جست‌وجوی استاد و پژوهشگر

• Electronic Warfare
• Electro-Optics
• Infrared Technology
• +۴ مورد دیگر

Professor Mark Richardson is a distinguished academic and leader at Cranfield University, serving as Pro-Vice-Chancellor at Shrivenham and Professor of Electronic Warfare. He leads the Defence and Security Theme and has over 40 years of expertise in electro-optics, infrared technology, and countermeasures systems. Richardson holds academic appointments at the Defence Academy of the United Kingdom and is affiliated with the Centre for Electronic Warfare Information and Cyber. Education: BSc (First Class Honours) in Physics from Imperial College London, MSc (Distinction) in Applied Optics, and PhD in Infrared Physics (Cranfield University). Affiliations: Royal College of Science Associate, Fellow of the Royal Photographic Society. Research Interests: Electro-Optic Countermeasures (EOCM) Infrared Signature Modelling Man-Portable Air-Defense Systems (MANPADs) Laser and Imaging Technologies Publications: Over 300 classified and unclassified papers, focusing on countermeasures, sensor systems, and aerospace applications. Recent work includes advancements in deep learning for space navigation and multispectral imaging. Awards: GEC Research Fellowship, Classified Patent for infrared camouflage material. Advising & Grants: Supervised over 100 postgraduate students and currently mentors 20 PhD candidates. Active in defense consultancy and has organized international conferences on EO&IR countermeasures. Labs & Teams: Leads research at the Centre for Electronic Warfare Information and Cyber, collaborating with global defense organizations like DSTL and QinetiQ.

• Computational Neuroscience
• Applied Mathematics
• Partial Differential Equations
• +۷ مورد دیگر

Dr. Jianzhong Su is a Professor and Chair of Mathematics at the University of Texas at Arlington's College of Science. With over 25 years of academic leadership, he has established himself as a prominent figure in applied mathematics, holding numerous significant research grants and mentoring dozens of graduate students. His administrative role as department chair demonstrates his leadership within the academic community. Dr. Su earned his PhD in Mathematics from the University of Minnesota Twin Cities in 1990 and completed his undergraduate studies in Applied Mathematics at Shanghai Jiao Tong University in 1984. His academic journey reflects a strong foundation in both theoretical and applied mathematics. His research spans multiple interdisciplinary domains, with primary focus on computational neuroscience, partial differential equations, and data science applications in agriculture. Dr. Su's work in EEG source reconstruction and brain dynamics has significant implications for understanding neurological disorders. His recent emphasis on data science in agriculture demonstrates his ability to apply mathematical techniques to pressing real-world problems. The mathematical modeling of glucose transporter deficiency has led to important insights into epilepsy mechanisms, while his agricultural applications focus on climate-smart solutions and optimization of food production systems. Analysis of Dr. Su's recent publications reveals a strong trend toward interdisciplinary research that bridges mathematics with neuroscience, medical diagnostics, and agricultural science. His work consistently applies advanced mathematical techniques to solve complex problems in these fields, with particular emphasis on inverse problems, neural dynamics modeling, and data-driven agricultural solutions. The integration of machine learning with traditional mathematical approaches is increasingly evident in his most recent work. American Mathematical Society Award for Mathematics Programs That Make a Difference (2023) American Mathematics Society Award for an Exemplary Program or Achievement in a Mathematics Department (2013) Dr. Su has served as PI or co-PI on over $10 million in federal research, education, and training projects from NSF, USDA, NIH, and the US Department of Education. His grant portfolio includes significant projects like the ALFA-IoT alliance for smart agriculture ($220,000), USDA ARS Research Apprenticeship Program ($400,000), and DATA-Ag for climate-smart agriculture training ($500,000). He has advised over 20 PhD students across mathematical sciences, with recent dissertation committees spanning topics from neural dynamics to agricultural optimization. His leadership extends to major collaborative initiatives that bridge mathematical sciences with practical applications in healthcare and agriculture. Through his leadership of the Mathematics Department at UTA, Dr. Su has fostered collaborative research teams focused on computational neuroscience, agricultural data science, and inverse problems. His work with the Gulf States Math Alliance demonstrates commitment to regional academic collaboration, while his numerous interdisciplinary projects showcase his ability to build effective cross-disciplinary teams that tackle complex scientific challenges.

