جست‌وجوی استاد و پژوهشگر

• Hydrology
• Environmental Impact Assessment
• Cold Climate Hydrology
• +۴ مورد دیگر

Knut Tore Alfredsen is a Professor in the Department of Civil and Environmental Engineering at NTNU. His research focuses on cold climate hydrology, environmental impacts of hydropower, river ice dynamics, and water resource management. He leads projects like Trygg Elv (flood detection tools) and Hydro Connect (climate change mitigation in hydropower). He supervises numerous PhD and master’s students and teaches courses in hydrology, hydropower engineering, and environmental design. His work combines field measurements, data analysis, and advanced modelling, often using LiDAR and remote sensing technologies. Key projects include Sagelva research catchment studies and evaluations of environmental impacts from hydropeaking and reservoir operations. He is an active contributor to international conferences and collaborates with organizations like NVE and the IAHR. Education: Not explicitly stated in the provided text. Affiliations: HydroCen, Center for Renewable Energy (FME), NTNU’s Civil and Environmental Engineering Department. Grants: Involved in projects like HydroFlex (turbine development) and Klima 2050 (runoff estimation). Awards: None explicitly mentioned. Labs/Teams: Leads research groups in ecohydraulics, river modelling, and cold climate hydrology. Research Highlights: Focuses on ice-jam flood hazards, hydropeaking effects on fish, and sustainable hydropower practices. Recent work includes LiDAR-based river bathymetry and historical river development analysis using AI.

• Autonomous Driving
• Sensor Fusion
• Intelligent Transportation Systems
• +۵ مورد دیگر

Prof. Dr.-Ing. Christoph Stiller is a full professor at the Karlsruher Institut für Technologie (KIT) and serves as the director of the Institute of Measurement and Control Technology (Institut für Mess- und Regelungstechnik, MRT). His work focuses on autonomous driving, sensor fusion, probabilistic estimation, HD mapping, motion planning, and intelligent transportation systems. Education: Details on his academic degrees are not provided in the text, but he holds the title of Dr.-Ing. indicating a doctoral degree in engineering. Research Interests: Prof. Stiller's research spans a wide array of topics critical to the development of autonomous vehicles. His work includes: Sensor Fusion: Integrating data from LiDAR, cameras, and radar to create robust perception systems. HD Mapping & Localization: Developing high-definition maps and precise localization techniques for urban and highway environments. Motion Planning & Decision Making: Creating algorithms for safe and efficient trajectory planning under uncertainty. Machine Learning & AI: Applying deep learning and reinforcement learning to perception, prediction, and control tasks. Publication Trends: His recent publications (2023–2025) emphasize robust traffic light detection, image stitching for panoramic views, motion prediction using redundancy reduction, and safety-enhanced model predictive control. The work increasingly integrates learning-based methods with classical control and estimation theory. Scientific Awards: No specific awards are listed in the provided text. Teaching & Supervision: Prof. Stiller teaches foundational and advanced courses in measurement and control systems, probabilistic estimation, and autonomous driving. He holds regular office hours during both summer and winter semesters and is actively involved in advising students and researchers. Labs & Teams: He leads the Institute of Measurement and Control Technology (MRT) at KIT, which is engaged in cutting-edge research in autonomous systems. The institute collaborates with industry and academia on large-scale projects such as UNICARagil and various European initiatives.

Jacob Mackenzieمشاهده پروفایل

دانشیار

• Photonics
• Solid-State Lasers
• Waveguide Amplifiers
• +۷ مورد دیگر

Jacob Mackenzie is an Associate Professor at the University of Southampton's Faculty of Engineering and Physical Sciences , affiliated with the Optoelectronics Research Centre (ORC) and Zepler Institute. His work spans advanced laser physics and photonics, focusing on efficient solid-state systems via planar waveguide geometries and cryogenic cooling for power scaling. Research interests: Waveguide amplifiers, cryogenically cooled lasers, ultra-fast compact lasers Key applications: Materials processing, space-borne LIDAR, silicon photonics Research Themes include innovative gain media engineering, thermal management, and spectroscopic optimization. His group explores non-standard laser transitions to expand accessible wavelengths and power regimes in continuous-wave (CW) and pulsed configurations. Publications highlight advancements in resonant waveguide gratings, thermal performance metrics, high-repetition rate systems, and optical coating durability. These align with his leadership in high-power laser design and novel manufacturing techniques. Scientific Awards Royal Academy of Engineering Postdoctoral Fellow (2004) Senior Member of the Optical Society (OSA) PhD Supervision includes Isaac Brock, Georgia Mourkioti, and Sahar Alidousti. He also mentors postgraduate students through technical workshops and co-teaches Photonics II (ELEC3217) for undergraduates. External Roles encompass invited speaking (2020), journal reviewing (2021-2022), and chairing conferences like the 10TH EPS-QEOD EUROPHOTON CONFERENCE (2022).

