جست‌وجوی استاد و پژوهشگر

Ásta Hannesdóttirمشاهده پروفایل

پژوهشگر

• Wind Energy
• Wind Turbine Engineering
• Remote Sensing (Lidar)
• +۴ مورد دیگر

Ásta Hannesdóttir is a Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU), specializing in wind energy systems with expertise in wind turbine aerodynamics, lidar remote sensing, and atmospheric turbulence modeling. She actively contributes to major research initiatives including the AIRE Horizon Europe project and TRASCAL, advancing wind farm design under challenging weather conditions. Her research focuses on leading-edge erosion impacts on turbine performance, lidar-based wind field reconstruction, and non-Gaussian turbulence modeling. She develops computational tools for wind resource assessment and integrates numerical simulations with field measurements to address aerodynamic degradation in offshore wind farms, significantly contributing to sustainable energy solutions aligned with UN SDGs. Recent publications reveal strong trends in lidar technology validation, erosion-aerodynamics interactions, and turbulence modeling innovations. Her work bridges atmospheric science and engineering to enhance wind turbine durability and energy yield under extreme weather, with growing emphasis on digital twin applications for wind farm optimization. Scientific recognition includes: Otto Mønsted travel grant (2019) for international conference participation in Massachusetts, USA Hannesdóttir supervises multiple graduate projects including PhD research on hub lidar flow-field estimation and master's theses on floating wind turbine control systems. She secures significant funding through collaborative grants: Active leadership in Horizon Europe's AIRE project (2023-2026) with €4.2M budget Principal investigator roles in TRASCAL (2023) and CCA LEE (2022) lidar/erosion projects Contributions to REQUIM rain erosion initiative (2022-2023) She operates within DTU's Wind Energy Systems division as part of cross-functional teams developing next-generation wind measurement technologies. Her work involves close collaboration with WindEurope, international research consortia, and industry partners to translate atmospheric physics into practical turbine design improvements.

Jack Bartonمشاهده پروفایل

استاد مدعو

• Urban Modeling
• Geospatial Analysis
• 3D Mapping
• +۳ مورد دیگر

Dr. Jack Barton is a Casual Academic at the School of Built Environment, University of New South Wales (UNSW), and an Adjunct Professor at Far Eastern University, Philippines. He specializes in geospatial research, urban modeling, and three-dimensional mapping applications. Current Role: Manages the Geospatial Research Innovations and Development (GRID) cluster at UNSW Past Roles: Associate (Digital Delivery) at SGS Economics and Planning (2018–19), Urban Data and eResearch Facilitator at AURIN (2013–17) His research focuses on integrating geospatial technologies with urban sustainability, digital twins, and spatial decision support systems. Recent work includes real-time bushfire messaging and voxel-based urban analytics . Dr. Barton combines consultancy (20+ years), academic research, and education. He has contributed to over 15 publications since 2003 in journals like ISPRS Annals and Housing Studies , with an emphasis on smart cities and urban resilience . He leads the GRID research cluster at UNSW, fostering interdisciplinary projects that bridge architecture, geospatial science, and urban policy.

Pia Ruttner-Jansenمشاهده پروفایل

پژوهشگر

• Remote Sensing
• Geomatics
• Snow and Avalanche Research
• +۳ مورد دیگر

Pia Ruttner-Jansen is an External Doctoral Student at the WSL Institute for Snow and Avalanche Research SLF and affiliated with the GSEG group at ETH Zurich since March 2021. Her work focuses on remote sensing and geomatics applications in snow and avalanche research . Education : BSc in Geodesy and Geoinformation (Technical University of Vienna, 2018) MSc in Geomatic Engineering (ETH Zurich, 2021) Her research explores high-resolution snow depth monitoring using drones, terrestrial laser scanning (TLS) , and GNSS technologies to improve avalanche risk assessment and infrastructure safety in alpine regions. Key methodologies include: Low-cost lidar and optical sensors for snow depth mapping Probability-based avalanche run-out modeling Machine learning integration for GNSS residual analysis Recent publications highlight her contributions to automated railway infrastructure monitoring , avalanche core-powder cloud simulation , and keypoint-based TLS deformation detection . Her work emphasizes practical applications for mountain hazard mitigation . Current affiliations include: PhD Student at WSL Institute for Snow and Avalanche Research SLF PhD Student at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering

Bernhard Höfleمشاهده پروفایل

استاد

• Geoinformatics
• 3D Point Cloud Analysis
• Environmental Monitoring
• +۵ مورد دیگر