Mary Love Tagertمشاهده پروفایل

استادیار

• Farm water storage systems
• Irrigation scheduling
• Environmental fate of herbicides
• +۳ مورد دیگر

Mary Love Tagert is an Assistant Extension Professor in the Department of Agricultural and Biological Engineering at Mississippi State University (MSU), part of the College of Agricultural and Life Sciences. She specializes in water quality, irrigation management, and watershed modeling. Her roles include research and extension responsibilities focused on sustainable agricultural practices and environmental stewardship. Education: PhD in Plant and Soil Sciences (MSU, 2006), MS in Forest Resources (MSU, 2000), BS in Biology (Millsaps College, 1998). Research Interests: Farm water storage systems, irrigation scheduling optimization, environmental fate of herbicides, watershed modeling using AnnAGNPS, non-point source runoff mitigation, and geospatial technologies in environmental management. She has contributed to projects addressing nutrient dynamics, sediment transport, and water quality monitoring in agricultural systems. Publications and Presentations: Over 50 peer-reviewed articles and conference presentations since 2004, focusing on water resource management, precision agriculture, and environmental modeling. Recent work includes studies on iron-deficiency chlorosis in soybeans and soil moisture monitoring innovations. Awards: 2009–2010 Faculty Leadership Forum Participant 2005 Support Staff Research Award Her advisory and grant activities include developing the Mississippi Irrigation Scheduling Tool (MIST) and collaborating with agencies like the Mississippi Water Resources Research Institute. She is actively involved in regional water management planning and educational outreach for sustainable agricultural practices. Labs/Teams: Collaborates with the GeoResources Institute and Mississippi Water Resources Research Institute on interdisciplinary projects combining geospatial analysis and hydrologic modeling.

Daljit Singh Dhillonمشاهده پروفایل

استادیار

• Computer Graphics
• Bio-physical Modeling and Simulation
• Realistic Appearances
• +۳ مورد دیگر

Dr. Daljit Singh Dhillon is an Assistant Professor in the Visual Computing division at Clemson University's School of Computing. He joined Clemson in January 2019 after a research associate position at Imperial College London (2017–2018) and a Swiss National Science Foundation fellowship at the University of Geneva (2016–2017). His research focuses on modeling material appearances, surface geometries, and bio-physical systems, with applications in computer graphics, fabrication, and interdisciplinary collaborations. Education PhD in Computer Science, University of Bern, Switzerland (2011–2015) M.Sc. (Engg.), Indian Institute of Science, Bengaluru (2007–2010) Bachelor's in Computer Engineering, University of Mumbai (1995–1999) Research Interests His work bridges visual computing and interdisciplinary fields, emphasizing practical measurement and modeling of materials like skin, holographic surfaces, and biological nanostructures. Notable contributions include spectral skin reflectance modeling, diffraction effects in reptile skin, and feather appearance rendering. He also collaborates on NSF-funded projects, such as developing light-scattering models for bird feathers. Grants & Awards NSF-Small Grant ($477K) for feather light-scattering research (2020) SNSF Early Postdoc Mobility Fellowship (2016–2017) Labs & Teams He leads research on material appearance and surface geometry processing at Clemson, with students like Makayla Master (PhD) and Srihith Alwala (research assistant). Collaborations include paleontologists and biologists for projects like feather structural modeling.

Howard Liمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Control Systems
• +۳ مورد دیگر

Howard Li is a Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick's Faculty of Engineering. His research focuses on robotics, artificial intelligence, unmanned vehicles, control systems, and quantum computing. Dr. Li completed his Ph.D. at the University of Waterloo and has conducted research internationally at institutions including EPFL (Switzerland) and University of Pavia (Italy). He has industry experience developing training systems for fighter aircraft and control systems for autonomous vehicles. His research interests span robotics, autonomous systems, quantum computing, and AI applications in mechatronics. Recent publications demonstrate focus on LiDAR simulation, deep learning architectures, satellite imagery analysis, and geospatial algorithms. Dr. Li has secured over $1,000,000 in research grants from agencies including NSERC, CFI, and DRDC. He chairs the IEEE Autonomous Robotics Group and contributed to the first IEEE robotics standard. Harrison McCain Foundation Young Scholars Award NSERC Postgraduate Scholarship IEEE Senior Member recognition He established the COBRA research group and open-source Quad Rotor Simulator. All his former postdocs/PhDs secured positions at prestigious institutions including MIT and NASA.

