جست‌وجوی استاد و پژوهشگر

• Mining Automation
• Autonomous Systems
• Robotics
• +۵ مورد دیگر

Dr. Kevin Austin is a Research Fellow at the School of Mechanical and Mining Engineering, Faculty of Engineering, Architecture and Information Technology at the University of Queensland. His work is affiliated with the Future Autonomous Systems and Technologies research group, where he focuses on automation and robotics applications in mining engineering. Dr. Austin received his academic qualifications from the University of Queensland, including a Bachelor (Honours) of Engineering and a Doctor of Philosophy. Dr. Austin's research centers on mining automation and autonomous systems for heavy machinery operations. His work spans several key areas including dragline operation planning, excavation sequencing, terrain mapping for autonomous bulldozers, and hyperspectral imaging for ore grade discrimination. He has made significant contributions to the development of algorithms for mining equipment automation, particularly in the areas of Monte-Carlo Tree Search for dragline operation planning and Iterative Closest Point variants for terrain scan matching. His research bridges theoretical advances in robotics and artificial intelligence with practical applications in the mining industry, focusing on improving efficiency, safety, and productivity. Dr. Austin has been involved in numerous research projects funded by industry partners including Caterpillar Inc and the Australian Coal Association Research Program (ACARP). His current research focuses on coal stockpile management for remote bulldozers, semi-autonomous bulldozers for mine site rehabilitation, and articulated truck automated systems. His work demonstrates a strong industry connection with practical applications in mining operations. As an academic supervisor, Dr. Austin has served as an Associate Advisor for multiple PhD and Master's students at the University of Queensland. His supervision portfolio includes research on real-time terrain mapping for autonomous bulldozers, mission planning for autonomous excavation, dragline excavation sequencing, and scan matching for terrain mapping in open-pit mining. His collaborative approach is evident in his work with other faculty members, particularly Professor Ross McAree. Dr. Austin's laboratory and research team work closely with industry partners through the Future Autonomous Systems and Technologies group. They maintain strong connections with mining equipment manufacturers and coal mining operations, ensuring their research addresses real-world challenges in the mining sector. Their facilities likely include simulation environments for mining equipment operation, testbeds for autonomous systems, and data analysis platforms for mining process optimization.

DAVID LOPEZ VILARIÑOمشاهده پروفایل

استاد

• Computer Architecture
• Computer Vision
• FPGA Acceleration
• +۳ مورد دیگر

David Lopez Vilariño is a **Professor** at the **University of Santiago de Compostela**, affiliated with the **Department of Electronics and Computing** within the **Faculty of Physics**. He earned his PhD in 2001 with a thesis titled *"Active contours at the pixel level: design and implementation on cellular network architectures,"* advised by Dr. Diego Cabello Ferrer. His research focuses on **Computer Architecture**, **FPGA Acceleration**, **LiDAR Data Analysis**, and **Embedded Systems**, with notable contributions to LiDAR-based applications in urban planning, infrastructure monitoring, and medical imaging. He is part of the **ARQCOMP (Computer Architecture)** and **Artificial Vision** research groups. His work spans topics such as high-performance computing, parallel processing, and hardware optimization for vision-capable systems. Key projects include developing FPGA-based solutions for real-time video surveillance, retinal vessel analysis, and autonomous navigation systems. Publications emphasize **LiDAR data processing**, including algorithms for road detection, power line characterization, and 3D point cloud analysis. He also pioneered tools like the *Open Lidar Visualizer and Analyser* for 3D stereoscopic visualization. His expertise bridges hardware design and software development, particularly in leveraging FPGAs for embedded vision systems. No scientific awards or grants are explicitly listed, but his prolific publication record highlights sustained innovation in computer vision and geospatial technologies. His research team collaborates on projects involving manycore systems, GPU acceleration, and reconfigurable computing architectures.