Prof. Dr. Bernhard Höfle is a Professor of Geoinformatics and 3D Geospatial Data Processing at the University of Heidelberg, where he leads the 3DGeo Research Group. His work focuses on computational methods for analyzing 3D/4D point clouds, with applications in environmental monitoring, natural hazard assessment, and vegetation studies. Research Interests: 3D/4D point cloud analysis for environmental observation Development of computational algorithms for geospatial data Integration of machine learning in remote sensing applications Virtual laser scanning simulations (VLS-4D) Real-time monitoring systems for critical infrastructure Digital Twin integration across scales Article Trends: His recent publications emphasize real-time 3D environmental monitoring, virtual simulation of dynamic scenes, multi-temporal analysis of natural processes, and machine learning applications for point cloud classification. They span from 2025 back to 2023 and cover diverse applications including rock glaciers, forest monitoring, building damage assessment, and bee activity tracking. Key Techniques: His work prominently features terrestrial laser scanning, UAV-based LiDAR, and open-source software development. He has contributed datasets like FOR-species20K and developed simulation frameworks such as HELIOS++.

Emily Arnoldمشاهده پروفایل

دانشیار

• Multifunctional Structures
• Remote Sensing
• Unmanned Aerial Systems
• +۳ مورد دیگر

Emily Arnold is an Associate Professor in the Department of Aerospace Engineering at the University of Kansas, where she also serves as Graduate Program Director. Her research centers on multifunctional aerospace structures, remote sensing technologies, and unmanned aerial systems (UAS) for glaciological applications. Key trends in her recent publications highlight advancements in reconfigurable radar systems for UAS-based ice and snow sounding, wing-mounted antenna design under flight stress, and 3D-printed microwave components. She merges aerospace structural analysis with electromagnetic simulation to enhance UAV sensor performance in polar environments. NSF CAREER Award (2019) for UAS radar systems NSF MRI Grant (2022) for radar instrumentation Her work at CReSIS (Center for Remote Sensing of Ice Sheets) supports Operation IceBridge and COLDEX projects, focusing on oldest ice core exploration. She explores the intersection of structural dynamics, microwave engineering, and environmental monitoring via airborne platforms.

Christopher Depcikمشاهده پروفایل

دانشیار

• Combustion
• Sustainability
• Electric Vehicles
• +۴ مورد دیگر

Dr. Christopher Depcik is an Associate Professor in the Department of Mechanical Engineering and a Courtesy Professor in Aerospace Engineering at the University of Kansas. His research focuses on combustion sustainability , alternative fuels , and aftertreatment devices to improve engine efficiency and reduce emissions. Leading the "Feedstock to Tailpipe" initiative for a systems approach to fuels development Specializes in catalytic aftertreatment simulation for emissions compliance Mentors students in the EcoHawks capstone design class with projects on electrified vehicles and biomass combustion His recent publications highlight work on additive manufacturing for heat exchangers , predictive combustion modeling , and hydrogen-powered UAVs . Dr. Depcik’s interdisciplinary research bridges automotive engineering , energy systems , and materials science , with applications to biofuels , Li-ion batteries , and space propulsion . Pioneered "Burn the Atmosphere of Titan" study for extraterrestrial combustion Developed low-cost LiDAR systems for transportation safety His teaching emphasizes the integration of transportation and energy infrastructure , aligning with national energy security strategies. The EcoHawks lab serves as a hub for hands-on research in smart electrical grids and engine test cells .