Jiri Srbaمشاهده پروفایل

استاد

• Formal Methods
• Model Checking
• Petri Nets
• +۴ مورد دیگر

Jiri Srba is a Professor at Aalborg University's Department of Computer Science, part of the Technical Faculty of IT and Design. He leads research in the Distributed, Embedded and Intelligent Systems group and contributes to projects like "ControLing wAter In an uRban Environment" and "Collective Adaptive System SynThesIs using Non-zero-sum Games". His office is located at Selma Lagerløfs Vej 300, 9220 Aalborg Øst, Denmark. Contact him at +4599409851 or srba@cs.aau.dk. His core research focuses on formal methods and applied computer science: Model checking and verification of concurrent systems Petri nets and their applications Network protocol verification and synthesis Distributed system correctness Automated reasoning for industrial systems His publication record shows strong emphasis on network verification, model checking optimization, and applying formal methods to environmental systems. Recent work integrates computer science with sustainable engineering, particularly in water management systems and energy control.

Joyoung Leeمشاهده پروفایل

دانشیار

• Connected Vehicle (CV) Systems
• Traffic Management
• Autonomous Vehicle Control
• +۵ مورد دیگر

Dr. Joyoung Lee is an Associate Professor in the Department of Civil and Environmental Engineering at New Jersey Institute of Technology (NJIT). He previously served as Laboratory Manager at the Federal Highway Administration's Saxton Transportation Operations Laboratory. His research focuses on Connected Vehicle (CV) systems, including applications in traffic management, signal control optimization, and autonomous vehicle infrastructure integration. Dr. Lee holds a Ph.D. (2010) and M.S. (2007) in Transportation Engineering from the University of Virginia, and a B.S. (2000) in Transportation Engineering from Hanyang University. His work emphasizes CV-based solutions for real-time traffic systems, cooperative vehicle-infrastructure systems (CVIS), and autonomous vehicle integration. Notable achievements include the 2019 IEEE CAVS Best Paper Award and multiple best paper recognitions from PTV User Group Meetings. His research also addresses traffic safety through innovations like the Virtual Guide Dog system for visually impaired pedestrians and advanced traffic monitoring frameworks using LiDAR and computer vision. Education: Ph.D., Transportation Engineering, University of Virginia (2010) M.S., Transportation Engineering, University of Virginia (2007) B.S., Transportation Engineering, Hanyang University (2000) Dr. Lee's research interests span smart city infrastructure, edge computing for traffic systems, and sustainable transportation solutions. He has pioneered algorithms for cooperative intersection management, automated platooning systems, and federated learning-based traffic optimization. His work bridges theoretical models with real-world implementation through partnerships with FHWA and industry stakeholders. Key contributions include development of the Cumulative Travel-Time Responsive (CTR) traffic signal control system, smart arrival notification systems for paratransit services, and advanced microsimulation calibration techniques. His lab focuses on translating CV data into actionable strategies for safer, more efficient transportation networks. Awards: IEEE CAVS Best Paper Award (2019) ASCE Grand Challenge Innovation Contest Honorable Mention (2017) PTV VISSIM Best Paper Awards (2012, 2008) Excellence in Research Award (University of Virginia, 2011) Ongoing projects include semi-decentralized graph neural networks for traffic forecasting and low-cost LiDAR-based traffic monitoring systems. His work addresses critical challenges in autonomous vehicle integration, incident management, and infrastructure resilience through interdisciplinary collaborations.

Jon McCormackمشاهده پروفایل

استاد

• Computational Creativity
• Human-machine interfaces
• Artificial Intelligence/Cybernetics
• +۹ مورد دیگر

