جست‌وجوی استاد و پژوهشگر

James Prittsمشاهده پروفایل

استادیار

• Computer Vision
• Underwater Robotics
• 3D Geometry
• +۵ مورد دیگر

Dr. James Pritts is a computer vision researcher currently working at the Institute of Computer Science, Kiel University, within the Marine Data Science group. He is affiliated with the Faculty of Engineering and contributes to interdisciplinary marine research through the KiTE early-career fellowship program. His work bridges robotics, computer vision, and ocean science, focusing on enabling autonomous underwater vehicles (ROVs) to operate effectively in challenging, low-visibility environments. His research interests include: Underwater visual localization and mapping Robust 3D reconstruction in turbid waters Geometric calibration of camera systems Sensor fusion (camera, IMU, DVL) Non-rigid reconstruction (e.g., jellyfish) Autonomous monitoring of marine ecosystems Dr. Pritts' work supports applications in marine biology, underwater archaeology, and infrastructure inspection. He develops algorithms that allow robots to assess their own perception accuracy, enabling reliable long-term monitoring of seagrass beds and fragile marine species. His research is deeply collaborative, involving partnerships with GEOMAR and MBARI, and aligns with Kiel University’s priority research areas such as Kiel Marine Science and Ocean Health. He has previously held research roles at NASA, DARPA, and Facebook Reality Labs, and was an Assistant Professor at the Ukrainian Catholic University. His academic journey reflects a strong focus on geometric computer vision and real-world deployment of complex systems. Notable scientific contributions include advancing calibration techniques for underwater optics and developing robust localization methods under refractive distortions. His work often requires solving multiple vision challenges simultaneously, such as refraction, non-rigid deformation, and sparse features. Dr. Pritts is actively involved in hands-on robotics, working closely with hardware engineers to deploy ROVs in coastal waters near Kiel. He emphasizes practical utility in research and is driven by the principle of being useful. He holds a PhD from the Czech Technical University in Prague (2020) and has conducted postdoctoral research at Chalmers University and the Czech Institute of Informatics, Robotics & Cybernetics.

Khaled Ksaibatiمشاهده پروفایل

استاد

• Pavement Engineering
• Transportation Safety
• Infrastructure Management
• +۷ مورد دیگر

Khaled Ksaibati is a Professor in the Department of Civil & Architectural Engineering at the University of Wyoming, College of Engineering and Physical Sciences. He serves as the Director of the Wyoming Technology Transfer Center and coordinates the WYDOT Certification Program, playing a key role in advancing transportation knowledge across the state. Education: B.S. in Civil Engineering, Wayne State University, 1984 M.S. in Civil Engineering, Purdue University, 1986 Ph.D. in Civil Engineering, Purdue University, 1990 His research focuses on pavement design, maintenance, and rehabilitation , with strong emphasis on low-volume and rural roads , gravel road management , and transportation safety . He has led numerous projects on tribal reservations and energy-impacted areas, contributing to sustainable and equitable infrastructure solutions. His work integrates field evaluation, material testing, and policy development. His recent publications highlight trends in pavement management optimization , safety improvements on rural highways , and cost-effective solutions for unpaved roads . These works span topics from recycled asphalt pavement to visual assessment systems and traffic impact modeling, reflecting a strong interdisciplinary and applied focus. Scientific and Professional Recognition: Director, Wyoming Technology Transfer Center Board Member, Mountain Plain Consortium Board Member, Transportation Learning Network (TLN) Coordinator, WYDOT/WCA Certification Program Member, Wyoming Safety Management System Committee Dr. Ksaibati has secured substantial research funding as Principal or Co-Principal Investigator from WYDOT, FHWA, and the Mountain Plains Consortium, supporting graduate students and advancing rural transportation safety. His projects include the Wyoming Rural Road Safety Program, tribal safety initiatives, and pavement material characterization. He actively advises students and leads research teams focused on infrastructure resilience and technology transfer. He is associated with key research entities including the Wyoming Technology Transfer Center and the Wyoming Rural Roads Safety Program , which serve as hubs for training, technical assistance, and applied research across Wyoming and regional tribal communities.

