. Key themes include settler colonialism , religious ecology , and historiographic critique . Scientific awards include multiple National Science Foundation grants , a Tow Professorship , and Presidential Research Awards . He has contributed to major edited volumes like The Oxford Handbook of Southwest Archaeology and authored An Archaeology of Doings: Secularism and the Study of Pueblo Religion . His teaching emphasizes Indigenous Place-Thought , material culture analysis , and collaborative field methods in New Mexico.

Aldo Geunaمشاهده پروفایل

استاد

• Economics of Innovation
• Science Policy
• University-Industry Relations
• +۷ مورد دیگر

Aldo Geuna is a Full Professor at the Department of Cultures, Politics and Society at the University of Turin, specializing in economic policy (SSD: SECS-P/02). His office is located at the "Luigi Einaudi" Campus in Turin, and he is currently on sabbatical leave until September 2026 during which time he is not supervising thesis work. Professor Geuna's research spans multiple areas within the economics of science, innovation, and technology. His primary interests include university-industry relations, research careers and academic mobility, gender issues in academia, science policy, and the history of the Italian automotive industry. He has made significant contributions to understanding how universities interact with industry, the impact of research assessment systems, and the dynamics of academic careers. His recent publications demonstrate a strong focus on the automotive industry, particularly examining the Italian automotive sector's evolution and its regional impacts in Turin. He also investigates PhD career trajectories, university-industry collaboration models, and the relationship between research funding, productivity, and gender. His work often employs comparative approaches, particularly between European and US contexts. Professor Geuna teaches Economics of Knowledge (CPS0831) and has supervised numerous theses on topics ranging from AI in medical diagnostics to electric vehicles and the history of the Italian automotive industry. His research has been published in leading journals including Research Policy, Industrial and Corporate Change, and Higher Education.

• Knee Osteoarthritis
• Rheumatology
• Chronic Pain
• +۵ مورد دیگر

Emma Haglund is a Clinical Associate Professor at Lund University's Faculty of Medicine, serving as a supervisor and physiotherapist within the Rheumatology research project and Spenshult Arthritis Group. Her work directly contributes to UN Sustainable Development Goals for health and well-being, focusing on clinical research in musculoskeletal disorders and patient-centered care. Her research spans knee osteoarthritis pathogenesis, chronic pain mechanisms, and the intersection of physiotherapy with lifestyle interventions. She employs mixed-methods approaches including longitudinal cohort studies, accelerometer-based physical activity monitoring, and radiographic analysis to investigate how metabolic factors, occupational exposures, and health literacy impact disease progression and quality of life. Her fingerprint reveals deep expertise in patient-centered outcomes, adolescent health, depression comorbidity, and spondyloarthritis. Recent publications demonstrate a strong focus on objective measurement techniques (e.g., accelerometry for physical activity quantification) and longitudinal tracking of radiographic changes in early osteoarthritis. Her work consistently bridges clinical practice with epidemiological research, emphasizing real-world applications for pain management and functional improvement in arthritis patients. No scientific awards are currently documented in available sources. Dr. Haglund actively supervises research projects and students within rheumatology, with her grant-funded work evidenced by 29 research outputs including 27 articles and a doctoral thesis compilation. Her collaborations span multiple countries as shown in institutional network maps, reflecting international engagement in arthritis research. As a core member of the Spenshult Arthritis Group—a leading Swedish research center for rheumatic diseases—she contributes to multidisciplinary teams investigating arthritis mechanisms, treatment optimization, and patient education strategies through clinical trials and observational studies.

Serkan Özbayمشاهده پروفایل

دانشیار

• Electrical and Electronics Engineering
• Signal Processing
• Computer Vision
• +۴ مورد دیگر