Jon McCormack is a Professor jointly appointed in Monash University's Faculty of Art, Design & Architecture (MADA) and Faculty of Information Technology. He founded and directs SensiLab, a research facility focusing on computational creativity, human-machine interfaces, and generative systems. His work spans electronic media art, evolutionary music, and artificial life. McCormack holds a PhD in Computer Science from Monash University, along with degrees in Computer Science, Applied Mathematics, and Film/Television. Research interests include computational creativity, tangible interfaces, and cybernetic systems. Notable projects include 'Explainable Artificial Creativity' (ARC-funded) and 'Building 4.0 CRC,' addressing architectural innovation through AI. He has been recognized with awards for collaborative projects like the Blundstone Intelligent Footwear for Healthcare. McCormack's recent articles explore AI-driven art, generative systems, and interdisciplinary design. His work bridges artistic practice with technical innovation, emphasizing ethical and creative dimensions of human-AI collaboration. SensiLab serves as a hub for practice-based research in digital media and interactive systems. Education: PhD in Computer Science, Monash University (2004) Bachelor of Science (Honours), Computer Science/Applied Mathematics, Monash University (1987) Graduate Diploma in Film/TV, Swinburne University (1986) Bachelor of Science, Computer Science/Applied Mathematics, Monash University (1985) Key Projects: Lead investigator on 'Explainable Artificial Creativity' (2022–2026) Co-investigator in 'Building 4.0 CRC' (2020–2027), exploring AI-driven architectural design Awards: 2022 Designers Australia Award for Blundstone Footwear 2020 'On the Machine Condition' Prize McCormack's lab, SensiLab, fosters collaborations across disciplines, producing exhibitions, software, and theoretical frameworks for computational creativity. He actively supervises PhD students in practice-based research, emphasizing the intersection of art and technology.

• Computer Vision
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Esa Rahtu is a Professor in the Department of Computer Science at Aalto University, Finland. His research focuses on computer vision, machine learning, and deep learning applications. He leads projects in image coding, neural networks, 3D reconstruction, object pose estimation, and anomaly detection. Rahtu has contributed to over 98 research outputs since 2017, with recent work emphasizing Gaussian splatting for SLAM, neural radiance fields, and hybrid video codecs for human-machine compatibility. His expertise spans visual-inertial odometry (e.g., ADVIO dataset), LiDAR-based place recognition, and manufacturing quality control systems. Key areas include: 3D scene reconstruction using Gaussian splatting techniques Deep learning models for anomaly detection in industrial processes Hybrid video codecs optimizing human perception and machine processing Multi-sensor fusion for robotic navigation and indoor mapping Notable datasets include ADVIO for visual-inertial odometry and FIORD for 3D reconstruction benchmarking. His research aligns with UN SDG 9 (Industry, Innovation & Infrastructure) and SDG 4 (Quality Education) through advancements in smart manufacturing and educational technology. Rahtu has received continuous research funding, including a grant period from April to June 2018. His work emphasizes practical applications, collaborating on real-world challenges like paper manufacturing quality control and smartphone-based 3D reconstruction.

Johnson Xuesong Shenمشاهده پروفایل

دانشیار

• Digital Twins
• Building Information Modeling (BIM)
• Construction Automation
• +۵ مورد دیگر

Dr. Johnson Xuesong Shen is an Associate Professor at the School of Civil and Environmental Engineering , University of New South Wales . His work integrates Digital Twins , Building Information Modeling (BIM) , and Construction Automation with a focus on robotics, AI, and LiDAR/UAS technologies. Research Interests: Digital Twins, BIM, Construction Robotics, Emissions Modeling, LiDAR/UAS, Structural Health Monitoring Education: Ph.D. in Construction Engineering and Management, The Hong Kong Polytechnic University His publications span 2025–2005, emphasizing construction automation , environmental impact reduction , and innovative tunneling solutions . Recent work includes IoT-Bayes fusion for real-time safety monitoring and life cycle analysis of construction waste. Scientific Awards: Vice Chancellor's Award for Teaching Excellence, UNSW, 2014 Best PhD Student Paper Award, CONVR, UK, 2013 Postdoctoral Fellowship, University of Alberta, 2011-2013 Best Paper Award, ASCE Construction Research Congress, 2010 Dr. Shen mentors 9 PhD candidates in areas like 3D object detection , fuel consumption modeling , and UAV-based LiDAR . His grants include $5.98M from the Australian Research Council (2022–2027) for resilient infrastructure systems and projects on modular construction and intelligent tunneling .