Rakesh Mishraمشاهده پروفایل

استاد مدعو

• Remote Sensing
• Computer Vision
• Artificial Intelligence
• +۱ مورد دیگر

Rakesh Mishra is an Adjunct Professor in the Department of Geodesy and Geomatics Engineering at the University of New Brunswick and Chief Technology Officer at SceneSharp Technologies. His expertise includes multi-sensor data fusion, computer vision, and AI-based object detection using LiDAR, SAR, and satellite imagery. Dr. Mishra completed his PhD at UNB and has research experience with institutions including Indian Institute of Technology Kanpur and IIRS-ISRO. He has collaborated with Canadian government agencies including DND, NRC, and NRCan. His research focuses on LiDAR simulation, deep learning applications in remote sensing, and geospatial algorithm development. Recent publications demonstrate advancements in physics-aware deep learning for LiDAR and super-resolution techniques for satellite imagery.

Ming Dongمشاهده پروفایل

استاد

• Deep Learning
• Data Mining
• Computer Vision
• +۴ مورد دیگر

Ming Dong is a Professor in the Department of Computer Science at Wayne State University, where he also serves as the co-director of the Data Science and Business Analytics MS program and the AI, Big Data & Analytics Group. He directs the Machine Vision and Pattern Recognition Lab, focusing on deep learning, data mining, and computer vision applications in health informatics and automotive industries. His research explores advanced computational methods including deep neural networks for medical image analysis, generative models for image synthesis, and multimodal learning techniques. Recent work focuses on medical image segmentation, 3D point cloud understanding, and image-to-image translation for clinical applications. Dr. Dong has secured significant research funding from National Science Foundation, National Institutes of Health, State of Michigan, and industry partners including Ford Motor Company. His research has resulted in over 100 publications in premium journals and conferences. He serves as associate editor for Statistical Analysis and Data Mining and IEEE Transactions on Circuits and Systems for Video Technology , and regularly participates in NSF review panels and conference program committees.

• Surface and groundwater hydrology
• Flood warning and alert systems
• Water infrastructure
• +۵ مورد دیگر

Dr. Nick Z. Fang is the Robert S. Gooch Endowed Professor in Civil Engineering at The University of Texas at Arlington (UTA), leading the Water Engineering Research Center (WERC) and Fang Research Group. He earned his Ph.D. from Rice University in 2008 and previously contributed to the SSPEED Center at Rice, securing over $6 million in research funds. He collaborates with federal agencies (NWS, USACE) and municipal bodies to address water-related challenges in Texas and beyond. Dr. Fang focuses on flood prediction, water infrastructure resilience, and disaster mitigation, developing real-time flood warning systems, such as the Texas Medical Center’s radar-based system. Education: Ph.D., Civil & Environmental Engineering, Rice University, 2008 MS, Chemical Engineering, Lamar University, 2003 BS, Environmental Engineering, Zhejiang University, 1998 Research Interests: Surface/groundwater hydrology, flood warning systems, water quality strategies, hydrologic modeling, stormwater management, and disaster mitigation. His work integrates advanced sensing technologies (UAVs, radar) and machine learning to enhance flood forecasting and infrastructure resilience. Grants & Awards: Robert S. Gooch Endowed Professorship (2024) 2019 Engineering Excellence Gold Medal (ACEC Texas) NSF grants for urban water modeling and disaster preparedness Over $30 million in research funding from federal/state agencies (NOAA, FEMA, USDA) Advising & Leadership: Advisor to over 30 graduate students. Leads UTA’s Interagency Flood Risk Management (InFRM) team, collaborating with USACE, FEMA, and NOAA. Serves on editorial boards and peer-review panels for major journals and agencies. Labs & Teams: WERC and Fang Research Group at UTA, focusing on flood modeling, UAV applications, and sustainable water management. Partnerships include NASA, USDA, and local municipalities for applied research projects.

Jeffrey Hickeمشاهده پروفایل

استاد

• Climate Change
• Global Environmental Change
• Forest Disturbances
• +۳ مورد دیگر

Jeffrey Hicke is a Professor in the Department of Earth and Spatial Sciences at the University of Idaho's College of Science. His research focuses on climate change, global environmental change, and forest disturbances, with an emphasis on understanding the impacts of disturbances such as bark beetles, drought, and wildfires on forest ecosystems. He holds a Ph.D. in Atmospheric Science from the University of Colorado (2000), an M.A. in Geography from the University of California, Santa Barbara (1994), and a B.S. in Mathematics/Computer Science from UCLA (1985). His work integrates remote sensing, ecological modeling, and field studies to address questions about forest resilience, carbon dynamics, and disturbance regimes. Recent publications highlight advancements in detecting forest mortality using satellite and drone imagery, quantifying climate influences on pest outbreaks, and evaluating the interplay between fire and insect disturbances. Hicke collaborates extensively with federal agencies and international organizations, contributing to climate assessments like the IPCC reports. Key research trends include developing tools for monitoring forest health at large scales, predicting vulnerability to climate-driven disturbances, and informing adaptive management strategies. His contributions span theoretical and applied science, bridging ecology, climatology, and geospatial technologies to address pressing environmental challenges.