Jun Liمشاهده پروفایل

مدرس

• Data Analytics
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Dr. Jun Li is a Lecturer in Mathematics and Computer Science at Cranfield University's Centre for Computational Engineering Sciences. His expertise spans Data Analytics, Machine Learning, Deep Learning, and Mathematical Modelling applied to diverse domains including aerospace, urban planning, and cybersecurity. BSc in Computer Science from QingDao University MSc in Software Engineering from LondonMet University PhD in Neural Networks from LondonMet University Dr. Li's research focuses on integrating Machine Learning with High Performance Computing and Mathematical Modelling. Key areas include: Large-scale Neural Network simulations in Neuroscience Deep Learning for aircraft engine defect detection via computer vision Neural Network language modeling with noise resilience Transport flow analysis using Complex Networks Urban agglomeration formation and imbalanced economy recovery modeling His recent publications highlight interdisciplinary applications of Machine Learning in transport systems, aerospace diagnostics, and cybersecurity. These works emphasize data-driven methods, GANs, and predictive analytics for real-world challenges. Current grants include funding from China's National Key Research and Development Program (2016YFC0503506) and CAS's Bingwei Excellent Young Scientists Programme (2015RC202). Dr. Li supervises MSc and PhD students in Artificial Intelligence, Machine Learning, and Big Data analytics. He collaborates with Cranfield's Centre for Computational Engineering Sciences, leading projects like: Airport service quality evaluation using Skytrax reviews Urban land-use transport modeling for policy impact analysis Imbalanced economic recovery frameworks post-disasters

Boyu Kuangمشاهده پروفایل

پژوهشگر ارشد

• Semantic Segmentation
• Object Detection
• Weakly Supervised Learning
• +۹ مورد دیگر

Dr. Boyu Kuang is a Research Fellow in Computer Vision and Artificial Intelligence at Cranfield University, affiliated with the Centre for Computational Engineering Sciences. His work bridges academic research with industrial applications in aviation, robotics, and energy systems. Current role: Research Fellow in Computer Vision and AI Key affiliations: Centre for Computational Engineering Sciences Research interests include semantic segmentation , object detection , weakly and self-supervised learning , multi-modal perception , and vision-language foundation models . His methodology emphasizes robust AI systems for low-resource industrial environments , with applications in aviation maintenance , robotics , and energy infrastructure monitoring . He leads the Artificial Intelligence and Machine Learning module at Cranfield. Key activities include the UKRI, ATI, and Airbus-funded ONEHeart project on autonomous systems and intelligent inspection. Collaborations span Stanford University , King’s College London , Civil Aviation University of China , and industry partners like Airbus and Leidos . Publications focus on vision-language models , multi-modal perception , and industrial AI . As an Editorial Board Member for Discover Artificial Intelligence (Springer Nature), he contributes to academic governance. Peer review experience includes 60+ journal manuscripts for venues like IEEE Transactions on Image Processing and Elsevier Neural Networks . Facilities utilized include DARTeC and AIRC .

