جست‌وجوی استاد و پژوهشگر

• Sustainable Architecture
• Thermal Comfort
• Building Energy Efficiency
• +۵ مورد دیگر

Dr. Timothy O. Adekunle is an Associate Professor at the University of Utah School of Architecture , where he serves as Interim Chair since 2023. He holds degrees including a Ph.D. in Architecture from the University of Kent, UK, and professional architecture degrees from Nottingham and [B.Arch institution]. A Fellow of the UK Higher Education Academy and member of AIA Utah Board, his work focuses on sustainable building practices and thermal comfort analysis. Ph.D. in Architecture, University of Kent M.Arch, University of Nottingham PGCHE, University of Kent His research interests span thermal comfort in historic and modern timber buildings, building energy efficiency , and urban environmental physics , with a particular focus on climate adaptation in diverse building typologies. Recent publications explore energy demands in CLT buildings , urban traffic CO2 impacts in Jakarta , and gender variations in thermal perception . His work has been recognized with multiple Outstanding Reviewer Awards from journals like Automation in Construction and Energy and Buildings . As a educator , he leads graduate architecture programs and teaches courses in sustainable design , building technology , and energy efficiency . His professional activities include leadership roles in AIA Utah and editorial board service. Current research grants support campus sustainability initiatives like CLT building evaluation and passive design strategies.

• Outdoor Sound Propagation
• Community Noise
• Urban Acoustics
• +۵ مورد دیگر

Jens Forssén is an Assistant Professor in the Department of Technical Acoustics , Vibroacoustics research group at Chalmers University of Technology . His work focuses on outdoor sound propagation , community noise , and urban acoustics , with a particular emphasis on the influence of meteorology , terrain , and soil properties on noise levels. Research Interests: Outdoor acoustics, urban soundscapes, road and train traffic noise, wind turbine noise, noise barriers, auralization techniques, and health impacts of environmental noise. Recent Trends: Analysis of low-frequency noise in urban environments, 3D noise mapping , digital twinning for urban design, and sonic crystal applications in noise reduction. Scientific Contributions: Publications on noise propagation models , auralization methods , traffic noise assessment , and health impact studies related to urban sound environments. Labs & Collaborations: Collaborates with the LISTEN project , SONORUS project , and HOSANNA project to develop urban noise mitigation strategies. His work includes partnerships with researchers like Wolfgang Kropp , Leon Müller , and Maarten Hornikx .

Lauren Sullivanمشاهده پروفایل

استادیار

• Plant Ecology
• Community Ecology
• Movement Ecology
• +۵ مورد دیگر

Lauren Sullivan is an Assistant Professor at Michigan State University’s Kellogg Biological Station, Department of Plant Biology, and Ecology, Evolution & Behavior Program. She earned her Ph.D. from Iowa State University and specializes in plant population/community ecology, movement ecology, species invasions, and conservation/restoration ecology. Her research combines field experiments and theoretical models to understand how global change drivers (habitat fragmentation, nutrient loading, herbivore shifts) affect plant dispersal and ecosystem outcomes. Her lab focuses on the interplay between seed dispersal, nutrient enrichment, and herbivory in shaping grassland biodiversity. Recent work explores wind seed dispersal mechanics, fire impacts on Ozark woodlands, and climate-dispersal interactions in Geum triflorum . Her team emphasizes inclusivity, antiracist practices, and mental health support for lab members. Lauren’s publications (2025–2018) span seed bank limitations in prairie restoration, soil microbial responses to nitrogen, forb diversity conservation, and modeling frameworks for dispersal and productivity. Key themes include global change impacts, ecological modeling, and sustainable restoration strategies. She has mentored students like Laís, Ale, and Kate, while advocating for equity in STEM through lab initiatives. Scientific contributions include advancements in understanding biodiversity-productivity relationships, herbivore-assisted reinvasions, and ethical specimen collection. Her work often bridges theoretical and applied ecology, with applications in conservation policy and ecosystem management. Lab updates highlight her mentorship of graduate students and ongoing efforts to foster diversity in plant ecology, aligning with her commitment to creating inclusive scientific environments.

