جست‌وجوی استاد و پژوهشگر

Ruud A.P. van Herpenمشاهده پروفایل

پژوهشگر ارشد

• Fire Safety Engineering
• Building Physics
• Materials Science
• +۳ مورد دیگر

Ruud A.P. van Herpen is a Research Fellow in Fire Safety Engineering at Eindhoven University of Technology (TU/e) and a Professor at Saxion University of Applied Sciences. He holds a Master’s degree in Civil Engineering from Delft University of Technology (1987) and transitioned to fire safety engineering around 1995. His career includes roles as Technical Director at Nieman Consulting Engineers (2002–2021) and Senior Fire Engineer at Peutz since 2021. His research focuses on Fire behavior in building materials (sandwich panels, insulation) Computational Fluid Dynamics (CFD) for fire-structure interactions Pyrolysis modeling Mass loss and flammability in pre-flashover fires Fire resistance testing Scale modeling His work spans structural engineering, materials science, and fire safety standards. Van Herpen initiated the post-graduate course Fire Safety Engineering & Management (2004–present) at the Dutch Fire Service Academy. Scientific recognition includes Fellow of the Institution of Fire Engineers (2011) 70+ Scopus citations Recent media engagements address rising residential fire rates in the Netherlands (2023).

• Robotic Fabrication
• Timber Construction
• Computational Design
• +۳ مورد دیگر

Jens Pedersen is an Assistant Professor at the Aarhus School of Architecture , affiliated with the Research Laboratory 2: Technology, Building Cultures and Settlement . His work focuses on robotic fabrication, timber construction, and computational design. Education : Master of Architecture (2012-2014) MSc in Associative Hydrological Urban Metabolism (2010-2011) Research Interests : Dr. Pedersen explores the intersection of digital fabrication and sustainable construction. Key areas include parametric timber design, robotic automation in architecture, and computational material management. His work emphasizes practical applications of emerging technologies in built environments. Projects : ParaWood (2019-2023): A PhD project on on-site parametric timber construction Regenerative Construction (2025-2026): Investigating paradigm shifts in sustainable building practices Professional Activities : He has presented at international venues such as the Advances in Architectural Geometry conference (2018) and organized workshops on architectural geometry. Recent lectures include topics like 'Frameworks for On-site Robotic Timber Fabrication' (2022). Labs/Teams : Active contributor to the Research Laboratory 2, focusing on technology integration in building cultures and settlement patterns.

• Biomimetic Engineering
• Parametric Design
• Evolutionary Computation
• +۳ مورد دیگر

Achim Menges is a contemporary architect and Professor of Digital Design at The European Graduate School (EGS) and the founding director of the Institute for Computational Design at the University of Stuttgart. He also holds a visiting professorship at Harvard University's Graduate School of Design. His research integrates biomimetic engineering, parametric design, evolutionary computation, and computer-aided manufacturing through interdisciplinary collaboration with engineers, computer scientists, and biologists. Education: Began at Technical University of Darmstadt (Germany), graduated with honors from the Architectural Association School of Architecture in London (2002). Taught at AA School (2002-2012), Rice University (visiting professor), and Offenbach University of Art and Design (2005-2008). Currently at University of Stuttgart since 2012. Research focuses on biomimetic principles applied to architecture, such as humidity-responsive wood structures (e.g., FAZ Pavilion, 2010). Key themes include material computation, adaptive systems, and the synergy between biological processes and digital fabrication. His work emphasizes translating natural phenomena into functional architectural solutions without mechanical control systems. Scientific contributions include the FEIDAD Awards (2002, 2003), RIBA Tutor Prize (2004), Bentley Educator of the Year (2005), and ACADIA Award (2007). Over 10 major publications since 2004, including Material Computation: Higher Integration in Morphogenetic Design (2012). Labs/Teams: Leads the Institute for Computational Design (ICD), affiliated with Germany's Biomimetics Competence Network and Computer Science in Architecture Network. Active in international research evaluations and conference committees.