Kartikeya Singhمشاهده پروفایل

پژوهشگر

• Autonomous Systems
• Simultaneous Localization and Mapping (SLAM)
• Risk-Aware Navigation
• +۷ مورد دیگر

Kartikeya Singh is a Ph.D. candidate and Researcher in the Department of Computer Science at the University at Buffalo, affiliated with the College of Engineering and Applied Sciences. His work focuses on autonomous systems, particularly SLAM and risk-aware navigation for robots operating in complex terrains. Current research emphasizes enabling legged robots to traverse challenging environments via advanced visual perception and dynamic motion planning. His approach integrates theoretical rigor with practical deployment, collaborating with industry partners to test solutions in real-world scenarios. Recent publications (2021–2025) span legged robot navigation, payload-aware path planning, and visual feature learning using motion. Key themes include environmental monitoring, off-road mobility, and sensor fusion technologies. 2025: Autonomous Culvert Inspection 2024: PANOS (Offroad Navigation), L-DYNO (Visual Perception) 2021: OFFSEG (Semantic Segmentation), Offroadtranseg (Transformer Models) 2020: Shoplifting Detection via Contour Analysis Scientific recognition includes: Top 10 emerging researcher at ICRA 2025 Best paper nomination at ICRA 2025 He has served as a Research Assistant (2023–Present) and Teaching Assistant (2022–2023), mentoring in courses like Robotic Algorithms and Data Intensive Computing . His work is conducted in the DRONES Lab under Professor Karthik Dantu.

Dimitrios Diochnosمشاهده پروفایل

استادیار

• Supervised Learning
• Semi-Supervised Learning
• Adversarial Learning
• +۴ مورد دیگر

Dr. Dimitrios Diochnos is an Assistant Professor in the School of Computer Science at the University of Oklahoma (OU) . His research focuses on theoretical and practical aspects of machine learning, including adversarial learning, semi-supervised learning, and imbalanced data classification. Prior to OU, he was a Hobby Postdoctoral Research Fellow at the University of Virginia and a Research Associate at the University of Edinburgh. He holds a PhD in Mathematics from the University of Illinois at Chicago, an MS in Mathematics from the University of Athens, and a BS in Informatics and Telecommunications from the University of Athens. Research Interests: Dr. Diochnos works on foundational aspects of machine learning, particularly under adversarial conditions. His current projects include developing semi-supervised learning techniques, analyzing online/streaming learning algorithms, and exploring theoretical guarantees for imbalanced classification. He is also involved in the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), focusing on trustworthy AI applications in environmental science. Awards and Recognition: He has received NeurIPS Top Reviewer awards (2023, 2019), NSF reviewer status, and the Teaching Award (2009). His postdoctoral fellowship at UVA was supported by the Hobby Endowment. He has held fellowships from the Zossima Brothers Foundation and the University of Illinois at Chicago. Service and Editorial Work: Dr. Diochnos serves as Managing Associate Editor of the Annals of Mathematics and Artificial Intelligence and has been a program committee member for major conferences like NeurIPS, AAAI, and IJCAI. He has organized events such as the Symposium on AI & ML at OU and served on the Scientific Committee for the International Olympiad in Informatics. Grants and Collaborations: His work is supported by NSF grants, including leadership in AI2ES. He collaborates with researchers in meteorology, oceanography, and climate science to address challenges in trustworthy AI for environmental systems. Labs and Affiliations: Dr. Diochnos is affiliated with the OU School of Computer Science and contributes to interdisciplinary initiatives like AI2ES. His research lab focuses on advancing machine learning theory with practical applications in adversarial robustness and environmental forecasting.

