جست‌وجوی استاد و پژوهشگر

• Water Resources Engineering
• Flood Modeling
• Remote Sensing
• +۵ مورد دیگر

Ceyhun Özçelik is an Associate Professor in the Department of Civil Engineering at Muğla Sıtkı Koçman University, specializing in Water Resources Engineering with a focus on flood modeling, remote sensing, and Geographic Information Systems (GIS). His academic journey includes a Bachelor's and Master's degrees in Civil Engineering from Pamukkale University (1999, 2002), a second Master's in Geographical Information Systems from Dokuz Eylül University (2006), and a Doctorate in Civil Engineering from Dokuz Eylül University (2007). Özçelik's research interests span water resources engineering, flood modeling, remote sensing applications, hydrological analysis, and drought assessment. His work demonstrates a strong integration of GIS technologies with traditional hydrological methods to address complex water management challenges. He has developed spatiotemporal models for monthly flows and runoff by coupling GIS and remote sensing techniques, contributing significantly to the field of water resources management. His publication record shows consistent scholarly output with recent articles focusing on watershed flood risk indices, drought assessment using satellite observations, and analysis of flood events in Turkey. His research has practical applications in disaster management, particularly in flood risk assessment and response systems like the 'Akıllı CanMELEK' mobile tracking and communication system he developed. Uygulama Yarışması Birincisi, 18. Esri Kullanıcıları Konferansı (2013) Doktora Tez Ödülü (2008) Postdoctoral Fellowship for Foreign Researchers (2008) Turkish-Indian Cultural Exchange Program (1st among 12 candidates) (2007) Özçelik has supervised numerous graduate students working on topics including flood simulation, drought analysis, water distribution systems, and GIS applications in water resources. He has served as principal investigator for multiple research projects funded by various institutions including TÜBİTAK and the Development Agency, with recent work focusing on flood risk analysis in Bodrum, Şanlıurfa flood disaster comparison, and hydrological analysis of Gökçeler Stream. He actively contributes to the academic community through editorial work for journals including Teknik Dergi, Journal of Hydrology, and Water Resources Management, and has participated in numerous national and international conferences presenting his research on water resources and flood management.

• artificial neural networks
• operations research

Meltem KARAATLI is a Professor at the Faculty of Economics and Administrative Sciences, Süleyman Demirel University, with expertise in artificial neural networks and operations research. She holds a PhD in Business Administration from Süleyman Demirel University (2010), following an MSc (2005) and BSc (1999) in Industrial Engineering and Business Administration, respectively. Her research focuses on applying data mining and machine learning techniques to financial and economic problems, including stock market analysis, forecasting, and decision-making. Recent work explores cryptocurrency portfolio management (2024), Baltic Dry Index prediction (2023), and pandemic-era market clustering (2022-2021). She frequently employs NARX neural networks, LSTM/GRU models, and association rule mining. Publications span internationally refereed journals and national journals, with 15 recent articles (2021-2024) addressing topics like container port logistics (2022), football match modeling (2021), and hospital performance evaluation (2021). She co-authored the book "Social Aspects of COVID-19" (2021, IKSAD) and contributed to "SPSS Applied Multivariate Statistical Techniques" (2005, Asil Publications).

• Artificial Intelligence
• Neural Networks
• Machine Learning
• +۲ مورد دیگر

Adrián Peñate Sánchez serves as an Associate Professor in the Department of Computer Science and Systems at the University of Las Palmas de Gran Canaria, actively contributing to research groups GIR SIANI (Artificial Intelligence, Neural Networks, Machine Learning and Data Engineering) and IU Intelligent Systems and Numerical Applications. His research spans Artificial Intelligence, Neural Networks, Machine Learning, Data Engineering, and Data Analytics, with specialized focus on applying these technologies to marine-maritime environments through strategic AI implementation and data-driven solutions. Current work emphasizes comprehensive AI strategy design for high-technology incubators and real-world problem solving in data analytics. Scientific awards: None documented in available sources. He leads the regional project 'Launch, promotion, and positioning of the High Technology Incubator in Data Analytics and Artificial Intelligence applied to the marine-maritime environment (IAT Marino-Marítima)' (Spegc Reference: C2023/65), serving as main researcher for technical assistance in AI strategy design from June 2023 to March 2024. This initiative demonstrates active engagement in securing research funding and translating theoretical frameworks into practical applications. Dr. Peñate Sánchez maintains core affiliations with GIR SIANI and IU Intelligent Systems and Numerical Applications, driving collaborative innovation in intelligent systems development and numerical methods research within the university's technical ecosystem.