Guillaume Tochonمشاهده پروفایل

استادیار

• Mathematical Morphology
• Statistical Signal Processing
• Machine Learning
• +۴ مورد دیگر

Guillaume Tochon is an Assistant Professor at EPITA since 2016 and an Invited Researcher at the Institut de Mécanique Céleste et de Calcul des Éphémérides (IMCCE, Observatoire de Paris) since 2022. He holds a M.Sc. and Ph.D. in electrical engineering and signal/image processing from Grenoble Institute of Technology and Université Grenoble Alpes, with postdoctoral experience at Carnegie Institution for Science and UCLA. His research focuses on mathematical morphology, statistical signal processing, and machine/deep learning, applied to space imagery (e.g., astrometry) and satellite data analysis. He leads projects on morphological neural networks, Sentinel-2 time series dynamics, and meteor/satellite detection using 1-second exposure imagery. Education: M.Sc. in Electrical Engineering, Grenoble Institute of Technology (2012) Ph.D. in Signal and Image Processing, Université Grenoble Alpes (2015) Visiting Scholar, UCLA Department of Mathematics (2013) Research Interests: Combines mathematical morphology with machine learning to address challenges in remote sensing and space imagery. Key areas include hierarchical representations, noise analysis, and applications in astrometry and hyperspectral unmixing. Current projects involve neural Koopman operators for forecasting, Sentinel-2 time-series assimilation, and meteor detection in night-sky imagery. Teaching: At EPITA, he teaches Mathematics for Signal Processing, Data Compression, Image Processing, Convex Optimization, Machine Learning, and Constrained Optimization across undergraduate and graduate levels. Collaborations: Works with researchers at IMCCE (e.g., V. Lainey, J. Vaubaillon), IMT-Atlantique, and Grenoble-INP. Supervises PhD students in topics such as noise estimation, spectral dynamics, and Cassini image analysis. Labs/Teams: Active in EPITA Research Laboratory's Image Processing and Pattern Recognition team and IMCCE's PEGASE team.

• Virtual Reality
• Computer Vision
• Human-Computer Interaction
• +۴ مورد دیگر

Joe K. Kearney is a Professor in the Department of Computer Science at the University of Iowa and the University of Minnesota. His career spans over three decades, focusing on virtual reality, computer vision, and human-computer interaction research. Key affiliations: University of Iowa (Iowa City, IA, USA), University of Minnesota (Minneapolis, MN, USA) Research domains: Virtual environments, perception-action coupling, motion capture systems, pedestrian behavior simulation Research trends show sustained contributions to immersive visualization , autonomous navigation , and human factors in virtual reality . His 2014-2025 work explores AR-based pedestrian safety systems, while earlier studies (1986-2006) established foundational frameworks for virtual environment simulation and optical flow analysis. Long-term collaborations with Jodie M. Plumert (1986-2021), James F. Cremer (1986-2009), and Pooya Rahimian (2015-2017) demonstrate consistent team research in VR cognition and autonomous systems.

Dov Krugerمشاهده پروفایل

استاد آموزشی

• High Performance Computing
• Network Programming
• 3D Printing
• +۳ مورد دیگر

Dov Kruger is an Associate Teaching Professor in the Department of Electrical Engineering at Rutgers University. He holds a BE in Electrical Engineering, an MS in Computer Science, and a PhD in Ocean Engineering, all from Stevens Institute of Technology. Prior to Rutgers, he spent 10 years as a professor at Stevens. His research focuses on high-performance computing, network programming, 3D printing, and computing education. He explores re-engineering software for efficiency, distributed programming models, and innovations in data compression and secure networking. His work also encompasses underwater acoustics and sensor systems from earlier career phases. Key themes in his recent articles include real-time video processing, federated learning privacy, AI bias mitigation, and blockchain-based systems. His earlier contributions involved underwater robotics and environmental sensor networks in estuaries. Dr. Kruger seeks collaborators in FPGA, network programming, and 3D printing. He has no listed scientific awards but maintains active research in multidisciplinary computer science and engineering education.

Greg Maguireمشاهده پروفایل

استاد

• Animation
• Computer Graphics
• Machine Learning
• +۶ مورد دیگر

Professor Greg Maguire is a faculty member at Ulster University , holding the Professor of Animation role within the Belfast School of Art under the Faculty of Arts, Humanities & Social Sciences. His work bridges academia and industry, focusing on sustainable animation ecosystems through partnerships with organizations like Digital Northern Ireland 2020 , Northern Ireland Screen , and the Visual Effects Society (USA) . He pioneered the Toody Threedy animation cluster to connect students, researchers, and studios globally. Research Focus : Facial animation, AI-driven character modeling, and industry-academia collaboration Industry Leadership : R&D Supervisor at Lucasfilm Animation, Technical Animation Supervisor at Walt Disney Feature Animation His recent publications with colleagues explore deep learning for facial animation and spectral mesh processing , emphasizing technical rigor and artistic innovation. He contributed to Academy Award-nominated visual effects in Harry Potter and the Prisoner of Azkaban and Avatar , maintaining Ulster University's status as a hub for applied creative technology research.

