جست‌وجوی استاد و پژوهشگر

Peiyuan Panمشاهده پروفایل

مدرس ارشد

• Software System Development
• Web-based Applications
• Artificial Intelligence Technologies
• +۳ مورد دیگر

Dr. Peiyuan Pan is a Senior Lecturer in Computer Science at London Metropolitan University, affiliated with the School of Computing and Digital Media. He holds a PhD in Computer-aided Manufacturing Engineering, a postgraduate certificate in Teaching and Learning in Higher Education, and a BSc (Hons) in Computer Science. He specializes in teaching OO programming, web systems development, and e-commerce applications. His research focuses on software system development, AI technologies, embedded systems, e-manufacturing, and supply chain management. Dr. Pan has led several research projects, including a Virtual Surgery system for Java programming education (2010–2011) and an Internet-based supply chain improvement system (1999–2002). He received the Vice Chancellor's Teaching Fellowship Award in 2010–2011. His publications span e-learning methodologies, robotics, and manufacturing automation. He contributes to interdisciplinary work in AI-driven design systems, fuzzy logic protocols, and web-based expert systems. His teaching responsibilities include leading the Computing and Business Information Technology FdSc program. Professional affiliations include the ACM and active participation in international conferences on computing and manufacturing systems.

Liem Tranمشاهده پروفایل

استاد

• Physical Geography
• Environmental Science
• Spatial Data Science
• +۳ مورد دیگر

Liem Tran is a Professor and Associate Dean for Academic Programs in the Department of Geography, Environment, and Earth Sciences at the University of Tennessee. His academic focus lies in Physical Geography and Geographic Information Science and Technology (GIST), with affiliations in the U.S. EPA’s Regional Vulnerability Assessment (ReVA) program. He has been a core team member of ReVA since 2000, contributing integration techniques and distance measures for environmental vulnerability analysis. Dr. Tran holds a Ph.D. from the University of Hawaii. His research emphasizes integrated regional vulnerability assessment, artificial intelligence applications in geographic modeling (e.g., neural networks, fuzzy logic), and GIS-driven spatial analysis. Notable contributions include developing frameworks for ecosystem service evaluation in China and disaster preparedness tools for flooding in rural areas. His work bridges environmental science and public health, addressing topics like healthcare accessibility, sleep disparities, and hospital closure impacts. Teaching focuses include Geography 131 (Natural Environment), GIS, and quantitative methods. He maintains active engagement with environmental justice and health equity through spatial data science. Publications highlight trends in geographic disparities, disaster resilience, and policy-relevant spatial analysis. His interdisciplinary approach combines environmental vulnerability metrics with socioeconomic factors to inform sustainable development strategies.

Mike Mooneyمشاهده پروفایل

استاد

• Tunneling Engineering
• Underground Construction
• Geotechnical Engineering
• +۵ مورد دیگر

Mike Mooney is a Professor of Mechanical Engineering at the Colorado School of Mines, holding the Grewcock Chair in Underground Construction & Tunneling. He directs the Center for Underground and leads the Heavy Construction Studio, focusing on advancing smart, rapid, and cost-effective construction technologies for urban tunneling and challenging ground conditions through instrumentation integration and field experimentation. His educational background includes: PhD in Civil Engineering, Northwestern University, 1996 MS in Civil Engineering, University of California, Irvine, 1993 BS in Civil Engineering, Washington University, St. Louis, 1991 BA in Physics, Hastings College, 1991 Mooney's research integrates instrumentation into tunnel boring machines and horizontal directional drilling systems, studying robotic excavation, soil transformation using polymers/foams, and ground-mechanical interactions via physics models and machine learning. His group conducts extensive field campaigns embedded in real construction projects worldwide, emphasizing data-driven approaches to complex geotechnical challenges. Recent publications (2018-2023) demonstrate expertise in TBM performance optimization, boulder detection systems, soil conditioning, and machine learning applications for ground prediction. Key contributions include real-time vibration monitoring for Venice lagoon restoration, annular pressure management, foam stability analysis, and autonomous tunneling frameworks across major projects in Seattle, Toronto, Los Angeles, and New York City. No scientific awards or fellowships were mentioned in the provided text. Professor Mooney actively advises graduate students as evidenced by extensive student co-authorship in publications. His research is directly applied to international construction projects including the Venice lagoon restoration and urban tunneling initiatives. He is a registered Professional Engineer in Colorado (License #39682) and provides technical consultation for construction projects globally. He directs the Center for Underground at Colorado School of Mines, where his Heavy Construction Studio develops instrumentation systems and conducts field experiments integrated into active construction sites. The lab specializes in real-time monitoring technologies, ground characterization methods, and machine learning applications for tunneling operations.