William Alvesمشاهده پروفایل

دانشیار

• Ethnomusicology
• Indonesian Gamelan Music
• Computer Music
• +۷ مورد دیگر

William Alves is an Associate Professor of Music in the Department of Humanities, Social Sciences, and the Arts (HSA) at Harvey Mudd College in Claremont, California. He is a composer, video artist, and scholar with deep expertise in ethnomusicology, particularly Indonesian gamelan, computer music, visual music, and alternate tuning systems. Alves co-directs MicroFest, Southern California’s annual festival of microtonal music, and directs the American Gamelan and Electronic Music ensembles at the Claremont Colleges. Associate Professor of Music, Harvey Mudd College Department of Humanities, Social Sciences, and the Arts (HSA) Director, American Gamelan Ensemble Director, Electronic Music Ensemble Co-Director, MicroFest Festival of Microtonal Music His research and creative work explore the intersections of music, technology, and global cultural traditions. He is particularly known for his work in world music pedagogy, having authored the widely adopted textbook Music of the Peoples of the World , now in its third edition, and for his biography of composer Lou Harrison. His compositions span gamelan, electronic music, and multimedia works, often blending Western and non-Western traditions. Alves’s publications and creative output reflect a strong interdisciplinary focus, with articles in journals such as Perspectives of New Music , Computer Music Journal , and SEAMUS Journal . His recent works explore microtonality, electroacoustic composition, visual music, and cross-cultural musical synthesis. The themes across his articles and compositions include global musical traditions, technological innovation in sound, and the blending of visual and auditory art forms. His scholarly and artistic contributions have been recognized through a Senior Fulbright Scholarship in Indonesia (1993–1994), where he studied and taught traditional music. He has also been active in performance, participating in Javanese and Balinese gamelan ensembles and West African drumming groups. Senior Fulbright Scholar, Indonesia (1993–1994) Co-author, Biography of Lou Harrison Author, Music of the Peoples of the World (3rd ed.) Published recordings: The Terrain of Possibilities , Imbal-Imbalan , Mystic Canyon , Guitars and Gamelan Video works: Celestial Dance (published by Kinetica Video Library) Alves has advised and mentored students through ensemble direction and coursework, though specific names of advisees are not listed. He has taught a wide range of courses including Music of the Peoples of the World , Electronic Music , Film Music , and Music Since 1900 . He has also contributed to academic discourse through publications and festival leadership. There is no mention of formal research grants, but his Fulbright award indicates significant recognition and funding support in the past. He is affiliated with the Society for Ethnomusicology and has led or participated in various musical ensembles and festivals, contributing to a vibrant interdisciplinary arts community at the Claremont Colleges. His work continues to bridge academic scholarship with artistic practice, fostering innovative approaches to music and culture.

• Mobile Robotics
• Autonomous Robotics
• Computer Vision
• +۴ مورد دیگر

António Fernando Macedo Ribeiro is an Associate Professor at the Department of Industrial Electronics within the School of Engineering at the University of Minho. He is also a Senior Researcher at the Algoritmi Research Center and a member of both the IE R&D Group and CAR R&D Lab. He graduated in Computer Science (1988), earned an MSc in Industrial Robotics (1992), and a PhD in Industrial Robotics and Advanced Manufacturing Technology (1995). His academic career includes roles as department director (2013-2016) and co-director of Algoritmi (2006-2010). He founded the Robotics Laboratory (LAR) at the University of Minho and the spin-off SAR (botnroll.com). His research focuses on mobile robotics , autonomous systems , computer vision , and industrial automation . He has led over 50 projects, including RoboParty (since 2007) and RoboCup participation (since 1999). His work spans robot localization , gesture recognition , and adaptive control . Recent publications highlight trends in autonomous navigation , deep learning for robotics, and human-robot interaction . Key subfields include hexapod locomotion, multi-agent systems, tactile sensing, and 3D recognition. He has organized over 30 events like RoboCup editions and RoboParty. He actively promotes robotics education for youth through TEDx talks, school visits, and robotics clubs.

Carsten Marohnمشاهده پروفایل

پژوهشگر

• Agroecology
• Land Use Modeling
• Soil Conservation
• +۵ مورد دیگر

Dr. Carsten Marohn is a Researcher at the University of Hohenheim, affiliated with the Institute of Agricultural Sciences in the Tropics (Hans-Ruthenberg Institute) and the Department of Agronomy in the Tropics and Subtropics. His work focuses on agroecology, land use modeling, soil conservation, and remote sensing applications in tropical and subtropical regions. He has contributed to interdisciplinary projects such as SustainSahel (2020–2025), addressing sustainable resource use and livelihood systems in West Africa. His research integrates biophysical and socioeconomic models to assess impacts of land use changes on ecosystems and food security, with a focus on Africa, Southeast Asia, and Latin America. Key contributions include developing models like LUCIA for simulating plant-animal interactions in African savannas and using MODIS EVI for food insecurity prediction in Ethiopia. He has collaborated with institutions like the World Agroforestry Centre and the Kenya Agricultural and Livestock Research Organisation. His recent projects involve scenario modeling for climate-resilient agricultural systems and analyzing historical land use change patterns using farmer decision rules. Marohn’s work emphasizes interdisciplinary approaches to sustainable agriculture, combining remote sensing, participatory research, and policy analysis. He has secured grants from the EU and DFG, contributing to global debates on food system resilience and climate adaptation strategies.