Hans-Joachim Schrammمشاهده پروفایل

مدرس ارشد

• Transport Economics
• Logistics
• Foreign Trade
• +۶ مورد دیگر

Hans-Joachim Schramm is a Senior Lecturer at WU Vienna University of Economics and Business in the Institute of Transport Economics and Logistics, and an external lecturer at Copenhagen Business School's Maritime Business program. With a diploma in economics from Humboldt University Berlin and a doctorate from Technical University of Dresden, he brings significant industry experience as a former freight forwarder to his academic work. His research focuses on international transport and logistics management, particularly trade facilitation measures, customs, foreign trade management, and controlling at transport and logistics service providers. His work spans economic and political issues across maritime, air, rail, and road transport sectors. Schramm has established expertise in Supply Chain Controlling, Digitalization, Air freight, Freight forwarding, Customs, Security and risk management, Supply Chain Financing, and various aspects of maritime transport. His publication portfolio shows a clear trend toward increasingly interdisciplinary research, combining traditional transport economics with digitalization, sustainability concerns, and geopolitical considerations. Recent work demonstrates particular attention to carbon emissions in freight transport, maritime safety systems, and the impacts of global events like the Suez Canal blockage on supply chains. ISM Best Supply Chain Paper Award at AOM Annual Meeting 2021 KLU Young Researcher Best Paper Award at IAME 2018 Best Paper Award at IAME 2016 CSCMP Teaching Innovation Award 2014 Schramm has been actively involved in numerous research projects, including investigations into cabotage in Austria, vehicle flagging out effects on the Austrian economy, transport industry consolidation through M&A, and automatic track changing systems. His international collaborations span across Europe and globally, with guest lecturing activities in Belgium, Denmark, Finland, France, Sweden, Hungary, China, and Cuba. He serves on editorial boards for International Journal of Logistics Management and Maritime Economics and Logistics, and has participated in peer review processes for numerous leading journals in his field.

Ostap Okhrinمشاهده پروفایل

استاد

• Econometrics
• Statistics
• Transportation Systems
• +۴ مورد دیگر

Ostap Okhrin serves as a Professor of Econometrics and Statistics at Dresden University of Technology, holding the Chair of Econometrics and Statistics with a special emphasis on Transportation Systems. His academic career is marked by a strong focus on methodological advancements in econometrics and statistics, applied to complex real-world problems in transportation and finance. Professor Okhrin's research interests span econometrics, statistical theory, copula modeling, time series analysis, and financial risk management. He has significantly expanded into machine learning and reinforcement learning applications for autonomous systems, with deep expertise in traffic flow modeling, autonomous driving, maritime navigation, and financial volatility estimation. His work bridges theoretical statistics with practical engineering challenges, particularly in transportation systems and risk forecasting, addressing high-dimensional data and dynamic environments through innovative methodological frameworks. Analysis of Okhrin's recent publications (2024-2025) reveals a pronounced interdisciplinary trajectory integrating reinforcement learning with transportation engineering. Key themes include drone-based trajectory data collection for traffic monitoring, algorithms for autonomous ships on inland waterways, and Sim2Real transfer frameworks for autonomous driving. Concurrently, he advances financial econometrics through high-frequency risk forecasting models incorporating realized moments. This dual focus demonstrates his ability to transfer statistical innovations across domains while maintaining rigorous theoretical foundations in copula theory and time series analysis.