Victor Hrymakمشاهده پروفایل

مدرس

• Workplace Safety
• Risk Assessment
• Safety Auditing
• +۳ مورد دیگر

Dr. Victor Hrymak serves as Lecturer and Programme Chair for the MSc in Environmental Health and Safety at Technological University Dublin's School of Food Science and Environmental Health within the Faculty of Sciences and Health. With over 30 years of workplace safety experience spanning regulatory enforcement in London/Dublin, fire safety consultancy, and expert witness testimony, he bridges academic research with practical industry applications. His academic credentials include a PhD in visual inspection and safety auditing from Trinity College Dublin, an MSc in Environmental Science from Brunel University, and a BSc in Environmental Health from the University of the West of England. He maintains professional standing as a Chartered Member of the Institution of Occupational Safety and Health (CMIOSH) and member of the Institution of Fire Engineers (IFE). Research focuses on two interconnected domains: visual inspection methodology refinement and systemic accident prevention strategies. His work investigates reliability improvements in hazard identification across construction sites, aircraft maintenance, and fire/rescue operations through systematic visual search techniques and risk assessment innovations. Current projects address construction safety and visual inspection conduct with active PhD supervision. Publication trends reveal consistent application of human factors principles to safety protocols, with increasing emphasis on EU policy frameworks like Vision Zero. His work connects technical inspection methods with regulatory compliance systems across aviation, education, and industrial sectors. Dr. Hrymak has supervised over 400 MSc dissertations and four PhD theses while securing collaborations with the European Agency for Safety and Health and European Commission. His advisory scope spans regulatory compliance tools, safety management system implementation, and statistical evaluation of safety interventions. He actively contributes to European safety initiatives including the EU 2021-27 Strategic Framework for Health and Safety at Work, demonstrating integration of academic research with transnational policy development through the European Commission's Advisory Committee on Safety and Health.

• Virtual Reality
• Augmented Reality
• Computer Vision
• +۶ مورد دیگر

Prof. Dr. Didier Stricker is a distinguished Professor of Computer Science at Rhineland-Palatinate University of Technology Kaiserslautern-Landau (RPTU) and serves as Scientific Director and Head of the Augmented Reality Research Department at the German Research Center for Artificial Intelligence (DFKI) in Kaiserslautern. He leads the Augmented Vision Group, which comprises approximately 30 researchers working across various domains of computer vision and augmented reality. His work bridges academic research with industrial applications through collaborations with major companies including Sony, Google, and John Deere. His educational background includes electrical engineering studies at the Polytechnic Institute of Grenoble and the Technical University of Karlsruhe. He earned his doctorate from the Technical University of Darmstadt in 2002 with a dissertation on "Computer Vision-Based Calibration and Tracking Methods for Augmented Reality Applications." Prof. Stricker's research spans virtual and augmented reality, computer vision, human-computer interaction, cognitive interfaces, and on-body sensor networks. His work focuses on developing practical applications that enhance human capabilities through advanced visual computing technologies. He has pioneered approaches in video and sensor analytics, particularly in creating cognitive interfaces that respond intelligently to user needs and environmental contexts. His recent publications reveal a strong emphasis on 3D scene understanding, real-time processing for augmented reality applications, and the integration of large language models with spatial reasoning capabilities. There's a clear trend toward more sophisticated multimodal approaches that combine vision, language, and spatial understanding to create more natural and intuitive human-computer interactions. Among his notable achievements: Innovation Prize of the German Society of Computer Science (2006) Organized the first IEEE & ACM International Symposium on Mixed and Augmented Reality (ISMAR) in 2002 Member of the ISMAR steering committee from 2000-2007 Multiple best paper and demonstration awards at major conferences Several registered patents in tracking and augmented reality technologies Prof. Stricker has supervised numerous PhD and Master's students through his leadership of the Augmented Vision Group. His research is supported by significant funding from both European and national research organizations, as well as through industrial partnerships. He serves as an expert reviewer for various research funding bodies and contributes to the academic community through editorial roles for journals and conferences in VR/AR and computer vision. The Augmented Vision Group under his direction maintains strong connections with industry partners and participates in numerous collaborative research projects including LUMINOUS, SHARESPACE, I-Nergy, BIONIC, and VIDETE. These projects span applications in language-augmented XR systems, social experiences in hybrid spaces, AI for energy systems, personalized body sensor networks, and 4D scene analysis.