Danial Chitnisمشاهده پروفایل

مدرس

• Microelectronics
• Biomedical Engineering
• Quantum Technology
• +۳ مورد دیگر

Dr. Danial Chitnis is a Chancellor's Fellow and Lecturer in Electronics at the School of Engineering, University of Edinburgh. He holds a DPhil in Engineering Science from the University of Oxford (2013) and has expertise in microelectronics, biomedical engineering, and quantum imaging. His research focuses on SPAD arrays, time-of-flight sensors, and wearable optical systems for biomedical applications. Education: BSc in Electronics Engineering, Chamran University of Ahvaz (2002–2007) MSc in Advanced Microelectronics Systems Engineering, University of Bristol (2007–2008) DPhil in Engineering Science, University of Oxford (2009–2013) Research Interests: Single-Photon Avalanche Diode (SPAD) arrays for optical communications and biomedical imaging Quantum-enhanced imaging via QuantIC Hub Wearable sensors for near-infrared spectroscopy (NIRS) AI-driven automation in test and measurement systems Articles Trends: Recent work emphasizes AI integration in electronics design, photon-counting receivers for 6G networks, and portable biomedical devices. Notable contributions include SYCL-based acceleration of circuit simulations and FPGA-driven time-to-digital converters. Grants & Collaborations: Principal Investigator of multiple grants, including EPSRC-funded projects on AI-enhanced human-machine interfaces and quantum technology applications. Collaborates with UCL, QuantIC, and industry partners like Keysight Technologies. Labs/Teams: Co-investigator at QuantIC, the UK Quantum Technology Hub in Quantum Enhanced Imaging. Leads interdisciplinary research on detector arrays and systems for quantum physics and consumer cameras.

Yelda Turkanمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Lidar Applications
• +۷ مورد دیگر

Dr. Yelda Turkan is an Associate Professor in the School of Civil and Construction Engineering at Oregon State University, where she leads research in automation, computer vision, and machine learning for sustainable infrastructure. She holds a PhD from the University of Waterloo and dual BS degrees in Civil Engineering and Geomatics Engineering from Istanbul Technical University. Her work focuses on leveraging lidar, digital twins, and BIM to improve construction operations and decision-making in the built environment. She has secured over $4M in grants from NSF, FHWA, and other agencies, and currently leads the NSF Convergence Accelerator-funded 'Deep Reality' project for AI-driven infrastructure management. Education: Ph.D., Civil Engineering, University of Waterloo, 2012 M.S., Engineering Informatics & Remote Sensing, Istanbul Technical University, 2006 B.S., Civil Engineering (double major in Geomatics Engineering), Istanbul Technical University, 2005/2003 Professional Roles: Vice President, International Association for Automation and Robotics in Construction (IAARC) Chair, ASCE Computing Division Education Committee Associate Editor, ASCE OPEN Journal Her research emphasizes automation in construction quality control, infrastructure inspection via drones and lidar, and immersive education tools using VR/AR. Recent projects include automated curb ramp compliance analysis, wildfire impact modeling, and digital twin development for timber structures. She has published over 80 peer-reviewed articles and actively promotes computing integration in civil engineering education and professional practice.

Pascale Bironمشاهده پروفایل

استاد

• Hydro-geomorphology
• River dynamics
• Stream restoration
• +۵ مورد دیگر

Dr. Pascale Biron is a Professor in the Department of Geography, Planning and Environment at Concordia University, Montreal. Her research focuses on river dynamics, stream restoration, flood modeling, and climate change impacts. She has been at Concordia since 1998 and holds professional affiliations with key organizations like the Canadian Geomorphology Research Group and the American Geophysical Union. Education: PhD from Université de Montréal and Leeds University (fluvial geomorphology) Research Interests Her work integrates fluvial geomorphology, computational fluid dynamics, and societal aspects of river management. Key themes include: River restoration for fish habitat Floodplain modeling using LiDAR Climate adaptation strategies Socio-hydrological dimensions of restoration Hydrodynamic processes at river confluences Recent Research Trends Recent publications emphasize global salmonid habitat analysis, machine learning for fluvial hazard detection, and the socio-environmental impacts of urban flooding. Her work bridges technical hydrology with policy-relevant solutions for sustainable water management. Grants & Advising Supervises over 15 graduate students (PhD/MSc) in topics ranging from flood modeling to bioengineering. Active in collaborative projects like the 'Freedom Space for Rivers' initiative and large-scale floodplain mapping. Labs & Teams Member of GRIL (Limnology Research Group) and RIISQ (Quebec Flood Network), contributing to interdisciplinary water security research.