Kari Tammiمشاهده پروفایل

استاد

• Mechatronics
• Autonomous Vehicles
• Electric Vehicles
• +۷ مورد دیگر

Kari Tammi serves as Professor and Dean of Aalto University's School of Engineering since 2015, concurrently holding the position of Chief Engineer Counselor at Finland's Administrative Supreme Court. His career spans industrial research leadership at VTT Technical Research Centre (2000-2015), postdoctoral work at North Carolina State University (2007-2008), and foundational research at CERN (1997-2000). His academic credentials include: MSc, Helsinki University of Technology, 1999 LicSc, Helsinki University of Technology, 2003 DSc, Helsinki University of Technology, 2007 Teacher’s Pedagogical Qualification, Häme University of Applied Sciences, 2017 Research Focus: Tammi pioneers in Mechatronics , Autonomous/Electric Vehicle Systems , and Energy Efficiency Optimization , with specialized expertise in Dynamics , Control Systems , and Digital Twin Applications . His work bridges theoretical innovation with industrial deployment across maritime, automotive, and manufacturing sectors. Publication Trends: Recent output (2024-2025) demonstrates concentrated advancement in industrial digital twins for crane operations, winter-condition autonomous perception, and marine energy systems. Key patterns include GPU-free real-time processing, semantic-enhanced metaverse architectures, and snow-robust sensor fusion techniques. Professional Leadership: As former VTT Team Leader and current Engineering Dean, Tammi directs cross-disciplinary research initiatives connecting academic theory with industrial practice, particularly in sustainable transportation and smart manufacturing ecosystems.

Dominic Hudsonمشاهده پروفایل

استاد

• Hydrodynamics
• Ship Design
• Energy Efficiency
• +۴ مورد دیگر

Dominic Hudson is Shell Professor of Ship Safety and Efficiency at the University of Southampton , leading the Centre for Maritime Futures . He serves as Head of the Maritime Engineering group and is a member of the Southampton Marine and Maritime Institute . Focus areas: hydrodynamics, energy-efficient ship design, decarbonisation Key collaborations: Shell Shipping, English Institute of Sport, British Swimming Teaching: ship design, hydrodynamics, power requirement prediction External roles: Royal Institution of Naval Architects (Chair 2002-2011), International Towing Tank Conference Education : BEng in Ship Science, University of Southampton (1994, First-Class) PhD in high-speed catamaran motion prediction, University of Southampton (1999) His research explores hydrodynamic optimization for maritime energy efficiency, focusing on future fuels , digitalisation , and crew safety . Recent work includes hydrogen fuel storage models, LNG boil-off gas prediction, and wind-propulsion yaw moment analysis. The Centre for Maritime Futures drives multidisciplinary projects in maritime decarbonisation and digital oceans. Scientific Awards : Vice Chancellor's Teaching Award (2008) Wakeham Prize (2002) Landrini Award (2013) Multiple Bronze Medals from RINA (2002, 2004, 2005, 2014, 2015) As a Chartered Engineer with industry experience at Three Quays Marine Services (2003), he has coordinated Ship Science courses (2008-2011) and directed programs (2011-2013). His academic leadership extends to visiting positions at Yokohama National University (2008) and Nanyang Technological University (2011-2016), plus collaborations with IHPC-SMMI Joint Laboratory in Singapore.

Adrian Bodenmannمشاهده پروفایل

پژوهشگر ارشد

• High-resolution Seafloor Mapping
• Autonomous Underwater Vehicles (AUVs)
• 3D Reconstruction Uncertainty Analysis
• +۴ مورد دیگر