• Control Systems
• Automation
• Robotic Control
• +۵ مورد دیگر

Dr. Keng Goh serves as a Lecturer at Edinburgh Napier University within the School of Computing Engineering and the Built Environment. He leads the MSc Renewable Engineering and MSc Automation and Control programs while actively contributing to the Centre for Artificial Intelligence and Robotic research group. His work spans multiple research centers including the Centre for Engineering and Mathematical Modelling and Engineering Research Group. Academically, Goh holds a B.Eng (First Class Honors) in Electrical and Electronic Engineering from the University of Leicester (1998), completed PhD research on Fault Diagnosis and Control of Diesel Generators at the same institution, and earned an MBA. His industry experience includes work at Hewlett Packard Ltd developing optical sensor test systems before transitioning to academia. His research focuses on nonlinear control systems, automation and robotic control, Industry 4.0 applications, electric vehicle battery thermal management, and sustainable energy systems. Current projects include the €2.8M European Commission-funded iMARS initiative developing multi-agent robotic systems for first responders, and Scottish-funded golf scorecard digitization. His work demonstrates strong industry engagement with practical applications in energy management and smart manufacturing. As evidenced by his extensive publication record in journals like Electronics and Applied Materials Today , Goh's research shows increasing emphasis on IoT integration, wireless power transfer for sensors, and thermal management of energy storage systems. Recent publications reveal growing collaboration with European institutions and industry partners. Chartered Engineer (CEng) Fellow of Higher Education Academy (FHEA) Member of Energy Institute (MEI) Member of Institution of Engineering and Technology (MIET) Peer Reviewer for MoHERI Research Grants Journal reviewer for IET Renewable Power Generation and Journal of Automobile Engineering Goh supervises numerous PhD candidates across diverse energy and engineering topics including smart manufacturing, photovoltaic systems, battery thermal management, and renewable air-conditioning. His research group collaborates with industry on practical implementations of sustainable technologies, particularly focusing on resource efficiency and climate change mitigation through engineering solutions. Current laboratory work emphasizes sensor networks for battery monitoring and optimization of multi-energy residential systems.

• Quantile Regression
• Statistical Inference
• Biostatistics
• +۴ مورد دیگر

Mercedes Conde Amboage is a Researcher at the University of Santiago de Compostela's Faculty of Mathematics, affiliated with the Department of Statistics, Mathematical Analysis and Optimization. She holds a PhD in Statistics (2017) from the same institution, focusing on Statistical Inference in Quantile Regression Models , advised by Dr. Wenceslao González Manteiga and Dr. César Andrés Sánchez Sellero. Her research interests center on quantile regression methodologies, statistical inference, and their applications in biomedical and environmental data. She contributes to the Galician Mathematical Research and Technology Center (CITMAga) and collaborates with research groups like GRID-BDS (Biostatistics and Biomedical Data Science) and MODESTYA (Optimization and Statistical Models). Her work bridges theoretical statistics with practical applications in clinical trials, proteomics, and environmental monitoring. Recent publications focus on quantile regression innovations in censored data analysis, biomedical biomarker identification, and environmental toxicology. She develops statistical software tools like the 'BwQuant' R package and has contributed to meta-analyses in dentistry and oncology. Notable collaborations include work on medication-related osteonecrosis of the jaw, HER2-positive breast cancer responses, and systematic reviews of surgical techniques. Her methodological advancements address high-dimensional covariates and lack-of-fit testing in complex models.