Amelia Carolina Sparavignaمشاهده پروفایل

استادیار

• Image Processing
• Liquid Crystals
• Solid State Physics
• +۱۱ مورد دیگر

Amelia Carolina Sparavigna is a Tenured Assistant Professor at the Department of Applied Science and Technology (DISAT), Politecnico di Torino . Her research spans image processing , liquid crystal physics , and thermal conductivity in solids, with interdisciplinary applications in archaeology , cultural heritage protection , and environmental studies . She leads the Image Processing for Physics and Environmental Studies research unit, applying fractional calculus and variational methods to satellite imagery analysis. Research Themes : Mesophase transitions in liquid crystals, entropy-based image analysis, thermal modeling for energy/environmental applications (phase change materials, solar radiation simulation), and satellite archaeology (geoglyphs, desert kites, ancient settlements). Academic Contributions : Over 15 years of publications on thermal conductivity of diamond, nematic-smectic phase transitions, and electromagnetic shielding textiles. Recent work focuses on κ-statistics for epidemiology and entropy in image analysis. Labs & Collaborations : Member of the Institute of Fundamental Physics and Materials for Nanotechnology and Generalized Statistical Mechanics of Complex Systems research group at DISAT. Teaching : Delivers Fisica II (Physics II) for Computer Engineering at Politecnico di Torino.

• Business Model Innovation
• Digital Platforms
• New Product Marketing
• +۳ مورد دیگر

Xiaohui Shi is a Senior Lecturer at the Business School, University of Aberdeen , with previous roles at the University of Kent and University of Portsmouth. He holds a PhD in Management from the University of York and focuses on business model innovation, digital platforms, and new product marketing. Research Interests include: Business Model Innovation Digital Platforms New Product Marketing Diffusion of Innovation Open Innovation Global Value Chains Teaching encompasses courses on: New Product and Service Development Business Model Innovation New Venture Creation Publications span 2014–2025, covering diffusion modeling, platform development, and sustainable commercialization strategies in digital healthcare.

Xiaochun Heمشاهده پروفایل

استاد

• High Energy Physics
• Nuclear Physics
• Cosmic Ray Studies
• +۳ مورد دیگر

Xiaochun He is a Professor in the Department of Computer Science at Georgia State University, affiliated with the Nuclear Physics Group. Their research focuses on high energy nuclear physics, cosmic ray studies, and detector development for experiments like the Electron-Ion Collider (EIC), particularly through the ECCE detector project. Recent work includes analyzing space weather effects on muon flux, jet substructure in heavy ion collisions, and soil radon gas diffusion validation. Key contributions involve advancing detector technologies (e.g., modular RICH detectors), simulating cosmic ray distributions, and developing frameworks for radiation data analysis. They hold the position at SA 402 with contact at xhe@gsu.edu and are actively involved in global collaborations for space and particle physics research. Research interests integrate computational methods with experimental physics, addressing topics like Bose-Einstein correlations, direct photon measurements, and machine learning applications in data discovery. Ongoing projects include optimizing EIC detector designs and studying gluon spin-momentum correlations in transversely polarized protons.

• 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.

• Mechanical Engineering
• Machining Optimization
• Surface Engineering
• +۳ مورد دیگر

Andrzej Matras is an Assistant Professor at the Department of Production Engineering, Faculty of Mechanical Engineering, Jagiellonian University. He holds a PhD and BEng in Mechanical Engineering, awarded in 2010. His research focuses on machining optimization, surface engineering, and advanced manufacturing processes, particularly in difficult-to-cut materials like Inconel and titanium alloys. He has published 46 peer-reviewed articles and supervised one promoted thesis. Education: PhD in Mechanical Engineering (2010) BEng in Mechanical Engineering Research Interests: Specializes in CNC machining strategies, tool material selection (PCD/CBN), simulation-driven process optimization, and surface integrity analysis. His work addresses challenges in precision machining of aerospace components and complex geometries. Publications Trends: His recent work emphasizes cutting parameter optimization (e.g., Inconel 718 turning), material model validation in FEA, and laser cutting surface analysis. Key themes include minimizing deformation in thin-walled parts and improving tool life in hard milling operations. Achievements: Holds an h-index of 9 (Web of Science) and 8 (Scopus), with a total citations score of 1,560. His research contributes to advancing manufacturing efficiency in high-precision industries. Advising & Grants: Supervised 1 promoted thesis without specific grant details mentioned. His work integrates CAD/CAM systems for process automation and error compensation in manufacturing.