• Laser Doppler Anemometry
• Thermography-Based Diagnostics
• Vision and Photogrammetry in Inspection
• +۱ مورد دیگر

Prof. Sławomir Zator holds the position of University Professor at the Department of Safety Engineering and Technical Systems under the Faculty of Production Engineering and Logistics at Opole University of Technology. His research focuses on advanced diagnostics techniques using laser Doppler anemometry, thermography, and vision-based methods for infrastructure and energy systems. He also explores energy management strategies in buildings, emphasizing smart home integration with renewable energy sources like photovoltaics and heat pumps. His work bridges theoretical advancements with practical applications in power line safety, industrial equipment monitoring, and sustainable energy solutions. Research interests include: Laser-based flow measurement innovations Non-destructive evaluation of boiler tubes and power line components Machine vision applications for structural diagnostics Optimization of building energy systems Recent publications highlight trends in smart grid energy scheduling, icing risk mitigation for power infrastructure, and hybrid energy storage integration. His work often features cross-disciplinary approaches combining thermal imaging, computational modeling, and automation technologies. Prof. Zator maintains an active research profile through collaborations with international institutions and contributes to technical education via course development in safety engineering and metrology.

Robert Sablatnigمشاهده پروفایل

دانشیار

• 3D Computer Vision
• Robot Vision
• Machine Learning
• +۷ مورد دیگر

Robert Sablatnig is an Associate Professor and Head of the Institute of Visual Computing & Human-Centered Technology at TU Wien. He leads the Computer Vision Lab and previously served as Head of the Institute of Computer Aided Automation (2005-2017). His roles include overseeing research in 3D computer vision, machine learning, and applications in industry and cultural heritage preservation. He holds a PhD (1997) and Habilitation (2003) from TU Wien, with a thesis focus on shape-based machine vision and visual inspection. Education: PhD in Computer Science (TU Wien, 1997), Habilitation in Applied Computer Science (TU Wien, 2003) Bachelor's/Master's/High School: Completed at Vienna University of Technology and BG/BRG Lerchenfeldstrasse, Klagenfurt. Research interests span 3D vision techniques, robot vision, deep learning applications, and heritage preservation through imaging technologies. He has authored/co-authored over 300 scientific publications and edited 17 conference proceedings. His work bridges theoretical advancements with practical applications in automation and cultural heritage. Professional affiliations include the Austrian Association for Pattern Recognition (OAGM/IAPR), IEEE, and roles as a certified expert witness in computer vision. Teaching focuses on computer vision applications, methodological foundations, and seminars for graduate students. Current courses include 'Scientific Presentation and Communication' and 'Dissertantenseminar'.

John Jerrimمشاهده پروفایل

استاد

• International Education Comparisons
• Teacher Mental Health and Wellbeing
• School Inspections
• +۳ مورد دیگر

John Jerrim is a Professor of Education and Social Statistics at University College London's IOE, leading the Quantitative Social Science research centre. His research focuses on international education comparisons, teacher mental health, and Ofsted inspection reforms. He advocates for evidence-based policy and practical data analysis training for students. Notable work includes studies on SATs' impact on teacher anxiety, inspector characteristics in Ofsted outcomes, and PISA assessment trends. He emphasizes collaboration across departments to enhance policy impact. His research aims to improve educational practices and systems globally. Director of the Quantitative Social Science research centre at IOE Leading expert on international educational assessments like PISA Research on Ofsted inspections' effects on schools and teachers Advocate for practical data skills in education curricula Research interests span education policy, mental health wellbeing, and systemic reform. His work bridges academic inquiry with real-world policy applications.