Karen Humesمشاهده پروفایل

استاد

• Water/Energy Nexus
• Food Systems Sustainability
• Remote Sensing Applications
• +۳ مورد دیگر

Karen Humes is a Professor in the Department of Earth and Spatial Sciences at the University of Idaho, College of Science. Her research focuses on the Water/Energy nexus in food systems and the application of remote sensing/GIS in hydrology and environmental science. She holds a Ph.D. in Hydrology from the University of Arizona, an M.S. in Soil Science (University of Arizona), and a B.S. in Geophysics from New Mexico Institute of Mining and Technology. Her educational background includes advanced studies in hydrology, soil science, and geophysics, providing a multidisciplinary foundation for her work. Research interests emphasize sustainable water-energy use in agriculture and innovative geospatial techniques for environmental monitoring. Recent projects include climate-impact assessments, disaster recovery strategies, and pest detection in forest ecosystems using satellite data. Publications span topics like streamflow forecasting, snowpack modeling, and forest health monitoring. Though no formal awards are listed, her extensive peer-reviewed output reflects significant contributions to environmental science. She advises on research projects but no specific students are named. Her work integrates hydrological modeling with technological advancements in remote sensing, addressing real-world challenges in resource management and environmental resilience.

Aaron Sparksمشاهده پروفایل

استاد پژوهشی

• Remote Sensing
• Precision Forestry
• Wildland Fire Ecology
• +۱ مورد دیگر

Aaron Sparks, Ph.D., is Research Assistant Professor of Fire Ecology & Geospatial Data Analysis at the University of Idaho. His work integrates remote sensing, field ecology, and geospatial analysis to understand fire effects on forest ecosystems. Education: Ph.D. in Natural Resources from University of Idaho (2017) M.S. in Natural Resources from University of Idaho (2014) B.S. in Resource Conservation from University of Montana (2010) Research combines LiDAR, multispectral imaging, and field measurements to quantify fire impacts on tree mortality, forest structure, and regeneration patterns. Current projects include developing remote sensing protocols for assessing fire-induced tree mortality, evaluating drought-fire interactions on conifer recovery, and mapping wildfire risk in Mediterranean landscapes. His methods advance precision forestry applications through improved inventory techniques and mortality prediction models.

Benjamin Fraserمشاهده پروفایل

استادیار مهمان

• Geographic Information Systems
• Remote Sensing
• Spatial Data Science
• +۷ مورد دیگر

Benjamin Fraser serves as a Visiting Assistant Professor in the Department of Natural Resources and the Environment at the University of New Hampshire, where he directs the Basic and Applied Spatial Analysis Lab and acts as AmericaView State Coordinator. With over a decade of experience, he specializes in applying geospatial technologies—GIS, remote sensing, and Unpiloted Aerial Systems (UAS)—to natural resource management across scales from individual trees to multi-million-acre landscapes. His work bridges technical innovation with practical conservation needs for agencies like the NH Division of Forests and Lands. Dr. Fraser's research centers on spatial data science and geovisualization for forest ecology and environmental conservation. He develops cutting-edge UAS and deep learning methods to monitor forest health, track pest outbreaks like spongy moth, and assess water quality. His international consulting portfolio spans nine countries across three continents with organizations including USAID, Wildlife Conservation Society, and NASA's SERVIR-SEA, addressing challenges in sustainable development and wildlife conservation through interdisciplinary collaboration. Analysis of his 10 publications (2018-2025) reveals consistent innovation in UAS applications, with dominant themes in individual tree detection, early pest identification, and cyanobacteria monitoring. His work demonstrates increasing integration of deep learning algorithms with multispectral imagery to enhance accuracy for land managers, particularly in temperate forest ecosystems. No scientific awards are documented in the provided materials. Dr. Fraser teaches core courses in Geographic Information Systems (NR 658), Remote Sensing (NR 757/857), and Digital Image Processing (NR 759/859) but has no listed advisees or grant details. He leads the Basic and Applied Spatial Analysis Lab, which develops spatial analysis methodologies for natural resource challenges, and coordinates AmericaView's state-level geospatial initiatives to support New Hampshire's environmental management needs through technology access and training.