Giovanni Albertiمشاهده پروفایل

استاد

• Partial Differential Equations
• Inverse Problems
• Applied Harmonic Analysis
• +۳ مورد دیگر

Giovanni Alberti is a Full Professor in Mathematical Analysis at the Department of Mathematics (DIMA) of the University of Genoa. He earned his D.Phil. at the University of Oxford and completed postdoctoral positions at École Normale Supérieure (Paris) and ETH Zurich. His research focuses on partial differential equations, applied harmonic analysis, inverse problems, and machine learning. University of Genoa MaLGa Center (Machine Learning Genoa) Mathematical Institute, Oxford Maths Department, ETH Zurich His work bridges mathematical analysis with computational methods, particularly in inverse problems , compressed sensing , and machine learning . He has developed algorithms for real-time geotechnical predictions, sparse optimization for scatterer localization, and continuous generative models. Recent publications emphasize physics-data-driven integration and low-dimensional manifolds. He received the Gioacchino Iapichino Prize (2017), Eurasian Association on Inverse Problems Young Scientist Award (2018), and an ERC Starting Grant (2021). He serves on editorial boards for journals including Inverse Problems and SIAM Journal on Imaging Sciences.

Jennifer McConnellمشاهده پروفایل

استاد

• Bridge Engineering
• Steel Structure Behavior
• Aging Infrastructure
• +۳ مورد دیگر

Jennifer McConnell is a Professor at the University of Delaware, specializing in bridge engineering, steel structure behavior, and sustainable infrastructure. She holds a Ph.D., Master's, and Bachelor's degrees from West Virginia University. Her research focuses on non-linear behavior of steel structures, aging infrastructure resilience, and innovative materials for infrastructure longevity. Her work integrates advanced technologies like carbon nanotube sensors and composite materials for structural health monitoring and repair. Key areas include fatigue analysis of skewed steel girder bridges, lifecycle assessment of steel bridges, and lean engineering applications in bridge inspection. She emphasizes data-driven approaches for infrastructure performance evaluation and sustainable construction practices. McConnell’s publications highlight interdisciplinary innovations, such as integrating wireless sensor networks for steel reuse potential and co-digestion systems for waste management. Her research contributes to safer, more durable, and environmentally conscious infrastructure solutions.

• Data Science
• Machine Learning
• Energy and Sustainability
• +۳ مورد دیگر

Dr. Lin Zheng is a Research Fellow at University College London's Bartlett School of Environment, Energy & Resources, affiliated with the Energy Institute and Smart Energy Research Group (SERL). Her work focuses on applying data science and machine learning to address energy and sustainability challenges in buildings. She holds expertise in smart meter data analysis, life cycle assessment, and energy poverty research. Research interests include: Data-driven approaches for building energy conservation Thermal performance of renewable energy systems Phase change materials in energy storage solutions Machine learning applications in carbon footprint prediction Her recent work highlights trends in: Quantitative analysis of building lifecycle emissions Regional variations in energy consumption patterns Integration of renewable energy systems with smart materials Dr. Zheng is available for consultancy and journal reviewing, and communicates in English and Mandarin. Current affiliations include: Smart Energy Research Group (SERL) University College London Energy Institute

Hao Chengمشاهده پروفایل

استادیار

• Statistical Genetics
• Computational Genomics
• Animal Breeding
• +۳ مورد دیگر

Hao Cheng is an Assistant Professor in the Department of Animal Science at the University of California, Davis. His research focuses on developing statistical methods, computational algorithms, and software tools for quantitative and statistical genetics, particularly in the context of genomic prediction, genome-wide association studies, and functional genomics. He is affiliated with the Graduate Groups in Animal Biology, Biostatistics, and Integrative Genetics and Genomics. Dr. Cheng’s work emphasizes cross-disciplinary approaches, combining genetics, computer science, and animal science to address challenges in precision breeding, disease resistance, and trait improvement. His lab explores applications in diverse species including pigs, poultry, rainbow trout, and plants, with recent projects involving AI-driven phenotyping and secure genomic data collaboration frameworks. His research has produced tools like VTag for automated video-based phenotyping and XSim for simulation of breeding programs. His publications reflect a focus on methodological advancements in genomic prediction (e.g., MegaLMM, JWAS software), functional conservation between species (human-pig comparisons), and integrative approaches using multi-omics data. He also investigates practical applications such as improving nitrogen-use efficiency in maize and enhancing disease resilience in aquaculture species. While no specific awards are cited in the provided materials, his contributions to genomic methodology and computational biology indicate significant scholarly impact. His advising and grant activities are not detailed here, though his research program likely involves graduate students in genetics, biostatistics, and computational biology. Dr. Cheng’s laboratory is located in 2239 Meyer Hall, UC Davis, and maintains active collaborations across academia and industry to advance translational genetics in agriculture and animal health.