Saeed Boorboorمشاهده پروفایل

استادیار مدعو

• Visualization
• Computer Graphics
• Medical Imaging
• +۴ مورد دیگر

Saeed Boorboor is a Principal Research Scientist at Stony Brook University's Center for Visual Computing and an Adjunct Assistant Professor at the University of Illinois at Chicago. His research focuses on immersive visualization systems, AR/VR/MR, medical imaging, and applied AI. He received his Ph.D. from Stony Brook University under Arie E. Kaufman and a B.S. from LUMS, Pakistan. He will join UIC as an Assistant Professor in Fall 2025. Education: Ph.D. in Computer Science, Stony Brook University (2015–2023) B.S. in Computer Science, LUMS, Pakistan (2010–2014) Research Interests: Dr. Boorboor designs visualization systems for scientific data exploration, leveraging immersive technologies like AR/VR. His work emphasizes human-centered design, applied AI, and novel interaction methods. Recent projects include Explainable XR , Silo , and NeuRegenerate . Publications & Awards: Over 20 peer-reviewed papers, patents in medical imaging, and awards including the IACS Junior Researcher Award and Stony Brook Chair Fellowship. His work has been presented at IEEE VIS, SIGGRAPH, and EuroVis. Teaching: Taught courses like CSE 366 (VR), EMP 532 (Big Data Systems), and mentored 17+ students. Currently recruiting students for his UIC lab.

Joseph Scalia IVمشاهده پروفایل

دانشیار

• Geoenvironmental Engineering
• Geotechnical Engineering
• Contaminant Hydrology
• +۴ مورد دیگر

Joseph Scalia IV is an Associate Professor in the Department of Civil and Environmental Engineering at Colorado State University (CSU), affiliated with the College of Engineering. Prior to joining CSU, he worked as a senior associate at Exponent (formerly Failure Analysis Associates) in their Environmental and Earth Sciences Practice. His research focuses on geoenvironmental and geotechnical engineering, particularly the intersection of soil mechanics with contaminant hydrology, environmental engineering, and mine waste management. Scalia holds a B.S. in Civil and Environmental Engineering from Bucknell University and M.S. and Ph.D. in Geological Engineering from the University of Wisconsin-Madison. He leads the Geoenvironmental Lab, which addresses challenges in tailings management, unsaturated terramechanics, and barrier systems for environmental protection. Education: Ph.D., Geological Engineering, University of Wisconsin-Madison (2012) M.S., Geological Engineering, University of Wisconsin-Madison (2009) B.S., Civil and Environmental Engineering, Bucknell University (2007) Research interests include geotechnical stability of tailings storage facilities, hydraulic conductivity of waste materials, and innovative containment systems. His work integrates field experimentation, laboratory testing, and numerical modeling to solve environmental and geotechnical challenges. Recent studies emphasize soil moisture dynamics in mine tailings, chemico-osmotic effects in clay barriers, and polymer-enhanced geosynthetic clay liners for waste containment. Labs/Teams: Geoenvironmental Lab : Focuses on tailings engineering, landfill covers, and geoenvironmental barrier systems. Advancing barrier systems for contaminated sites and optimizing landfill cover designs are central themes. While no specific grants or awards are listed, his extensive publication record reflects sustained contributions to environmental geotechnics and mine waste management.

Ursula Eickerمشاهده پروفایل

استاد

• Urban energy systems
• 3D City modeling
• Urban data and simulation platform development
• +۷ مورد دیگر

Prof. Ursula Eicker is the Canada Excellence Research Chair in Smart, Sustainable and Resilient Cities and Communities at Concordia University , leading cutting-edge research in urban energy systems. Her work integrates 3D city modeling, renewable energy systems, and sustainable transport to develop zero-carbon city strategies. PhD in Solid State Physics (Heriot-Watt University) Habilitation in Renewable Energy Systems (Technische Universitat Berlin) Research Interests focus on urban simulation platforms, district energy networks, and climate-resilient infrastructure. The INSEL4Cities platform enables holistic urban modeling for building demands, transportation, and greenery. Her Residential Densification studies demonstrate 65% energy reduction through retrofits and solar integration. Recent publications explore urban solar shading , transactive energy systems , green infrastructure equity , and decentralized hydrogen production . Awards include the German-African Innovation Incentive and recognition for photovoltaic research in Egypt. Over 50 graduate students in her lab examine zero-carbon pathways. Teaches ENCS 691 on urban energy systems. Secured 10M CAD for the CERC chair and multiple grants. Co-Director of Concordia's Next Generation Cities Institute .