Hyung Sub Simمشاهده پروفایل

استادیار

• Combustion
• Carbon-Free Energy Conversion
• Rocket Propulsion
• +۶ مورد دیگر

Hyung Sub Sim is an Assistant Professor in the Department of Aerospace Engineering at Sejong University, South Korea. Since 2022 he has led a research program centered on advanced combustion science, propulsion, and nano-engineered energy materials. His career spans academic, government, and industry roles, including positions at Pennsylvania State University, UCLA, Sandia National Laboratories, and the Agency for Defense Development. Education B.S., Chung-Ang University (2006) M.S., Chung-Ang University (2008) Ph.D., Pennsylvania State University (2016) Research Interests Professor Sim’s research integrates experiment, high-fidelity simulation, and machine learning to advance the fundamental understanding and practical deployment of: Combustion and carbon-free energy conversion Rocket propulsion and green propellants Optical diagnostics for reactive flows Nanoengineered energetic and catalytic materials Active combustion control strategies His work leverages state-of-the-art laser diagnostics (PLIF, schlieren) and reactive molecular-dynamics (ReaxFF) simulations to elucidate soot formation, ignition dynamics, and additive-enhanced fuel decomposition under high-pressure, high-temperature conditions. Publication Trends Across 31 publications (2013-2025) his output focuses on three dominant themes: (1) nanoparticle-laden hydrocarbon fuels for enhanced combustion and hypersonic propulsion, (2) soot and PAH formation mechanisms studied via high-speed optical diagnostics, and (3) computational materials design using ReaxFF for glass-ceramics, nanowires, and metal–graphene composites. A marked surge in 2020-2025 papers reflects intensified efforts in machine-learning-assisted combustion modeling and additive manufacturing of energetic nanomaterials. Scientific Awards Distinguished Paper Award, 38th International Symposium on Combustion (2022) Grants & Collaborations While specific grant numbers are not disclosed, his trajectory indicates sustained funding from Korean and U.S. defense agencies (ADD, Sandia), evidenced by joint publications with Sandia, UCLA, and Penn State teams. International collaborations span South Korea, USA, and Europe, focusing on next-generation propulsion systems and environmentally benign energetic materials. Laboratory & Teams At Sejong University he directs a combustion and propulsion laboratory equipped with high-pressure spray chambers, high-speed laser diagnostics, and GPU-accelerated ReaxFF simulation clusters. The group actively collaborates with the Engine Combustion Network (ECN) and maintains partnerships with Agency for Defense Development (ADD) for defense-oriented propulsion research.

Craig B Clementsمشاهده پروفایل

استاد

• Wildfire Meteorology
• Fire Weather
• Extreme Fire Behavior
• +۴ مورد دیگر

Craig B Clements is a Professor in the Department of Meteorology and Climate Science and Director of the Wildfire Interdisciplinary Research Center at San José State University . He specializes in wildfire meteorology, fire weather, and extreme fire behavior, with a focus on turbulence and meteorological instrumentation. Education: B.S. in Geography (University of Nevada, Reno), M.S. in Meteorology (University of Utah), Ph.D. in Geophysics (University of Houston) Key Research Areas: Fire-Atmosphere Interactions, Plume Dynamics, Boundary-Layer Meteorology, and Climate-Wildfire Feedback Clements leads the Fire Weather Research Laboratory , which develops mobile Doppler lidar systems for real-time wildfire monitoring. His work includes the FireFlux II and RaDFIRE experiments, and he has collaborated on international projects like New Zealand's field-scale burns. He has been featured in Scientific American , NPR , and PBS NOVA . Scientific Awards: Erskine Fellowship (2024) NSF CAREER Award (2012) SJSU Early Career Investigator Award (2010) His courses include Wildfire in the Earth System , Meteorological Instrumentation , and Mountain Meteorology . He has mentored students on smoke dynamics, turbulence during wildfires, and fire-induced wind systems.

• Control Engineering
• Automation
• Marine Icing
• +۵ مورد دیگر

Sushmit Dhar serves as an Associate Professor in the Department of Automation and Process Technology at UiT The Arctic University of Norway, focusing on control engineering and automation solutions for Arctic maritime challenges. His work bridges theoretical control methods with practical applications in extreme environments. His research spans: Classical and modern control methods (PID, LQR, MPC) State estimation and Kalman filtering Physics-Informed Neural Networks and Reinforcement Learning for decision support IoT-based automation for maritime operations Marine icing phenomena and sea spray measurement Recent publications demonstrate cutting-edge work in marine icing prediction using LiDAR and capacitive sensors, Arctic road safety systems, and optimization of maritime operations. His research integrates advanced sensing technologies with data-driven modeling to address safety challenges in cold climates, particularly through sea spray measurement innovations and route planning algorithms for fishing vessels and search-and-rescue operations. Dr. Dhar actively contributes to collaborative initiatives: Member of the Sustainable Technology and Safety (STS) research group Member of the IR, Spectroscopy, and Numerical Modelling Research Group Key participant in the SPRICE project (Multidisciplinary approach for spray icing modelling and decision support) His teaching portfolio includes foundational courses in Linear Systems (AUT-2604) and Control Engineering (AUT-2801) for Automation Engineering undergraduates, preparing students for technical challenges in Arctic engineering contexts.