Adrian Bodenmann is a Research Fellow at the University of Southampton , affiliated with the Maritime Engineering Group and the Ocean Perception Group . His work focuses on high-resolution seafloor imaging, autonomous underwater vehicle (AUV) operations, and uncertainty analysis in 3D reconstructions. Research Interests : High-resolution visual seafloor mapping for benthic habitat analysis Remote awareness in autonomous offshore mapping Uncertainty characterization in digital 3D reconstructions Trust in human-machine interactions (HMI) Publication Trends : Adrian's recent work emphasizes AI-driven seafloor mapping, AUV-based environmental monitoring, and uncertainty quantification. He explores applications of self-supervised learning, SLAM algorithms, and low-bandwidth data transmission for marine robotics. Education & Career : Graduated from Ecole Polytechnique Fédérale de Lausanne (EPFL) with degrees in microengineering (2009). Worked at the University of Tokyo before joining Southampton in 2017 to develop the BioCam seafloor mapping system. Field Experience : Participated in 15 ocean expeditions across the Pacific, Atlantic, and North Sea, accumulating over 6 months of at-sea research aboard Japanese, American, and British research vessels.

Huseyin Topalogluمشاهده پروفایل

استاد

• Revenue Management
• Pricing Analytics
• Operations Research
• +۴ مورد دیگر

Dr. Huseyin Topaloglu is the Howard and Eleanor Morgan Professor at the School of Operations Research and Information Engineering at Cornell University and Cornell Tech . He holds a B.S. in Industrial Engineering from Bogazici University (1997), an M.A. in Operations Research from Princeton University (1999), and a Ph.D. in Operations Research from Princeton University (2001). Education: B.S. Industrial Engineering (1997) – Bogazici University M.A. Operations Research (1999) – Princeton University Ph.D. Operations Research (2001) – Princeton University His research focuses on revenue management , pricing analytics , assortment optimization , and stochastic dynamic programming . Recent work includes advancements in multinomial logit models , network revenue management , and dynamic inventory allocation . He has published extensively in leading journals such as Operations Research , Management Science , and M&SOM , often collaborating with researchers like Y. Bai , P. Rusmevichientong , and O. El Housni . His 15 most recent publications (2024–2003) demonstrate expertise in revenue management using multinomial logit models , dynamic programming , and stochastic optimization . Key subfields include assortment planning , network revenue , pricing under uncertainty , and approximation algorithms for complex systems like ambulance redeployment and airline capacity control . He has also authored books like Revenue Management and Pricing Analytics (2019) and Fundamentals of Linear Optimization (2021).

Tianlong Liuمشاهده پروفایل

استادیار

• Artificial Intelligence in Engineering
• Machine Learning Applications
• Process Control and Optimization
• +۶ مورد دیگر

Tianlong (Taylor) Liu is an Assistant Professor in the Department of Chemical and Biochemical Engineering at Western University. His academic journey includes a Ph.D. in Civil Engineering from the University of British Columbia (2020), an M.A.Sc. from South China University of Technology, and a B.Eng. from Qilu University of Technology. Research Focus AI-Enhanced Process Control and Optimization Machine Learning for Industrial Data Analysis Physics-Informed Machine Learning (PIML) Large Language Models (LLMs) in Engineering His publications span machine learning , environmental engineering , and chemical process optimization , with recent work on AI-driven conductive polymer development, water quality prediction, and industrial wastewater treatment. He actively collaborates with industry partners across engineering disciplines. Education Ph.D., Civil Engineering, University of British Columbia (2020) M.A.Sc., Chemical Engineering, South China University of Technology B.Eng., Chemical Engineering, Qilu University of Technology

Vishal M. Patelمشاهده پروفایل

استادیار

• Signal and image processing
• Computer vision
• Machine learning
• +۲ مورد دیگر