Nathan Lenssenمشاهده پروفایل

استادیار

• Climate Science
• Statistical Prediction
• Spatial Statistics
• +۴ مورد دیگر

Dr. Nathan Lenssen is a Teaching Assistant Professor in the Department of Applied Mathematics and Statistics at the Colorado School of Mines, as well as a Project Scientist at the National Center for Atmospheric Research (NCAR). His academic background includes a B.A. in Mathematics and Physics from Claremont McKenna College, an M.A. in Statistics, and a Ph.D. in Earth and Environmental Sciences from Columbia University. Research Focus: Lenssen's work centers on understanding climate system variability, predictability, and change. He develops statistical and dynamical models to analyze large-scale datasets, addressing challenges like climate model biases and observational uncertainties. Key areas include ENSO predictability, climate impact projections, and spatial statistics for geoscience applications. Teaching & Curriculum: He designs data science and climate science courses emphasizing project-based learning. Current courses include Math 324 (Statistical Modeling), Math 334 (Introduction to Probability), and Math 335 (Introduction to Mathematical Statistics). His pedagogical approach integrates statistical methods with real-world environmental questions. Publications: Lenssen's research spans topics like Arctic warming amplification, ENSO forecast skill, and uncertainty quantification in climate models. His work bridges computational methods, large-scale climate dynamics, and interdisciplinary applications. Professional Engagement: His dual role at Mines and NCAR reflects a commitment to both education and cutting-edge climate science. He collaborates on projects like crop yield forecasting and NASA's GISTEMP uncertainty modeling, highlighting the societal relevance of his work.

• Physical geography
• Environmental geoscience
• Hydrology
• +۶ مورد دیگر

Professor Richard Forster from the University of Utah's School of Environment, Society & Sustainability is a leading expert in glaciology and remote sensing with ORCID 0000-0003-3945-5072. His research focuses on firn aquifers, cryospheric processes, and hydrological modeling through advanced geophysical techniques. Current position: Professor (2010-present) Previous academic positions: Assistant Professor (1999-2004), Associate Professor (2004-2010) at University of Utah Research interests include: Firn aquifer dynamics and ice sheet hydrology Remote sensing of snow and glacier systems Climate change impacts on cryospheric regions Hydrological modeling in extreme environments Recent publications demonstrate methodological innovations in SAR coherence analysis, firn aquifer characterization, and snowmelt progression mapping across Greenland, Antarctica, and the Indus Basin. His work integrates field measurements with advanced geophysical techniques. Scientific awards include: College Senior Superior Research Award (2012) Student Choice Teaching Award (2009) Professional activities feature service on NASA's Standing Review Board (2014-2016) and multiple NSF advisory roles (2008-2011). He has secured major grants from NASA and NSF for ice sheet monitoring and snow water equivalent estimation.

Chris Kolibaمشاهده پروفایل

استاد

• Governance Networks
• Complex Adaptive Systems
• Community Resilience
• +۷ مورد دیگر

Chris Koliba is the Edwin O. Stene Distinguished Professor at the University of Kansas School of Public Affairs and Administration (SPAA), where he focuses on governance networks, complex systems, and community resilience. Previously, he served as a Professor at the University of Vermont, directing the MPA program and founding the Office of Engagement. His academic journey includes a Ph.D. from Syracuse University's Interdisciplinary Social Science Program, an MPA from Maxwell School, and a BS in Finance from Whitman School of Business. Research Interests: Koliba’s work bridges governance networks, complex adaptive systems, and critical infrastructure resilience. He employs computational and qualitative methods in domains like water quality, food systems, and disaster response. He has secured significant grants from NSF, USDA, and other agencies. Professional Contributions: He co-founded the SEGS Lab, served at Vermont EPSCoR, and was elected a Fellow of the National Academy of Public Administration (2023). His awards include the Marshall Dimock Award (2015) and a Regional Emmy for the documentary Saving Our Waters (2018). He teaches courses on public policy, organizational behavior, and science-society interfaces. Service & Engagement: Koliba held leadership roles in NASPAA, the American Society for Public Administration, and local governance. He has collaborated internationally, including as a Fulbright Scholar in Sri Lanka (2015).