Serkan Özbay serves as an Associate Professor in the Department of Electrical and Electronics Engineering at Gaziantep University's Faculty of Engineering, Turkey. With academic appointments since 2003, he progressed from Lecturer to his current position (2024), maintaining continuous affiliation with the institution where he also completed all his degrees. His career demonstrates deep institutional integration and vertical advancement within the same department. His academic credentials were entirely earned at Gaziantep University: Doctorate (2007-2015): Institute of Science, Electrical and Electronic Engineering Master's (2003-2006): Institute of Science, Electrical and Electronics Engineering (Thesis) Licence (1997-2002): Faculty of Engineering, Electrical and Electronics Engineering Özbay's research centers on signal processing and machine learning applications, with significant contributions to computer vision for medical diagnostics (sinus segmentation, lung cancer detection) and security systems (image/video forgery analysis). His work bridges theoretical algorithms with practical implementations in edge computing and biomedical devices, evidenced by projects like real-time fall detection systems and metamaterial antennas. Recent publications show intensified focus on deep learning since 2020, particularly convolutional neural networks for medical imaging and object tracking. His publication trajectory reveals strategic interdisciplinary expansion: early work (2007-2015) concentrated on spectrum sensing and wireless communications, while post-2020 output pivoted toward AI-driven medical applications and digital forensics. Approximately 70% of his 22 publications (2019-2023) involve deep learning implementations, with strong institutional collaboration patterns—85% co-authored with Gaziantep University researchers. Journal publications predominantly appear in Q2-Q4 SCI-indexed engineering journals, while conference papers target international venues in computer vision and biomedical engineering. As an academic advisor, Özbay has supervised 16 graduate theses (1 PhD, 15 Master's) between 2017-2025, with 11 completed in 2020-2023 alone. Current advisees include students developing Raspberry Pi-based plate recognition systems and real-time fall detection solutions. He additionally mentors 15 undergraduate students in senior design projects annually, as evidenced by 2024 EEE498/499 project meetings. Administrative leadership includes Deputy Head of Department (2016), Erasmus Coordinator (2015-2016), and Institute Board membership (2020-2023).

• Blockchain technologies
• Quantum Computing
• Artificial Intelligence
• +۷ مورد دیگر

Dr. Ernestas Filatovas is a Senior Researcher and Chief Researcher in the Project at Vilnius University's Institute of Data Science and Digital Technologies (formerly Institute of Mathematics and Informatics), where he has been affiliated since 2013. He leads the Blockchain and Quantum Technologies Group, focusing on cutting-edge research at the intersection of quantum computing, blockchain, and artificial intelligence. Previously, he served as an Associate Professor and Lecturer at Vilnius Gediminas Technical University's Faculty of Fundamental Sciences from 2013 to 2019. Dr. Filatovas earned his Doctor of Technology in Computer Science Engineering from Vilnius University Institute of Mathematics and Informatics in 2012. His dissertation, supervised by Prof. Dr. Olga Kurasova, focused on the interactive solution of multi-criteria optimization problems. His research spans multiple high-impact domains, with particular expertise in blockchain technologies, quantum computing, artificial intelligence, and machine learning. He has pioneered work in quantum blockchain implementations, reproducibility of AI research through blockchain verification, and quantum machine learning applications. His research bridges theoretical computer science with practical applications in financial markets, healthcare, and distributed systems. His extensive publication record—over 50 scientific papers, with more than 25 in Clarivate Analytics-indexed journals—demonstrates consistent productivity and international collaboration. Recent work shows a clear trajectory toward quantum-enhanced AI systems, blockchain-based research verification frameworks, and quantum algorithms for practical problems. Laureate of the 4th LMA Young Scientists' Conference (2014) INFOBALT scholarship 2nd place winner (2014) Lithuanian State Science and Studies Foundation funding recipient (2009, 2010) Recognized as one of Lithuania's most active doctoral students Master's degree with honors (2006) Dr. Filatovas leads multiple significant research projects, including the 2021-2024 project 'Solving the problems of reproducibility of scientific research in the field of artificial intelligence using blockchain technologies' as team leader, and the 2023-2027 project 'Development and validation of quantum machine learning methods using prepared datasets' as Chief Researcher. He has also contributed to international collaborations such as the Spanish-funded 'High Performance Solutions for Modern Scientific Computing Challenges' (2019-2021). His popular science contributions, including the VU news portal article 'Quantum Computing: Who and Why?', demonstrate his commitment to science communication. As a key member of Vilnius University's Blockchain and Quantum Technologies Group, Dr. Filatovas contributes to Lithuania's growing reputation in quantum computing research and blockchain innovation, working closely with international collaborators across Europe.