Gaël Kermarrecمشاهده پروفایل

پژوهشگر

• Boundary Layer Meteorology
• Atmospheric Turbulence
• GNSS Applications
• +۳ مورد دیگر

Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections

Paola Passalacquaمشاهده پروفایل

استاد

• Water Resources Engineering
• Geomorphology
• Hydrology
• +۴ مورد دیگر

Paola Passalacqua is a Professor of Environmental and Water Resources Engineering and Earth and Planetary Sciences at the University of Texas at Austin, holding the L.B. (Preach) Meaders Professorship in Engineering. She leads research at the intersection of water resources engineering, geomorphology, and hydrology, focusing on river networks, coastal restoration, and remote sensing applications. Her work addresses delta dynamics, floodplain connectivity, and community resilience to compound hazards. Dr. Passalacqua earned a PhD in Civil Engineering (2009) and MS in Water Resources from the University of Minnesota, and dual MS/BS in Environmental Engineering from the University of Genoa (2002). Her technical expertise includes hydrological connectivity, network theory, and morphodynamic modeling using LiDAR and satellite data. Research interests emphasize river delta structure/dynamics, floodplain sedimentation, and translating science into community adaptation strategies. She co-developed tools like GeoFlood for large-scale flood mapping and the pyDeltaRCM numerical delta model. Her interdisciplinary approach integrates socio-technical vulnerability analysis with environmental systems. Awards include the endowed Meaders Professorship. Current projects involve coastal Alaska infrastructure resilience, SWOT satellite data applications, and delta sustainability in the Anthropocene. She leads the Passalacqua Research Group, engaging in citizen science through initiatives like UTBiome.

Cynthia Ebingerمشاهده پروفایل

استاد

• Geophysics
• Rifts
• Seismic Monitoring
• +۳ مورد دیگر

Cynthia Ebinger is a Professor in the Department of Earth and Environmental Sciences at Tulane University, affiliated with the School of Science & Engineering. She holds the Marshall-Heape Chair and previously served at the University of Rochester and as an Adjunct Professor at Royal Holloway, University of London. Her research focuses on geophysics, rift systems, seismic monitoring, volcanoes, and plate tectonics in West Africa and East Africa, particularly the Turkana Depression and East African Rift. She has conducted fieldwork in Ecuador, Peru, Kenya, Uganda, Ethiopia, and Australia. Education : Ph.D., MIT/WHOI, Joint Program in Oceanography, Marine Geology & Geophysics (1988) M.A., MIT, Geophysics (1986) B.S., Duke University, Geology (1982) Research Interests : Dr. Ebinger investigates continental rifting mechanisms, magmatic processes, seismic anisotropy, and volcanic systems. Her work integrates geophysical methods (e.g., InSAR, receiver functions) to study deformation in regions like the East African Rift and Gulf of Mexico passive margin. She emphasizes understanding crustal dynamics, lithosphere modification, and the interplay between tectonics and surface processes. Publications : Her recent work addresses rift linkage mechanics, crustal anisotropy variations, and volcanic deformation (e.g., Nyiragongo eruption). Key themes include seismic imaging of rift zones, subsidence patterns in coastal Louisiana, and mantle lithosphere interactions. Awards : American Geophysical Union Distinguished Lecturer (2023-2024) NASEM Jefferson Science Fellow (2022-2023) Woollard Award (2021) Tulane Honors Professor of the Year (2021) Grants & Collaborations : Leads projects funded by NSF and international collaborations, focusing on Turkana Depression geodynamics, Gulf of Mexico subsidence, and volcanic monitoring in East Africa. Active in education initiatives to strengthen quantitative geophysics training. Labs/Teams : Core member of the Tulane Earth Sciences group and collaborates with global networks (e.g., Project TRAILS in East Africa). Engages in field-based research and satellite geodesy applications.

Thierry Badardمشاهده پروفایل

دانشیار

• Geospatial Big Data
• GeoAI
• GeoNLP
• +۹ مورد دیگر

Thierry Badard is an Associate Professor at the Department of Geomatics Sciences , Université Laval, where he also serves as Director of the Center for Research in Geospatial Data and Intelligence (CRDIG) . With over 28 years of experience in geospatial science, he leads research initiatives at the intersection of GeoAI , LiDAR processing , and smart city technologies . Director, CRDIG (2016-2022) Steering Committee Member, Big Data Research Centre (CRDM) Researcher, Institute for Intelligence and Data (IID) Research Expertise spans geospatial big data, GeoNLP, and IoT applications for digital twins. His work addresses flood risk modeling , 3D urban analytics , and environmental monitoring through AI-driven solutions. Recent publications focus on contrastive learning for LiDAR segmentation and geospatial ontologies for early warning systems. Grant Leadership includes collaborative projects on smart insurance analytics (2018-2025), Arctic bioaerosol research (2019-2025), and Quebec-Morocco digital twin partnerships (2022-2023). He has advised 15+ graduate students in geomatics and related fields.