Vishal M. Patel is an Assistant Professor in the Department of Electrical and Computer Engineering at Johns Hopkins University, with research focusing on signal processing, computer vision, and biomedical applications. His work bridges machine learning with medical imaging and biometrics. Ph.D. in Electrical Engineering, University of Maryland, College Park (2010) Dr. Patel's research centers on medical image analysis, surgical video processing, and bias mitigation in generative models. He develops diffusion-based frameworks for ophthalmic applications like cataract surgery analysis and nystagmus video generation, while advancing face recognition systems and image restoration techniques under unconstrained conditions. His recent work integrates vision-language models for zero-shot classification in satellite imagery and maritime surveillance. His 2025 publications reveal a strong emphasis on medical AI, particularly in surgical video understanding and neurological disease phenotyping using eye movement data. Key trends include physics-aware video generation guided by large language models, identity-preserving face restoration, and robust bias mitigation in diffusion-based synthesis. The work consistently addresses real-world challenges in medical imaging, remote sensing, and biometric security. Major recognitions include: 2016 ONR Young Investigator Award 2016 Jimmy Lin Award for Invention A. Walter Tyson Assistant Professorship Award Best Paper Awards at IEEE AVSS 2017 and IEEE BTAS 2015 Two Best Student Paper Awards at IAPR ICPR 2018 Best Poster Awards at BTAS 2015 and 2016 As an Associate Editor for IEEE Signal Processing Magazine and IEEE Biometrics Compendium, Dr. Patel shapes scholarly discourse in his field. His ONR Young Investigator Award supports high-impact research in active learning for surgical videos, while editorial roles and technical committee memberships demonstrate leadership. Though student names aren't specified, his lab trains graduate researchers in medical computer vision. Dr. Patel leads a research laboratory focused on computer vision for biomedical applications, developing frameworks like GenVOG for nystagmus video generation and StepAL for surgical step detection. The lab pioneers diffusion models for medical image synthesis, surgical skill assessment, and robust biometric systems, with strong ties to ophthalmology and neurology applications.

• Artificial Intelligence
• Machine Learning
• Big Data Analytics
• +۷ مورد دیگر

Göran Falkman is an Associate Professor of Computer Science at the University of Skövde, working within the Department of Information Technology at the School of Informatics. His research spans artificial intelligence, machine learning, big data analytics, and human-computer interaction, with applications in transportation, healthcare, and defense domains. His educational background includes a PhD in Computing Science and he holds the Swedish academic title of Docent in Computer Science. He has supervised numerous PhD students including Niclas Ståhl, Rakesh Rana, Ulrika Ohlander, and Maria Riveiro. Falkman's research interests focus on developing AI systems that effectively support human decision-making. His work includes driver intention recognition, uncertainty quantification in deep learning, maritime anomaly detection, and cockpit interface design for fighter pilots. He has developed approaches for interactive clustering, visual data analysis, and information fusion that bridge the gap between complex algorithms and human understanding. His recent publications demonstrate a strong trajectory in applying deep learning to transportation safety, particularly driver intention recognition, while maintaining his longstanding interest in human-centered AI systems. His work shows increasing sophistication in uncertainty modeling and probabilistic approaches to machine learning. Falkman has led major research projects including BISON (Big Data Fusion), BIDAF (Big Data Analytics Framework), and collaborations with Saab Aeronautics on human-machine interfaces for distributed decision-making in aviation contexts. He has supervised numerous PhD students across diverse applications of AI, from drug design to fighter pilot teamwork, demonstrating his ability to guide research at the intersection of theory and practical application. His work consistently addresses the challenge of making complex AI systems transparent and trustworthy for human users.

• Data Mining
• Machine Learning
• Multidimensional Data Analysis
• +۴ مورد دیگر

Dr. Gintautas Dzemyda is a leading research professor in data mining, machine learning, and multidimensional data visualization. With over 30 years of academic contributions, he has authored/co-authored 49+ publications and participated in 20+ conferences, including WorldCIST and Baltic DB&IS. His work spans medical imaging, financial security, and maritime decision support systems. Research Focus: Multidimensional Scaling (MDS), Neural Networks, Medical Image Analysis Key Collaborations: Olga Kurasova, Viktor Medvedev, Martynas Sabaliauskas Research Interests include: Advanced Data Visualization Techniques Machine Learning for Medical Diagnostics Fraud Detection in Financial Systems Decision Support Systems for Maritime Navigation Optimization of Neural Network Architectures Dimensionality Reduction Methods Scientific Awards (none explicitly mentioned).