Baoxin Huمشاهده پروفایل

استاد

• Remote Sensing
• Geomatics Engineering
• LiDAR Data Processing
• +۵ مورد دیگر

Dr. Baoxin Hu is a Professor in Geomatics Engineering at York University's ESSE department since 2003. She leads airborne LiDAR and hyperspectral missions, focusing on vegetation canopy characterization and wetland ecosystems. Her research integrates multi-source remote sensing data for environmental monitoring, including DEM generation and permafrost analysis. She directs the Earth Observation Laboratory located in Petrie Halls. Education background includes prior visiting fellowships at the Canadian Space Agency. Research emphasizes algorithm development for 3D scene reconstruction, forest succession stage analysis, and EAB infestation detection. Key areas include spatial-temporal modeling, InSAR technology applications, and machine learning integration with geospatial data. Publications span LiDAR-based methods (e.g., boundary adjustment algorithms, individual tree crown delineation) to multi-source data fusion for carbon modeling. Active in developing CNN frameworks for land cover classification and environmental impact assessments. Collaborates on projects involving RADARSAT-2 data and MODIS time-series analysis for northern Ontario ecosystems.

Konstantinos Derpanisمشاهده پروفایل

دانشیار

• Computer Vision
• Artificial Intelligence
• Data Science
• +۵ مورد دیگر

Konstantinos Derpanis is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University. He holds a BSc (Honours) in Computer Science from the University of Toronto (2000), an MSc and PhD in Computer Science from York University (2003, 2010). His doctoral work earned the CIPPRS Doctoral Dissertation Award 2010 Honourable Mention. Prior to York, he served as Associate Professor at Ryerson University (2012–2020) and was a postdoctoral researcher at the GRASP Laboratory, University of Pennsylvania (under Prof. Kostas Daniilidis). He currently serves as an Associate Editor for IEEE TPAMI and Area Chair for AAAI 2021, ICRA 2021, CVPR 2021, and ICCV 2021. His research focuses on computer vision with emphasis on motion analysis, human motion understanding, and applications in image processing and machine learning (including deep learning). Key interests include generative models, neural radiance fields, and vision-language systems. His work bridges theoretical advancements and practical applications in computational photography, 3D reconstruction, and AI-driven perception. Education: BSc (Honours), Computer Science, University of Toronto, 2000 MSc (Computer Science, York University, 2003, supervised by Prof. John Tsotsos & Prof. Richard Wildes) PhD (Computer Science, York University, 2010, supervised by Prof. Richard Wildes) Awards: CIPPRS Doctoral Dissertation Award 2010 Honourable Mention His recent research trends highlight contributions to neural radiance fields (NeRF), generative models, and vision-language systems. He explores techniques for robust scene representation, image/video editing via text instructions, and cross-modal retrieval. His work also addresses challenges in sensor fusion, temporal alignment, and interpretable AI. Dr. Derpanis has no listed grants or advisees in the provided texts but maintains active roles in academic service and conference organization.

Pieter G. Kikمشاهده پروفایل

دانشیار

• Nanophotonics
• Near-Field Optics
• Optical Engineering
• +۵ مورد دیگر

Pieter G. Kik is an Associate Professor in the Department of Optics & Photonics at CREOL, The College of Optics and Photonics, University of Central Florida. His research focuses on nanophotonics and near-field optics, with expertise in optical analysis tools for nanostructured devices. He leads a team investigating surface plasmon dispersion, erbium excitation enhancement in semiconductor nanocrystals, and plasmon-induced optical nonlinearities. Kik has been recognized for teaching excellence with awards from 2006 to 2014, including the 2006 Presidential Major Research Equipment Award and the 2007 Millionaire’s Club for research contributions. His research group employs advanced setups like near-field scanning optical microscopes, fiber-coupled microscopes, and variable-temperature photoluminescence systems. Key projects include manipulating plasmon dispersion in nanoscale films and developing transparent electrode geometries for light-trapping applications. Kik has advised multiple graduate students and contributed to over 15 peer-reviewed publications since 2018, with recent work on metasurface optofluidics and anti-biofouling silica nanoparticulate films. Awards: Excellence in Teaching (2013, 2014), TIP Award (2009), Millionaire’s Club (2007) Advising: 6 completed PhD/MS students, including Mengdi Sun (2022) and Fabricio Casco (current M.S.) Labs: Specializes in nanophotonics labs with cutting-edge optical characterization tools