Valeria Cascioneمشاهده پروفایل

مدرس

• Building Physics
• Moisture Buffering
• Indoor Air Quality
• +۵ مورد دیگر

Valeria Cascione is a Lecturer in Regenerative Design at the Department of Architecture & Civil Engineering, University of Bath, with affiliations to the Centre for Climate Adaptation & Environment Research (CAER), Centre for Bioengineering & Biomedical Technologies (CBio), Institute of Sustainability and Climate Change, and Centre for Regenerative Design & Engineering for a Net Positive World (RENEW). Her research focuses on sustainable building materials and indoor environmental quality. Education: Civil Engineering, Doctor of Philosophy (PhD), University of Bath, Award Date: 31 Mar 2021 Building Engineering and Architecture, Master in Science (MSc), Politecnico di Bari, Award Date: 15 Dec 2016 Valeria Cascione's research centers on building physics with emphasis on moisture dynamics and indoor air quality. She investigates innovative sustainable materials—particularly bio-based construction materials—to enhance hygrothermal performance and occupant health, spanning material development to life cycle assessment while addressing sustainable building design and circular economy challenges. Analysis of her 15 most recent publications (2020-2025) reveals a dominant focus on bio-based construction materials and environmental impact assessment. Over 80% of her work applies life cycle assessment (LCA) to evaluate carbon footprints of insulation and wall systems, while moisture buffering research constitutes 40% of output, linking hygrothermal properties to indoor air quality. Her studies increasingly integrate circular economy principles and address scalability barriers in real-world construction, with notable emphasis on dynamic LCA methodologies and regenerative design frameworks. Valeria Cascione has not been documented as receiving any major scientific awards or fellowships. She actively supervises doctoral students in hygrothermal performance, indoor air quality, and life cycle assessment, leading externally funded projects including: Principal Investigator (PI) : Reimagining Occupant-centred, Versatile and Efficient Retrofit (The British Academy, 2024); Returning Parents Support Grant (2023) Co-Investigator (CoI) : Innovative low-cost recyclable building materials in Egyptian local construction (The British Council, 2024-2025); InNovative Bio&geo-soUrced project (Innovate UK, 2023-2027) Valeria Cascione is a core member of the Centre for Regenerative Design & Engineering for a Net Positive World (RENEW) and Centre for Climate Adaptation & Environment Research (CAER), while serving as advisor to Global Open Air Quality Standards (GO AQS) and participating in the GW4 Air Network for collaborative air quality research.

• human-centered ai
• psychology of technology
• machine learning
• +۵ مورد دیگر

Chao Zhang is an Assistant Professor in Human-Centered AI at the Human-Technology Interaction group, Eindhoven University of Technology. His research bridges psychology and technology through data-driven methods and psychological theories, focusing on behavior change, AI-human dynamics, and trustworthy systems. MSc in Human-Technology Interaction (TU/e) PhD in Intelligent Systems (TU/e, 2019) Postdoc at Utrecht University Research interests span Human-Centered AI , Explainable AI , and Behavioral Data Science . Key contributions include: Integrating psychological principles with machine learning Modeling longitudinal behavioral data Developing interpretable AI systems for lifestyle interventions Investigating social characteristics in AI-driven environments Current work includes the ENFIELD project on Trustworthy Green AI. Scientific contributions appear in CHI Conference , arXiv , and International Journal of Social Robotics . Recognized with a TU/e PhD Thesis Award nomination in 2021.

• Biomedical Engineering
• Fetal Monitoring
• Signal Processing
• +۴ مورد دیگر

SG Oei is a Professor at Eindhoven University of Technology in the Department of Electrical Engineering, affiliated with the Eindhoven MedTech Innovation Center and Biomedical Diagnostics Lab. His research focuses on developing novel technologies for maternal-fetal health monitoring, particularly in obstetric care settings. Research interests center on: Advanced fetal monitoring techniques including electrohysterography and non-invasive fetal electrocardiography Biomedical signal processing applications in perinatal care Development of AI-driven diagnostic tools for fetal distress detection Simulation-based obstetric training systems for low-resource settings Publication analysis reveals consistent focus on improving fetal monitoring through: Novel signal processing algorithms for cardiotocography interpretation Validation of non-invasive electrophysiological monitoring techniques Application of speckle tracking echocardiography in fetal assessment AI-powered diagnostic systems for high-risk pregnancies Extensive student supervision includes 28 doctoral candidates since 2010, with dissertations covering fetal cardiac function monitoring, electrohysterography applications, and obstetric simulation training. Research is conducted through the Biomedical Diagnostics Lab and Center for Care & Cure Technology Eindhoven.