• Laser Scanning
• Point Cloud Processing
• Geospatial Information Systems
• +۳ مورد دیگر

Tamás Lovas serves as Associate Professor at the Department of Photogrammetry and Geoinformatics, Faculty of Civil Engineering, Budapest University of Technology and Economics. He teaches advanced courses in Building Information Modeling, Laser Scanning, Remote Sensing, and Intelligent Transportation Systems while supervising diploma theses in Surveying and Geoinformatics Engineering. Education: 1994: High school graduation, Városmajor High School, Budapest 1999: Certified Surveyor and Geoinformatics Engineer, Budapest University of Technology, Faculty of Civil Engineering 2005: PhD (Earth Sciences), Budapest University of Technology and Economics, Faculty of Civil Engineering Research Interests: Dr. Lovas specializes in laser scanning technologies and geospatial data processing with emphasis on airborne and terrestrial point cloud analysis. His work bridges civil engineering applications and computational methods, particularly in infrastructure monitoring and digital representation. Processing, classification, and modeling of airborne laser scanned data Accuracy testing of terrestrial laser scanning Processing and modeling of terrestrial laser scanned data Comparative study of spatial data acquisition technologies His 2022-2025 publications demonstrate accelerating integration of artificial intelligence in point cloud processing, with significant contributions to road surface extraction, urban land cover classification, and BIM automation. Current research trends show strong focus on digital twin development for autonomous vehicles and infrastructure management. Scientific Awards: Republic Scholarship (1998-1999) Karlsruhe Chancellor's Scholarship (1999) ERASMUS scholarship (2000) Korányi Fellowship (2001-2002) János Bolyai Research Scholarship (2008-2011) OHV 1st place (2008) Dean's commendation for ERASMUS committee work (2014) For Students Award - Teaching Department (2017) Advising and Grants: Dr. Lovas mentors students through diploma theses and TDK research projects on topics including object survey with amateur sensors and hull modeling. His research funding includes the prestigious János Bolyai Research Scholarship and international fellowships supporting collaborations with institutions like The Ohio State University. Labs and Teams: As founding member and supervisory board member of the Hungarian BIM Association, he drives industry-academia collaboration. His leadership roles include Deputy Dean of Education at the Faculty of Civil Engineering and responsibility for English language training programs, facilitating international academic exchange.

• Robotics
• Simultaneous Localization and Mapping (SLAM)
• Sensor Fusion
• +۵ مورد دیگر

Maurice Fallon is a Professor of Engineering Science at the University of Oxford and a Royal Society University Research Fellow, leading the Dynamic Robot Systems Group (Perception) at the Oxford Robotics Institute. His research focuses on robust probabilistic methods for localization and mapping in challenging environments through advanced sensor fusion. Education: Electronic Engineering, University College Dublin PhD in Acoustic Source Tracking, University of Cambridge Research Interests: Dr. Fallon specializes in probabilistic state estimation , legged robot navigation , and dynamic motion planning for autonomous systems operating in vision-denied or complex natural environments. His work emphasizes robustness through multi-sensor integration , with applications spanning disaster response, forestry, and industrial inspection. Key innovations include terrain-aware locomotion and long-term autonomy frameworks. Publication Trends: Recent work (2024-2025) demonstrates a strategic shift toward forest robotics and long-term industrial inspection , leveraging legged and aerial platforms. There is strong emphasis on vision foundation models for place recognition, scalable 3D reconstruction using neural radiance fields, and open-vocabulary scene understanding . The research consistently addresses real-world challenges like lighting variations, sensor dropout, and environmental dynamics. Scientific Awards: Royal Society University Research Fellowship 4x Best Paper Awards at ICRA Nominations at Intelligent Vehicles, AAAI, and Humanoids conferences Advising and Grants: Dr. Fallon has secured major funding as PI/Co-I for EU/UK projects including ORCA, RAIN, THING, MEMMO, and the DARPA SubT-winning CERBERUS team. Current initiatives include the Horizon Europe DigiForest project and UKAEA collaborations. He mentors PhD students and postdocs in robotics systems development, though specific advisees aren't listed in source materials. Labs and Teams: He directs the Dynamic Robot Systems Group, which achieved global recognition through DARPA Robotics Challenge participation and SubT Challenge victory. The team operates specialized facilities for legged robot testing and maintains partnerships with nuclear energy and forestry sectors for field deployment.