René Westerholtمشاهده پروفایل

استادیار

• Spatial Analysis
• GIScience
• Urban Analytics
• +۷ مورد دیگر

René Westerholt is an Assistant Professor (Juniorprofessor) in Spatial Modelling at the Department of Spatial Planning at Technische Universität Dortmund, Germany. He also leads the Spatial Modelling Lab (RAM) and is affiliated with the GIScience research group at Heidelberg University. His academic background includes a PhD in Geography from Heidelberg University and an M.Sc. in Geoinformatics from Osnabrück University. His research focuses on spatial analysis methodologies, particularly integrating social dimensions into quantitative analysis. Key areas include geosocial media data analysis, spatial autocorrelation, and urban analytics. He has interdisciplinary experience in software development for nature conservation and agricultural projects, and is active in professional societies like the Royal Geographical Society and DGPF. Teaching responsibilities include leading the M.Sc. Urban Analytics and Visualisation programme at the University of Warwick and courses such as IM913 Spatial Methods and IM927 Digital Cities. His work bridges theoretical GIScience with practical applications in urban planning and environmental studies.

Oh Joon-Yeoulمشاهده پروفایل

دانشیار

• Network Optimization
• Wireless Telecommunication Network Expansion and Optimization
• Non-Linear Programming
• +۶ مورد دیگر

Oh Joon-Yeoul serves as Associate Professor in the Department of Mechanical and Industrial Engineering at Texas A&M University-Kingsville's College of Engineering, specializing in optimization methodologies for telecommunications and public infrastructure systems. His academic credentials include: Ph.D. in Industrial Engineering (Operations Research), New Mexico State University (2003) M.S. in Industrial Engineering (Engineering Management), New Mexico State University (2000) M.S. in Industrial Engineering (Operations Research), Chong-Ju University (1998) B.S. in Industrial Engineering, Chong-Ju University (1995) Dr. Oh's research integrates mathematical programming and algorithmic development to solve complex industrial problems, with core expertise in Network Optimization , Wireless Telecommunication Systems , and Queueing Theory . His work bridges theoretical operations research with practical applications in municipal services, robotics, and emergency management, emphasizing non-linear and heuristic integer programming approaches for large-scale systems. Analysis of his 15 publications (2015-2020) reveals consistent focus on vehicle routing optimization (including multi-vehicle scenarios), facility location for public safety infrastructure, and multi-criteria decision frameworks . His research demonstrates strong methodological continuity in applying combinatorial optimization to real-world challenges like garbage collection routing, fire station allocation, and telecommunication network expansion, primarily through conference presentations at INFORMS and industrial engineering forums. Dr. Oh actively mentors graduate researchers as evidenced by student co-authorship on projects involving blockchain applications, humanoid robotics, and municipal service optimization. While specific grant details aren't documented, his collaborative work with colleagues like Amir Hessami indicates engagement in funded research initiatives addressing regional infrastructure challenges in South Texas. His research team focuses on practical implementation of optimization models for Kingsville municipal operations, particularly in waste management and emergency response systems, though dedicated laboratory facilities aren't specified in available materials.

Ari Sternمشاهده پروفایل

استاد

• Geometric Numerical Analysis
• Computational Mathematics
• Applied Analysis
• +۴ مورد دیگر

Ari Stern is a Professor of Mathematics at Washington University in St. Louis , specializing in Geometric Numerical Analysis . His work bridges geometry, applied analysis, and computational mathematics, focusing on numerical methods that maintain global accuracy for differential equations through modern geometric principles. He earned his B.A. and M.A. in Mathematics from Columbia University and a Ph.D. in Applied and Computational Mathematics from Caltech (2009), advised by Jerrold E. Marsden and Mathieu Desbrun. Prior to WashU (2012), he was a postdoc at UCSD with Michael Holst. Research Interests : Geometric integration, finite element exterior calculus, symplectic geometry, and applications to physics and machine learning. His recent publications address multisymplecticity, functional equivariance, and hybrid finite element methods. Collaborations span topics from Alzheimer’s disease modeling via machine learning to Hamiltonian mechanics and geometric electrodynamics. Awards : NSF Grant (2019). Teaching : Courses include Numerical Methods for Differential Equations, Measure Theory, and Honors Mathematics.