• Speech Processing
• Artificial Neural Networks
• Binaural Sound Localization
• +۷ مورد دیگر

Dr. Jean-Luc Zarader is a Professor at Sorbonne University's Faculty of Engineering , serving as Deputy Director of the UFR of Engineering. Based at ISIR (Institute of Intelligent Systems and Robotics) in Paris, his research focuses on speech processing , neural networks , and binaural sound localization with applications in humanoid robotics and aircraft diagnostics. Key research areas: Speech coding, Nonlinear signal processing, Humanoid auditory systems, Fault diagnosis Active collaborations with teams: ACIDE, MLIA, IRIS Research Trends (2017-1996): 2017-2012: Whale bioacoustics, Aircraft diagnostics, Binaural localization 2007-2000: Speaker verification, Predictive coding, Neural network applications 1999-1996: Doppler lidar analysis, Speech compression His scientific contributions span multiple disciplines, including: Neural network optimization for signal processing Acoustic feature extraction Humanoid robot perception systems Aerospace fault detection Bioacoustic pattern recognition

• Robotics
• Human-Robot Interaction
• Virtual Reality
• +۷ مورد دیگر

Sheila Sutjipto is a Postdoctoral Research Fellow at the School of Mechanical and Mechatronic Engineering, University of Technology Sydney (UTS). Her research focuses on robotics, virtual reality, and human-robot interaction, with applications in mining safety, assistive technology, and industrial automation. She has published extensively in top robotics conferences and journals, demonstrating expertise in teleoperation systems, digital twin technology, and sensor fusion for robotic applications. Dr. Sutjipto's research spans multiple domains of robotics and human-computer interaction. Her work particularly emphasizes virtual reality interfaces for robot teleoperation , digital twin technology for industrial applications , and multi-modal perception systems . She has made significant contributions to mining safety through rock scaling robotics, assistive technology for visually impaired individuals, and haptic feedback systems for industrial robots. Her interdisciplinary approach integrates mechanical engineering, computer vision, and human factors to develop intuitive and safe robotic systems. Dr. Sutjipto's recent publications demonstrate a strong trajectory toward practical applications of robotics in challenging environments. Her work on digital twin-based teleoperated rock scaling robots addresses critical safety issues in mining operations. She has also pioneered multi-modal perception systems combining RGB, event cameras, and LiDAR for assistive robotics. A consistent theme across her publications is enhancing human-robot interaction through intuitive interfaces, whether via virtual reality, haptic feedback, or annotation-assisted control systems. Dr. Sutjipto has been involved in several funded research projects, including the HALO rock scaling robot project (stages 2 and 3), IntelliForce Tooling for hydraulic safety, and integration of live surround video for VR digital twins. She has collaborated with industry partners like Ausdrill and BTP Parts Pty Ltd. Her grant history shows a strong industry-academia collaboration focused on practical robotics applications. Dr. Sutjipto appears to be part of the robotics research group at UTS's School of Mechanical and Mechatronic Engineering. Her collaborations suggest involvement with teams focused on mining robotics, assistive technology, and industrial automation. She frequently collaborates with researchers like G. Paul, D.T. Le, and K. Nguyen, demonstrating strong interdisciplinary teamwork across engineering disciplines.

Felix Heideمشاهده پروفایل

استاد

• Computational Imaging
• Computer Vision
• Optics
• +۶ مورد دیگر

Felix Heide is a Professor of Computer Science at Princeton University , where he leads the Princeton Computational Imaging Lab . He also serves as Head of AI at Torc Robotics , focusing on full autonomy stacks for self-driving trucks. His research sits at the intersection of optics , machine learning , and computer vision , addressing imaging challenges in harsh environments like dense fog, ultra-low/high illumination, and scattering media. Ph.D. in Computer Science from the University of British Columbia Postdoctoral research at Stanford University His work on computational imaging spans physics-based vision, non-line-of-sight imaging , end-to-end camera design , and robust sensor fusion . He has pioneered techniques for inverse neural rendering , nanophotonic optics , and light-speed AI through optical computing. His recent papers in Nature Machine Intelligence , Science Advances , and top conferences ( SIGGRAPH , CVPR , ICCV ) focus on: Adverse weather imaging (fog, snow, rain) Multi-sensor fusion (LiDAR, radar, gated cameras) Light transport through scattering media Optical metasurfaces and diffractive optics End-to-end optimization of imaging pipelines Event-based vision and polarization cues He has received prestigious awards including the SIGGRAPH Significant New Researcher Award , Sloan Research Fellowship , and Packard Fellowship . His lab's open-source code and datasets enable real-world applications in autonomous driving, microscopy, and augmented reality.