Shashi Bhushan Jhaمشاهده پروفایل

استادیار

• Automated Defect Detection
• Computer Vision
• Deep Learning
• +۶ مورد دیگر

Dr. Shashi Bhushan Jha is an Assistant Professor in the Department of Computer Science at the University of West Florida, part of the Hal Marcus College of Science and Engineering. He holds a Ph.D. in Electrical Engineering and Computer Science from Embry-Riddle Aeronautical University and teaches undergraduate and graduate courses such as Data Structures and Algorithms and Data Mining. Education: Ph.D., Electrical Engineering and Computer Science, Embry-Riddle Aeronautical University, 2023 M.S., Indian Institute of Technology Kharagpur, India, 2018 B.E., Nagpur University, India, 2013 His research centers on automated defect detection, computer vision, deep learning, machine learning, and optimization, with extensions into graph machine learning, data mining, sustainable computing, and cybersecurity. He applies these areas to industrial and societal problems such as visual inspection systems and real estate forecasting. His recent publications span high-impact journals and arXiv preprints, focusing on CNN-based defect detection, housing market prediction, and improvements in CNN model performance using image gradients. These works reflect a strong trend in applying deep learning to real-world data analysis and industrial automation. Dr. Jha actively serves as a reviewer for leading journals including Computers & Industrial Engineering , Information Sciences , and IEEE SMC , contributing to academic rigor in his field. He mentors students on capstone projects and has secured research experience through an industry internship at Cash App @ Block Inc., where he developed machine learning models using large datasets in collaboration with cross-functional teams. No formal grants are mentioned, but his applied research suggests strong industry-academia engagement. Dr. Jha is involved in research groups related to Artificial Intelligence and High-Performance Computing at UWF, contributing to ongoing projects in smart systems and scalable computing solutions.

Mehmet Baysanمشاهده پروفایل

دانشیار

• Bioinformatics
• Computational Biology
• Cancer Genomics
• +۸ مورد دیگر

Assoc. Prof. Dr. Mehmet Baysan is a faculty member in the Department of Computer Engineering at Istanbul Technical University (ITU), where he leads BaysanLab, focusing on computational genomics and bioinformatics. He holds a Ph.D. in Computer Science from The University of Texas at Dallas and completed postdoctoral training at the National Institutes of Health (NIH), specifically the National Cancer Institute. His academic journey includes research scientist roles at NYU Cancer Institute and Weill Cornell Medical College before returning to Turkey. B.S., Computer Engineering, Bilkent University (1999–2003) M.S. and Ph.D., Computer Science, The University of Texas at Dallas (2003–2008) Postdoctoral Fellow, National Cancer Institute, NIH (2010–2013) Dr. Baysan's research lies at the intersection of computer science and genomics, with a strong emphasis on cancer genomics , bioinformatics pipeline development , and machine learning applications in biological data. His work involves integrating multi-omics datasets to improve cancer diagnosis and treatment strategies, particularly in glioblastoma and colorectal cancer. He has developed tools like COSAP for comparative sequencing analysis and VCF Observer for variant file inspection. His recent publications (2023–2024) demonstrate sustained activity in somatic exome sequencing , genetic variant interpretation using tree-based models , and evaluation of NGS pipelines across different tumor microenvironments. These works appear in high-impact journals such as BMC Bioinformatics and Stresses , highlighting his contributions to methodological rigor and reproducibility in computational genomics. Dr. Baysan has led multiple research projects funded by TTO, SRP, and TUSEB, including initiatives on spinal muscular atrophy diagnostics and cancer sequencing algorithm comparisons. While specific awards are not listed, his h-index of 11 and 393 citations reflect significant scholarly impact. He mentors students through supervised research and advises on bioinformatics projects. His lab, BaysanLab, is actively involved in developing efficient and accurate sequencing analysis workflows, contributing to precision medicine. Collaborations span institutions like Istanbul University and involve interdisciplinary teams working on cancer and rare disease genomics.