• Raman Spectroscopy
• Bone Biology
• Medical Diagnostics
• +۷ مورد دیگر

Dr. Jemma Kerns serves as a Senior Lecturer and Director of Research at Lancaster Medical School, Lancaster University, a position she has held since August 2018. As Director of Research, she champions and advocates for the medical school's research activities while maintaining an active research program focused on spectroscopic techniques for healthcare applications. Her research primarily centers on developing Raman and infrared spectroscopy techniques for early diagnosis of bone conditions including osteoporosis, osteoarthritis, and osteogenesis imperfecta. She is particularly interested in advancing computational methodologies for spectral processing and analysis to translate these techniques into clinical settings for non-invasive, high-throughput medical diagnosis. Her work spans multiple disciplines including biomedical engineering, bone biology, and diagnostic medicine, with applications in both clinical practice and archaeological science. Dr. Kerns' publication record demonstrates a consistent focus on applying spectroscopic techniques to medical diagnostics, with recent work spanning from bone health analysis to wildlife conservation applications. Her research shows increasing interdisciplinary collaboration, connecting medical diagnostics with conservation science, particularly in ivory identification techniques. Fellow of the Royal Society of Chemistry Inspirational Woman for EDI award As a PhD supervisor, Dr. Kerns mentors students in Raman spectroscopy applications to bone biology, non-invasive detection of mineralization in bone, and osteoporosis prediction and prevention. She currently supervises Dr. Milli Raizada. Her research is supported by multiple grants including projects on ivory detection at customs, bone health monitoring in sailors aboard the Mary Rose, and prevention of osteoporosis through early monitoring of bone health. Dr. Kerns is actively involved with several research groups including the Cancer Biology and Genome Stability group, Centre for Ageing Research, Experimental Medicine group, Lancaster Intelligent, Robotic and Autonomous Systems Centre, and LIRA - Biomedical.

• Thin-walled Structures
• Marine Technology
• Structural Mechanics
• +۵ مورد دیگر

Jani Romanoff is a Professor in the Department of Energy and Mechanical Engineering at Aalto University's School of Engineering, specializing in thin-walled structures across marine, architectural, and microelectronic applications. His research uniquely integrates multi-scale mechanics to develop sustainable material solutions for visible structures like ships and bridges, as well as microscopic applications in microelectronics. Professor Romanoff's work centers on the mechanics of thin-walled structures, with a distinctive focus on length-scale interactions often overlooked in conventional engineering. This approach enables innovative sustainable material utilization across diverse applications, from passenger ship design to microelectronic components. His expertise spans marine technology, structural mechanics, fatigue analysis, and vibration dynamics, with significant contributions to lightweight structural design and sustainable engineering practices. Analysis of his 15 most recent publications (2023-2025) reveals a dominant focus on cruise ship engineering, particularly laminated glass units, passenger satisfaction, and structural integrity of thin-walled components. Key trends include computational modeling of welding distortions, application of machine learning for deformation prediction, and sustainability-driven design optimization. His work consistently bridges theoretical mechanics with practical marine applications, emphasizing environmental impact reduction through material efficiency. Professor Romanoff's accolades include: Aalto Education Impact Award (2018) for establishing the Marine Technology study program SNAME Honorable Mention for Vice Admiral EL Cochrane Award (2018) for research on steel sandwich panel joints Aalto School of Engineering Teaching Award (2012) for Shipbuilder's Portfolio and Toolbox Special Recognition Award for Research Excellence (2014) As leader of the Marine and Arctic Technology research group, he directs collaborative international projects focused on structural innovation in marine engineering. His work integrates teaching with cutting-edge research, evidenced by multiple education awards and active supervision of student projects in marine technology. The Marine and Arctic Technology research group under Professor Romanoff pioneers advanced structural analysis techniques for extreme environments, with current projects addressing green transition in cruise shipping, multi-scale modeling of composite structures, and human-centered design of passenger vessels. The group maintains strong industry partnerships with major shipbuilders and classification societies.