Zahra Nili Ahmadabadiمشاهده پروفایل

استادیار

• Control Systems
• Robotics
• Nonlinear Dynamics
• +۷ مورد دیگر

Dr. Zahra Nili Ahmadabadi is an Assistant Professor in the Department of Mechanical Engineering at San Diego State University (SDSU), affiliated with the College of Engineering. She leads the DSIM Lab (http://dsimlab.com/), focusing on cutting-edge research in control systems, robotics, and nonlinear dynamics. Her work integrates advanced methodologies like neural networks, sensor fusion, and chaotic systems to address challenges in autonomous navigation, vibration control, and aerospace engineering. Her research interests span Control Systems , Robotics , and Nonlinear Dynamics , with emphasis on applications such as autonomous terrain exploration, energy harvesting, and predictive modeling of mechanical systems. Recent studies highlight contributions to extremum seeking control, chaotic path planning, and vibration analysis in aerospace and industrial contexts. Publications reflect a strong focus on interdisciplinary solutions, blending theoretical insights with practical implementations in robotics, aerospace, and mechanical systems. While no scientific awards are explicitly listed, her prolific output and innovative approaches underscore her academic impact. Advising and grant activities are not detailed in available texts, though her lab’s active research indicates sustained engagement with academic and industry collaborators.

Mohamed Alyمشاهده پروفایل

استاد

• Geospatial Technologies
• Remote Sensing
• Geohazard Assessment
• +۳ مورد دیگر

Mohamed Aly is a Professor at the University of Arkansas, affiliated with the Department of Geosciences, Center for Advanced Spatial Technologies (CAST), Arkansas Center for Space & Planetary Sciences, and Environmental Dynamics (ENDY) Program. His research integrates Synthetic Aperture Radar Interferometry (InSAR), GIS, GNSS, and machine learning for geohazard assessment and environmental monitoring. Education: PhD in Geology (Radar Interferometry), Texas A&M University MS in Geology (Remote Sensing & GIS), Zagazig University Research focuses on InSAR for crustal deformation, machine learning in geospatial analysis, wildfire and landslide susceptibility modeling, and geothermal process monitoring. Recent publications emphasize multisensor data fusion and Google Earth Engine applications. Scientific awards include NASA EPSCoR Early Career Investigator, Fulbright College Teaching Commendation, and Academic Excellence from Texas A&M. He mentors students in geohazard research and geospatial technologies.

Hans Georg Beyerمشاهده پروفایل

استاد

• Renewable Energy Systems
• Energy Meteorology
• Wind Energy Forecasting
• +۴ مورد دیگر

Hans Georg Beyer is an Affiliated Professor in Energy Engineering at the Faculty of Science and Technology, The University of the Faroe Islands. His work focuses on sustainable energy systems with emphasis on renewable energy integration and meteorological aspects of power generation. With extensive publication history spanning over three decades, he has established himself as a leading researcher in renewable energy systems analysis. Professor Beyer's research interests center on sustainable energy supply systems based on renewables, with special emphasis on relating system performance characteristics to meteorological conditions. His work in Energy Meteorology covers analysis and modeling of spatial and temporal statistics of wind and irradiance fields, including forecasting methods for wind speed and solar irradiance with horizons of 6-35 hours and near now-casts in minute time scales. In Renewable Energy Systems, he investigates layout, dimensioning, modeling and performance analysis of grid-connected and stand-alone solar, wind and hybrid systems. His research bridges meteorological science with practical energy engineering applications, particularly for island and remote communities. His publication record shows consistent research activity with 55 research outputs documented, including significant contributions to solar and wind energy forecasting, hybrid system design, and grid integration challenges. Notable work includes the development of methods for satellite-derived irradiance data applications in PV system monitoring and performance assessment. Solar Energy Best Paper Award, ISES 1999 Solar World Congress, Jerusalem Professor Beyer has been instrumental in several major collaborative projects including PVSAT-2 (satellite-based PV system performance monitoring), SWERA (UNEP solar resource assessment), and various European initiatives focused on renewable energy integration. His work demonstrates strong international collaboration, particularly with German, Brazilian, and other European research institutions. While specific grant details aren't provided in the source material, his extensive publication record in high-impact journals suggests substantial research funding support throughout his career.