• Visual Cognition
• Brain Imaging
• Object Recognition
• +۶ مورد دیگر

Hans Op de Beeck is a full professor at KU Leuven's Faculty of Psychology and Educational Sciences. He chairs the Brain and Cognition research unit within the Laboratory for Biological Psychology and is a member of the KU Leuven Brain Institute. His work bridges cognitive neuroscience, visual perception, and computational modeling approaches to understand human visual cognition. Professor Op de Beeck's research focuses on visual cognition, particularly object recognition, category selectivity, and the neural organization of the visual system. His work combines multiple methodologies including fMRI, computational modeling, and behavioral experiments to investigate how the brain processes visual information. His research spans basic visual neuroscience to applied domains like aesthetic appreciation and social scene processing. His recent publications demonstrate a strong trend toward integrating computational approaches with human neuroscience. The research spans visual category representation, social cognition, aesthetic processing, and cross-modal plasticity. A notable pattern is the increasing use of artificial neural networks to model and understand human visual processing, as well as the exploration of visual expertise in various domains including Braille reading and chess expertise. Professor Op de Beeck is actively involved in numerous research projects as both promotor and co-promotor, with ongoing work spanning from 2022 to 2030. His laboratory, the Brain and Cognition unit, investigates the fundamental principles of visual processing and their applications in understanding both typical and atypical cognitive functioning.

Abhinav Kumarمشاهده پروفایل

استاد

• Wireless Communications
• Machine Learning
• Internet of Things
• +۳ مورد دیگر

Abhinav Kumar is a Professor at Indian Institute of Technology Hyderabad , affiliated with the Department of Electrical Engineering, Department of Artificial Intelligence, and Department of Engineering Science. His research bridges Wireless Communication & Networking , Machine Learning , and Green Communication in emerging technologies like V2X , UAVs , and IoT . Education: PhD in Electrical Engineering from IIT Delhi (2013), Dual B.Tech/M.Tech from IIT Delhi (2009) Professional Roles: IEEE Senior Member, Editor of IEEE Transactions on Communications, Reviewer for multiple IEEE journals His research focuses on resource allocation in 5G networks, security in wireless systems, and machine learning applications for UAVs and mmWave radars. Recent projects include funded work on 6G integrated sensing, digital twin networks, and OTFS modems. Students under his guidance explore topics like QoE modeling , drone detection , and energy-efficient IoT protocols . Key publication trends combine machine learning with mmWave radar , VLC , and NOMA systems. He has co-authored over 25 journal articles since 2013, with a focus on 5G/6G , UAV communication , and edge computing . He leads the Wireless Communications and Networking (WiCoN) Laboratory , mentoring 25+ PhD and MTech students on projects ranging from smart triage systems to e-waste battery analysis . His lab has produced multiple IEEE Graduate Congress Best Thesis Award winners.

Sanaul Hoqueمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Biometrics
• Security Systems
• +۶ مورد دیگر

Dr. Sanaul Hoque is a Senior Lecturer in Secure Systems Engineering at the University of Kent's School of Engineering and Digital Arts, where he also serves as Course Lead for Electronic and Computer Engineering. His research focuses on biometric security systems, computer vision, and pattern recognition applications with over 79 publications documented in the Kent Academic Repository. Dr. Hoque's primary research interests include: Computer Vision and Pattern Recognition Biometrics and Security Systems Document Analysis and Modeling Encryption and Secure Systems Multi-Expert Fusion Techniques EEG-based Biometric Recognition His extensive publication record spanning over two decades demonstrates expertise in developing innovative biometric security solutions. Recent work focuses on neural network applications for security systems, explainable presentation attack detection, and EEG-based biometric recognition. His research shows a consistent trajectory toward more sophisticated and explainable biometric security systems that address real-world challenges in authentication and identification, with his most recent publication appearing in 2025. Dr. Hoque has maintained productive research collaborations with colleagues including Farzin Deravi, Konstantinos Sirlantzis, and Gareth Howells, resulting in numerous co-authored publications across various domains of biometric security. His work has appeared in reputable journals including Sensors, IEEE Access, and Pattern Analysis and Applications. As Course Lead for Electronic and Computer Engineering, Dr. Hoque plays a significant role in curriculum development and student mentorship within the engineering program at Kent. His expertise bridges theoretical computer science with practical security applications, particularly in biometric systems and secure document modeling.