Haoxiang Langمشاهده پروفایل

دانشیار

• Mechatronics
• Autonomous Robotics
• Visual Servoing
• +۳ مورد دیگر

Haoxiang Lang serves as Department Chair and Associate Professor in the Department of Automotive and Mechatronics Engineering at Ontario Tech University's Faculty of Engineering and Applied Science. His laboratory, GRASP Lab, focuses on advanced robotics and intelligent systems research. Education: PhD in Mechanical Engineering, University of British Columbia (2013) MASc in Mechanical Engineering, University of British Columbia (2008) BSc in Marine Engineering, Ningbo University (2003) Dr. Lang's research spans mechatronics, autonomous robotics, visual servoing, and machine learning. His work focuses on developing advanced control systems for robotic manipulation, autonomous vehicle navigation, and sensor fusion techniques. Recent projects include vision-based combat vehicle control, deep learning for aerial image processing, and thermal management for robotic systems. His publications demonstrate strong emphasis on robotic perception-control integration, with recurring themes in visual servoing, sensor fusion, autonomous navigation, and machine learning applications in robotics. Recent works increasingly incorporate deep neural networks for complex tasks like object manipulation and environment mapping. Dr. Lang leads the GRASP Lab, which develops experimental platforms including autonomous combat vehicles and robotic manipulators. The lab focuses on practical implementations of control theories and collaborates on industrial applications.

Maarten van der Vegtمشاهده پروفایل

دانشیار

• Coastal Dynamics
• Sediment Transport
• Delta Morphology
• +۳ مورد دیگر

Maarten van der Vegt is an Associate Professor in Physical Geography at Utrecht University's Faculty of Geosciences. His research focuses on coastal dynamics, sediment transport, and delta morphology, with a particular emphasis on tidal systems, estuaries, and human impacts on coastal environments. He leads projects like the 'Rise and Fall' initiative studying the Mekong Delta and contributes to programs such as 'Future Deltas' and 'Pathways to Sustainability.' His work integrates computational modeling (e.g., Delft3D), field observations, and laboratory experiments to understand processes like saltwater intrusion, sediment budget changes, and tidal inlet dynamics. Recent studies include the stability of river bifurcations, cyclic channel-shoal dynamics, and the effects of sea-level rise on estuaries. He collaborates with institutions globally and advises PhD students on projects related to deltas and coastal systems. Van der Vegt teaches courses on coastal morphodynamics, tides, and marine sciences, and actively publishes in top journals like Journal of Geophysical Research and Earth Surface Dynamics . His research has been funded by grants such as the NWO Urbanizing Deltas of the World program.

Sarah L Danceمشاهده پروفایل

استاد

• Data Assimilation
• Environmental Science
• Numerical Weather Prediction
• +۳ مورد دیگر

Professor Sarah L Dance is a Professor of Data Assimilation and EPSRC Senior Fellow in Digital Technology for Living With Environmental Change at the University of Reading's Department of Mathematics and Statistics, part of the School of Mathematical, Physical and Computational Sciences. She leads the Data Assimilation Research Centre (DARC) and focuses on advancing data assimilation techniques in weather forecasting, hydrology, and environmental monitoring. Her work integrates cutting-edge computational methods with real-world applications, particularly in improving flood prediction and soil moisture estimation through innovative modeling approaches. Her research interests span data assimilation algorithms, remote sensing applications, and numerical modeling of environmental systems. Recent work emphasizes the use of satellite data, radar observations, and deep learning for environmental monitoring and disaster management. She collaborates extensively with international institutions on projects like Hydro-JULES and the Transatlantic Data Science Academy, advancing both theoretical and applied aspects of environmental data science. Professor Dance has contributed to operational systems such as the Met Office's data assimilation frameworks and has pioneered methods to handle observation uncertainty in high-resolution models. Her projects often bridge academia and industry, addressing challenges in flood forecasting, climate modeling, and sensor data integration.