Kenneth Wilsonمشاهده پروفایل

مدرس پاره‌وقت

• Structural Engineering
• Civil Engineering
• Christian Ethics
• +۳ مورد دیگر

Kenneth Wilson is a Part-Time Lecturer in the School of Engineering at Geneva College, teaching courses in Structural Analysis, Engineering Design, and Christian Ethics. He holds degrees in Civil Engineering, Structural Engineering, and Theological Studies, blending technical expertise with ethical and spiritual perspectives. M.A. in Theological Studies (1984), Gordon-Conwell Theological Seminary M.S. in Structural Engineering (1980), University of Illinois at Urbana-Champaign B.S. in Civil Engineering (1979), Cornell University Wilson's research focuses on structural engineering, particularly bridge design, fatigue analysis, and Load and Resistance Factor Design (LRFD) standards. His work bridges technical innovation with aesthetic and functional considerations, including strut-and-tie modeling and influence line-based load ratings. His technical publications span 1990-2017, addressing concrete structures, steel bridges, and software tools. Key themes include 3D analysis, LRFD compliance, and infrastructure resilience. Excellence in Part-Time Teaching award, Geneva College (2023) Denman Evangelism Award (1993) Wilson's professional experience includes roles at Michael Baker International, HNTB, and Modjeski & Masters, with certifications as a Registered Structural Engineer in Illinois and Professional Engineer in Pennsylvania. He also engages in Christian education missions in Uganda and campus ministry.

Nikola Miškovićمشاهده پروفایل

استاد

• Marine Robotics
• Autonomous Underwater Vehicles (AUV)
• Human-Robot Interaction
• +۳ مورد دیگر

Nikola Mišković is a Full Professor at the Department of Control and Computer Engineering, Faculty of Electrical Engineering and Computing, University of Zagreb. His work focuses on marine robotics and autonomous systems. Marine Robotics Autonomous Underwater Vehicles (AUV) Human-Robot Interaction Control Systems Sonar Data Processing His research explores underwater localization, formation control, and sensor integration with applications in aquaculture and environmental monitoring. Projects include EU-funded initiatives like FP7 CADDY , H2020 EXCELLABUST , and subCULTron . Key collaboration networks involve institutions in Croatia, Israel, and EU marine robotics consortia. His work demonstrates strong integration of simulation (Gazebo, LabVIEW) and real-world deployment.

Clayton M Prattمشاهده پروفایل

مدرس

• Asset Management
• Infrastructure Inspection
• Machine Learning
• +۱ مورد دیگر

Capt Clayton M. Pratt is an Instructor in Asset Management at the Air Force Institute of Technology (AFIT), affiliated with The Civil Engineer School. He holds a Master of Science in Civil Engineering from Virginia Tech and the University of Louisville, and a Bachelor of Science in Environmental Engineering from Clemson University. His professional roles include Readiness & Emergency Management Flight Officer, Project Development Team Lead, and Project Programmer in various Air Force bases. Pratt teaches courses such as WMGT 301 (Introduction to Asset Management), WMGT 417 (Activity Management), and WMGT 436 (Requirements & Optimization). He is a certified Professional Engineer (PE) in South Carolina and focuses on research areas including infrastructure inspection, machine learning applications, and data analysis. His expertise supports Air Force engineering education and operational readiness through continuing education programs.

Kevin Flemingمشاهده پروفایل

استاد

• Cognitive Psychology
• Attention Mechanisms
• Aviation Psychology
• +۵ مورد دیگر

Kevin Fleming is Professor and Chair of the Department of Psychology and Education at Norwich University's College of Arts & Sciences, where he has served since 2006. He holds a Ph.D. and M.A. in Cognitive Psychology from the University of New Hampshire and a B.A. from Lehigh University. His research examines cognitive models of attention through dual-process frameworks, applied to domains including aviation safety, surgical interventions, trauma response, and facial processing. Methodologies include eye-tracking and event-related potentials (ERPs). Notable projects include a $1.5 million USAF-DARPA grant studying pilot cognition during F-16 flight simulations. Fleming's recent publications demonstrate strong foci on: 1) Trauma and PTSD mechanisms, particularly hypervigilance and attentional biases measured via neurophysiological tools; 2) Visual processing of facial deformities including cultural/age influences; and 3) Non-cognitive predictors of academic success like grit. Aviation psychology remains a consistent interdisciplinary thread. He teaches laboratory-based courses in Aviation Psychology and flight simulation, alongside core psychology courses: PY 344 (Cognition), PY 360 (History and Systems of Psychology), and PY 263 (Perception).