Jagannatha Raoمشاهده پروفایل

دانشیار

• Mathematical Optimization Theory
• Parametric Nonlinear Programming
• Multilevel Optimization
• +۷ مورد دیگر

Dr. Jagannatha Rao is the Cullen Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Houston, College of Engineering. He also serves as the Senior Associate Dean for Undergraduate Programs and Distance Learning, demonstrating leadership in academic administration. His office is located in the Engineering Building 1, and he has been a core faculty member since 1990. Education: Ph.D. in Mechanical Engineering, University of Michigan, Ann Arbor (1989) B.Tech. in Mechanical Engineering, Indian Institute of Technology-Madras (1985) Dr. Rao's research focuses on mathematical optimization theory and algorithms , including parametric nonlinear programming, multilevel decomposition, duality principles, and game-theoretic modeling in engineering design. His work extends to the numerical optimization of mechanical systems, compliant mechanisms, and structural topology. He has developed theoretical frameworks for optimal decision-making under conflict and unified elastic/plastic structural analysis. His recent publications (2005–1997) reflect a sustained focus on duality-based modeling, topology optimization, and multidisciplinary design , particularly in aerospace and mechanical systems. Key themes include game-theoretic decision protocols, aggregation in modeling, and NAND/SAND logic in launch vehicle design. These works span journals like Engineering Optimization , International Journal for Numerical Methods in Engineering , and AIAA conferences, indicating strong disciplinary impact. Scientific Awards: No specific awards or honors are listed in the provided text. Dr. Rao has extensive experience in teaching and curriculum development, offering both undergraduate and graduate courses in mechanical design, dynamics, finite elements, and optimization. As Senior Associate Dean, he plays a significant role in shaping undergraduate education and online learning initiatives. His research collaborations include work with NASA Langley’s ICASE and industry partners like Sandvik Rock Tools. While no formal lab or team is mentioned, his long-standing research program suggests active supervision of graduate students and research projects.

Eric Millerمشاهده پروفایل

استاد

• Signal and Image Processing
• Tomographic Image Formation
• Inverse Problems
• +۴ مورد دیگر

Eric Miller is a Professor of Electrical and Computer Engineering at Tufts University's School of Engineering. He also holds adjunct professorships in Computer Science, Biomedical Engineering, and Mathematics. His academic roles include serving as Chair of the Electrical and Computer Engineering department and leading the Lab for Imaging Science Research (LaISR). Miller earned his SB, SM, and PhD in Electrical Engineering from MIT (1990–1994). His research focuses on signal and image processing, particularly inverse problems, tomographic imaging, and applications in medical imaging, environmental monitoring, and security screening. He has pioneered methods like the parametric level-sets (PaLEnTIR) for reconstruction and shape-based inversion algorithms. His work integrates physics-based modeling with computational techniques, addressing challenges in subsurface sensing, biomedical diagnostics, and materials science. Miller is a Fellow of IEEE and a member of honor societies like Tau Beta Pi and Phi Beta Kappa. Over 489 publications reflect his contributions to imaging science, with recent advancements in AI-driven pedestrian behavior analysis and X-ray anomaly detection.

• Agricultural Engineering
• Sensor Technology
• Computational Fluid Dynamics
• +۷ مورد دیگر

Qianying Yi is a Postdoctoral Scientist at the Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) in Germany since July 2019, with a focus on Sensor Technology and Modeling . Her academic journey includes a PhD in Engineering (2015-2018) and a Research Assistant role (2018-2019) at Aarhus University , Denmark, and a Master in Pharmaceutical Engineering (2012-2015) and Bachelor in Biological Engineering (2008-2012) in China. PhD in Engineering, Aarhus University, Denmark Master in Pharmaceutical Engineering, Sichuan University, China Bachelor in Biological Engineering, Shandong University of Science and Technology, China Her research spans two distinct domains: (1) Agricultural Engineering , where she specializes in designing natural ventilation systems for livestock buildings, modeling indoor climate and emissions , and optimizing airflow patterns using computational fluid dynamics (CFD) and wind tunnel experiments , and (2) Pharmaceutical Engineering , where her early work focused on virtual screening of enzyme inhibitors for drug discovery applications, particularly targeting NAMPT , EphB4 , and MEK1 . Recent publications highlight her expertise in agricultural ventilation systems , including machine learning-based modeling , CFD simulations for multi-floor pig buildings, and pollutant dispersion mitigation . Earlier works emphasize computational drug discovery through pharmacophore modeling and molecular dynamics. While no explicit awards are listed, her career trajectory reflects interdisciplinary innovation across engineering and bioeconomy sectors.