Chongfeng Weiمشاهده پروفایل

دانشیار

• Decision-making and Planning of Intelligent Vehicles
• Collective Autonomy
• Robotic System Design
• +۵ مورد دیگر

Dr. Chongfeng Wei is an Associate Professor (University Senior Lecturer) at the James Watt School of Engineering, University of Glasgow. Prior to joining the University of Glasgow, he was a lecturer at Queen's University Belfast. His research focuses on intelligent vehicles, autonomous systems, and human-robot interaction, with applications in transportation and robotics. Dr. Wei's research spans several key areas in autonomous systems and vehicle dynamics: Decision-making and Planning of Intelligent Vehicles Collective Autonomy: Perception and Planning Robotic System Design and Dynamical Control Dynamics and Control of Mechanical Systems Human Behaviour Study and Prediction His recent publications demonstrate a strong focus on human-vehicle interaction, with particular emphasis on pedestrian-vehicle interactions, decision-making frameworks, and control strategies for autonomous systems. His work often combines AI technologies, bio-designs, and first principles of dynamics and control to create smarter or human-acceptable autonomous systems. Dr. Wei serves as an Associate Editor for several prestigious journals including IEEE Transactions on Intelligent Transportation Systems (TITS), IEEE Transactions on Vehicular Technology (TVT), IEEE Transactions on Intelligent Vehicles (TIV), IEEE Open Journal of Intelligent Transportation Systems (OJ-ITS), and Frontiers on AI and Robotics. He actively supervises PhD students and postdoctoral researchers, with current projects focusing on vision-based 3D flow prediction, pedestrian interaction modeling, and multimodal interaction for behavior prediction in autonomous driving.

Martin C Rabenhorstمشاهده پروفایل

استاد

• Hydromorphic Soils
• Wetland Soils
• Pedogenesis
• +۴ مورد دیگر

Martin C Rabenhorst , Professor at the University of Maryland's College of Agriculture and Natural Resources , specializes in Environmental Science & Technology . His career spans pedogenesis, hydropedology, and soil survey innovations. Ph.D. (1983, Texas A&M) M.S. (1978, University of Maryland) B.S. (1975, University of Maryland) Research focuses on hydromorphic soils , pedogenesis in tidal and subaqueous environments , and redoximorphic feature analysis . He pioneered IRIS (Indicator of Reduction in Soils) technology for environmental monitoring. Key publication trends since 2021 include: Advancements in subaqueous soil-landscape modeling Refinements to Soil Taxonomy for hydric soils Development of Fe/Mn oxide-coated films for redox assessment Studies on carbon dynamics in coastal wetlands His work intersects soil survey , wetland restoration , and pedological modeling , with recent emphasis on Chesapeake Bay subestuaries and blue carbon accounting .

Cristinel Ababeiمشاهده پروفایل

دانشیار

• Network-on-chip architectures
• Embedded systems
• Multicore processors
• +۷ مورد دیگر

Cristinel Ababei serves as an Associate Professor in the Department of Electrical and Computer Engineering at Marquette University's Opus College of Engineering. He directs the Marquette Embedded Systems (MESS) Laboratory and holds a Ph.D. in Electrical and Computer Engineering from the University of Minnesota (2004), with prior degrees from Technical University of Iasi in Romania. Ph.D., 2004, Electrical and Computer Engineering, University of Minnesota M.S., 1998, Signal Processing, Technical University of Iasi B.S., 1996, Microelectronics, Technical University of Iasi Dr. Ababei's research spans network-on-chip architectures, embedded systems design, FPGA implementations, and energy optimization systems. His work particularly focuses on uncertainty modeling in embedded systems, multicore processor optimization, and applications in underwater drones, LiDAR systems, and battery management. The MESS Lab under his direction conducts research in embedded systems (including tinyML and IoT applications), FPGAs as accelerators for computer vision, and network-on-chip architectures with emphasis on carbon emissions and uncertainty modeling. His recent publications demonstrate a clear trajectory toward integrating machine learning techniques with traditional hardware design, particularly in energy management systems, battery optimization, and environmental monitoring applications. This includes work on HVAC optimization using reinforcement learning, carbon-aware datacenter scheduling, and TinyML applications for battery health monitoring. William and Nancy Stemper Award for underwater drone prototype IEEE Senior Member (2015) Multiple NSF research grants as PI and Co-PI Teaching innovation grants for entrepreneurship-focused courses Dr. Ababei actively mentors students through the NSF REU Site program 'Hardware, Embedded Software, and Analytics for Environment Quality Monitoring' and has graduated multiple Ph.D. and M.S. students. He has secured significant research funding including NSF grants for uncertainty modeling in heterogeneous embedded systems, cross-layer optimization of energy and cost in multiple buildings, and REU site funding for environmental monitoring. He also founded the 'Men as Advocates and Allies Group' at Marquette as part of the Advance Program. His laboratory work includes the development of underwater drones for water quality monitoring, SmartBuilds energy simulation framework, and various embedded systems for environmental sensing applications. He has been instrumental in organizing WE-GIRLS Summer Camps to encourage girls in engineering from grades 6-8.