K S Venkateshمشاهده پروفایل

استاد

• Signal processing
• Image processing
• Video processing
• +۳ مورد دیگر

K S Venkatesh is a Professor in the Department of Electrical Engineering at Indian Institute of Technology Kanpur (IIT Kanpur). His research spans multiple areas of signal and image processing with applications in computer vision and robotics. Education: PhD from IIT Kanpur M.Tech from IIT Kanpur B.E. from Bangalore University Professor Venkatesh's research focuses on signal processing, image and video processing, computer vision with applications in robotics, and signal and system theory . His work bridges theoretical foundations with practical applications, particularly in the domain of visual perception systems. He has made significant contributions to areas such as object occlusion handling, gesture recognition under challenging lighting conditions, image enhancement techniques, and efficient stereo depth computation. His recent publications demonstrate a strong focus on computer vision problems with practical applications. The research shows progression from fundamental signal processing techniques to more complex vision systems capable of operating in real-world conditions. Several of his papers have received recognition, including Best Paper Awards at prominent conferences. Scientific Awards: Best Paper Award at Second Michael Faraday IET India Summit 2013 Best Paper Award at IEEE INDICON, IIT Bombay, December 2013 Professor Venkatesh maintains active research collaborations, as evidenced by his co-authored publications with researchers from various institutions. His work appears in prestigious international conferences including IJCAI, IEEE INDICON, and specialized computer vision conferences. His office is located in room 207-A/ACES at the Department of Electrical Engineering, IIT Kanpur, where he leads research activities in signal and image processing.

Esmaeil Nadimiمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Data Science
• +۵ مورد دیگر

Esmaeil Nadimi is a Professor and Head of Unit at The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, where he leads the Applied AI and Data Science research unit. He holds multiple concurrent positions including Visiting Professor at Harvard University, Chair of Data Analytics at SDU eScience Center, and research roles with Innovationsfonden and Swiss National Science Foundation (SNSF) in Medicine & Biology and Health & Well-being domains. His educational background includes a Ph.D. in Electrical and Computer Engineering from Aalborg University (2008) and an M.Sc. in Electrical Engineering (Control Theory) from Sharif University of Technology (2004). Research focuses on foundational AI methodologies including Physics-Infused Learning, Meta & Transfer Learning, with applied research in healthcare (medical imaging, cancer detection, diabetic neuropathy), energy systems, and optical technologies. Core expertise spans machine learning, computer vision, statistical modeling, and medical AI systems development. Publications demonstrate strong emphasis on AI applications in medical diagnostics, particularly capsule endoscopy, cervical/colorectal cancer detection, and diabetic complication screening. Recent work increasingly addresses explainable AI frameworks and practical implementation pathways for clinical adoption. Leadership includes supervision of industrial PhD/postdoc programs and development of academic courses in AI/Data Science. Current grants involve Innovationsfonden and SNSF-funded projects. Leads multiple research teams focused on medical AI systems at SDU Applied AI and Data Science unit.

• Machine Learning
• Computer Vision
• 3D Geometry
• +۲ مورد دیگر

Dr. Jun Li is a Senior Lecturer at the School of Computer Science, Faculty of Engineering and Information Technology, University of Technology Sydney (UTS), Australia. He received his Ph.D. in Computer Science from Queen Mary University of London in 2009 and is affiliated with the Australian Artificial Intelligence Institute (AAII) at UTS. His research spans multiple domains within artificial intelligence, with primary focus on Machine Learning applications in computer vision and 3D geometry. Dr. Li has published extensively in high-impact journals including IEEE Transactions (TPAMI, TIP, TNNSLS) and Pattern Recognition, with recent work expanding into interdisciplinary research in earth science and marine applications. His research output demonstrates consistent productivity with numerous publications each year across diverse AI application areas. Dr. Li's work shows strong thematic progression from foundational computer vision techniques to applied interdisciplinary research. Early work focused on face hallucination and video super-resolution, while more recent publications address environmental applications using Graph Neural Networks for wave prediction and damage classification for disaster response. His research consistently bridges theoretical AI advances with practical real-world applications across healthcare, autonomous systems, and environmental science. AI to assist disaster emergency response (2023-2026) Applying Generative Adversarial Network in Medical Image Analysis (2020-2021) Big Massive Open Online Course (MOOC) Data Retrieval (2017-2020) As an educator, Dr. Li teaches core courses including '31005 Machine Learning' and '32513 Advanced Data Analytics Algorithms' at UTS, and is available for Masters Research and PhD student supervision, contributing to the development of next-generation AI researchers.