Qi Zhengمشاهده پروفایل

استاد

• Mathematical Modeling of Biological Processes
• Applied Stochastic Processes
• Application of Computer Algebra
• +۱ مورد دیگر

Qi Zheng is a Professor at Texas A&M University's Department of Epidemiology & Biostatistics, with research interests in Mathematical Modeling of Biological Processes, Applied Stochastic Processes, Application of Computer Algebra, and Estimation of Microbial Mutation Rates. He holds a PhD in Statistics (1993) and a BA in Mathematics (1982) from Zhejiang University. Education: PhD in Statistics from Texas A&M University (1993), BA in Mathematics from Zhejiang University (1982) Research Interests: Mathematical Modeling of Biological Processes, Applied Stochastic Processes, Application of Computer Algebra, Estimation of Microbial Mutation Rates Teaching Interests: Biostatistics, Categorical and Longitudinal Data Analysis, Statistical Computing Contact: qzheng@tamu.edu | Phone: 979.436.9398 Recent publications focus on swarm robotics, mixed-reality interfaces, and reconfigurable robotic mechanisms. Key themes include entropy-based consensus algorithms for artificial swarms, adaptable sensorimotor systems for human-swarm interaction, and innovative designs for multiterrain locomotion and robotic grasping. These works bridge theoretical stochastic modeling with practical applications in robotics and computational systems.

• Planetary Science
• Aeolian Geomorphology
• Mars Geology
• +۴ مورد دیگر

Elena Favaro is a Research Fellow at the European Space Agency (ESA), specializing in planetary science with a focus on aeolian geomorphology. She utilizes geographic information systems and high-resolution imagery to study landforms (yardangs, periodic bedrock ridges) and bedforms (megaripples, dunes, transverse aeolian ridges) on Earth and Mars, with current emphasis on Oxia Planum—the designated 2030 landing site for ESA's ExoMars Rosalind Franklin rover mission. Her research reconstructs Martian climatic history through analysis of aeolian features using remote sensing, 3D image analysis, and GIS. Key interests include landscape evolution, sediment transport processes, and wind dynamics, with specific focus on how yardangs, periodic bedrock ridges, and dust devils record past and present environmental conditions. Current work integrates deep learning for terrain classification to support mission planning at Oxia Planum. Recent publications reveal concentrated research on Oxia Planum, featuring high-resolution geological mapping, wind regime modeling, and classification of aeolian bedforms. Studies emphasize periodic bedrock ridges as paleowind indicators, secondary cratering for stratigraphic dating, and megaripple architecture for sediment transport analysis. This work provides critical context for rover operations by linking surface features to ancient climate conditions and contemporary aeolian processes.

Martin Karlsonمشاهده پروفایل

دانشیار

• Remote Sensing
• Geographic Information Systems (GIS)
• Environmental Science
• +۵ مورد دیگر

Martin Karlson is an Associate Professor at Linköping University's Department of Thematic Studies (TEMA), specializing in Environmental Change (TEMAM). He holds a Ph.D. (2016), MSc (2010), and BSc (2007) in Environmental Science from Linköping University. His research focuses on leveraging satellite imagery and GIS to study environmental processes in Africa, particularly agroforestry systems and peatlands. Key projects include analyzing tree cover impacts on soil health, groundwater, and carbon sequestration in West African parklands. He teaches specialized courses on GIS and remote sensing in environmental science. Research Interests: Remote Sensing applications in environmental monitoring GIS-based spatial analysis Climate change adaptation strategies Agroforestry and carbon dynamics Peatland ecology and mapping Recent Work Trends: Articles emphasize interdisciplinary approaches combining satellite data with field studies to address global environmental challenges, particularly in semi-arid regions and high-latitude ecosystems. Methodological innovations in multi-source remote sensing integration stand out. Scientific Contributions: His work contributes to sustainable land use policies and climate resilience frameworks, with notable collaborations like the Visual Water platform for urban stormwater planning. Grants & Advising: While no specific grants are mentioned, his projects reflect substantial funding for international collaborations. No formal advisee names are listed in the provided materials.