Jenny Sabinمشاهده پروفایل

استاد

• Computational Design
• Bioinspired Design
• Adaptive Architecture
• +۵ مورد دیگر

Jenny E. Sabin is the Arthur L. and Isabel B. Wiesenberger Professor in Architecture and Chair of the Department of Design Tech at Cornell University's College of Architecture, Art and Planning. She directs the Sabin Lab at Cornell AAP, focusing on trans-disciplinary research in computational design, digital fabrication, and bioinspired systems. Sabin earned her M.Arch from the University of Pennsylvania and a BFA in ceramics and interdisciplinary visual art from the University of Washington. Her research explores intersections of architecture and science, specializing in adaptive materials, responsive environments, robotic fabrication, and sustainable design. Key research themes include bioinspired design strategies, material computation, and ecological building systems like the NSF-funded HelioSkin photovoltaic system. Her work translates biological principles from cell biology and mathematics into architectural applications. Sabin's publications demonstrate a consistent focus on interdisciplinary approaches spanning architecture, biology, and computational design. Her 2017 co-authored book LabStudio established frameworks for biology-architecture collaboration, while her articles investigate material innovation and design methodologies at multiple scales. Pew Fellowship in the Arts (2010) MoMA PS1 Young Architects Program Winner (2017) Architectural Record’s Innovator Award (2016) NSF EFRI ODISSEI Grant (2013-18) NSF EFRI-SEED Grant (2010-14) She leads multiple NSF-funded projects including 'Energy Minimization via Multi-Scalar Architectures' and directs the Sabin Lab's research in computational design. Her studio has executed installations for Nike, Cooper Hewitt Museum, and Centre Pompidou, while her 'eSkin' project develops adaptive building systems for energy efficiency.

Shermin Sherkatمشاهده پروفایل

پژوهشگر

• Computational Design
• Construction Automation
• Artificial Intelligence
• +۱ مورد دیگر

Shermin Sherkat is a doctoral researcher and research associate at the Institute for Computational Design and Construction (ICD) within the Cluster of Excellence IntCDC at the University of Stuttgart. Holding a Master of Science in Digital Technology in Architecture from the University of Tehran, her work focuses on integrating computational design with artificial intelligence applications in construction and fabrication. Her research explores classical Automated Task Planning (ATP) techniques using Planning Domain Definition Language (PDDL) to optimize robotic assembly processes. Current projects involve modeling fabrication domains for pick-and-place operations with multiple end-effectors, addressing challenges in 3D geometry representation and multi-object stacking limitations within classical planning frameworks. Recent publications examine the application of symbolic AI in construction automation, including systematic reviews of ATP methods and case studies on the BUGA Wood Pavilion's cassette fabrication. She contributes to advancing AI-driven task planning while identifying constraints in numerical tracking and geometric grouping within deterministic environments.

• Statistical Methodology
• Public Health
• Biomedical Sciences
• +۷ مورد دیگر

Minggen Lu is a Professor in the Environmental Sciences & Health at the University of Nevada, Reno , where he serves as Graduate Director of Health Analytics and Biostatistics. His research bridges statistical methodology and public health/biomedical applications, with a focus on semiparametric regression, panel count data, and survival analysis. Education: Ph.D. in Biostatistics (University of Iowa), Ph.D. in Mathematics (Northeastern University) Lu’s work integrates statistical innovation with collaborations in clinician medicine, nursing, opioid overdose prevention, and adolescent health. Recent publications highlight applications in HPV vaccination , ACEs (Adverse Childhood Experiences) , HIV interventions , and healthcare disparities . His methodological contributions include penalized splines and quasi-likelihood estimation for complex data structures. Article trends reflect dual expertise in biostatistical methods (interval-censored models, zero-inflated regression) and applied public health research (HIV prevention, cancer screening, youth assets). Collaborative projects often address cultural barriers in healthcare access for Chinese and Latino populations. While no explicit scientific awards are listed, his extensive co-authorship network indicates active interdisciplinary collaboration . Affiliations span health informatics , emergency medicine , and epidemiology . Recent work examines COVID-19 hospitalization risks and opioid overdose interventions in Nevada’s emergency departments. Lu’s teams include researchers in biostatistics , public health , and clinical medicine , particularly in studies involving longitudinal cohort designs and health behavior modeling . His Google Scholar profile confirms ongoing contributions to statistical literature and health sciences.