جستجوی استاد راهنمای دانشگاهی

Jana Eichelمشاهده پروفایل

استادیار

• Biogeomorphology
• Climate Change Impacts on Landscapes
• Vegetation-Grounded Feedbacks
• +۳ مورد دیگر

Dr. Jana Eichel is an Assistant Professor in Biogeomorphology at the Department of Physical Geography, Utrecht University. She specializes in understanding feedbacks between Earth surface processes and plant dynamics, particularly in mountain and polar regions undergoing rapid climate change. Her work integrates field observations, remote sensing, and modeling to study landscape evolution across scales. Education: PhD in Geomorphology (2016), University of Bonn MSc in Geography (2011), University of Bonn/Aberdeen Research Interests: Her research focuses on biogeomorphic feedbacks in alpine and polar environments, including vegetation-geomorphic interactions, solifluction dynamics, and climate change impacts. She combines UAV imagery, machine learning, and experimental methods to analyze landscape resilience and ecosystem adaptation. Grants & Projects: Lead of NWO-Veni project “Go or grow?” (2022–2026) German Research Foundation (DFG) project on Chilean biogeomorphic feedbacks (2019–2023) Awards: EGU Geomorphology Division Early Career Award (2024) German Society for Geomorphology PostDoc Award (2023) Hanna Bremer Award (2017) Labs/Teams: She leads the Mountain Biogeomorphology Lab at Utrecht University, collaborating with global institutions on projects combining fieldwork and advanced geospatial technologies.

• Condensed Matter Physics
• Materials Science
• Quantum Phenomena
• +۳ مورد دیگر

Maciej Dendzik is a Researcher at KTH Royal Institute of Technology, affiliated with the Department of Light and Materials Physics within the School of Engineering Sciences. His research focuses on advanced experimental techniques in condensed matter physics, including angle-resolved photoemission spectroscopy (ARPES), ultrafast dynamics, and the study of topological materials, 2D systems, and quantum phenomena. He has contributed to understanding electron-phonon interactions in superconductors, the emergence of Weyl fermions in magnetic materials, and energy transfer mechanisms in nanostructured systems. His work integrates cutting-edge spectroscopic methods with computational tools, such as machine learning for band mapping, to explore electronic structures and dynamics in novel materials. Key areas of investigation include charge density waves in kagome superconductors, ultrafast carrier dynamics in topological insulators like bismuthene, and the development of advanced light sources for time-resolved studies. While no specific awards or grants are explicitly listed, his extensive publication record reflects a commitment to advancing experimental methodologies and unraveling fundamental material properties at the nanoscale. He teaches the Degree Project in Engineering Physics at the undergraduate level, contributing to KTH's educational mission.

• Teaching Chinese as a Second Language
• Language Teaching Materials Development
• Online Language Education
• +۲ مورد دیگر

Chao Li is a Lecturer of Chinese at the Georgia Institute of Technology's School of Modern Languages, part of the Ivan Allen College of Liberal Arts. He has been with Georgia Tech since 2001, focusing on teaching Chinese language at all proficiency levels and co-directing the Chinese Language for Business and Technology (LBAT) Program since 2006. His expertise includes developing online Chinese language courses, creating multimedia content, and compiling grammatical notes for effective language learning materials. Chao Li holds a Master of Arts in International Relations from Beijing Institute of Foreign Affairs and a Bachelor of Arts in Economics and Chinese from Yunnan University, China. He is a key figure in advancing online Chinese language education at Georgia Tech, emphasizing the integration of technology into language pedagogy. His work bridges language instruction with business and technology contexts, reflecting his commitment to practical, industry-relevant language training. His professional contributions include pioneering efforts in online course development, particularly in designing interactive and adaptive learning environments. While no formal awards are listed, his role in shaping Georgia Tech's Chinese language program highlights his significant impact on language education innovation. Chao Li’s teaching philosophy centers on student engagement through culturally immersive and technologically enhanced methodologies.

Christian Schwabمشاهده پروفایل

دانشیار

• Astrophysics
• Exoplanet Detection
• Spectroscopy
• +۳ مورد دیگر

Christian Schwab is an Associate Professor at Macquarie University, affiliated with the School of Mathematical and Physical Sciences and the Astrophysics and Space Technologies Research Centre. His research focuses on exoplanet detection, spectroscopic techniques, and astrophotonics, particularly in developing high-precision instruments like spectrographs to identify Earth-like planets. He leads and collaborates on projects such as the NEID Earth Twin Survey and the MARVEL radial velocity facility. Key research interests include radial velocity methods, spectrograph calibration, and the study of planetary systems around low-mass stars. Schwab has contributed to over 200 publications, with recent work emphasizing exoplanet orbital dynamics, stellar parameter estimation, and instrument design. He received the Faculty of Science and Engineering Award for Excellence in Learning Innovation in 2021. His projects involve collaborations across institutions to advance exoplanet science, including work on the iLocater spectrograph and the Large Fiber Array Spectroscopic Telescope (LFAST). These efforts aim to improve precision in detecting small planets and understanding planetary formation mechanisms.

Thuy Doمشاهده پروفایل

استاد

• Bacteriology
• Microbial Culturing Methods
• Oral Biofilms
• +۶ مورد دیگر

Professor Thuy Do holds the position of Professor of Molecular Microbiology at the University of Leeds School of Dentistry. She specializes in bacteriology, oral biofilms, and microbiome analysis using advanced sequencing technologies. Her research focuses on understanding oral microbiome dysbiosis, host-microbiome interactions, and developing diagnostic tools for systemic diseases linked to oral health. Education: She earned a Licence es Sciences from the Université de Strasbourg (1998), followed by BSc and MSc degrees from Teesside University (1999–2000) and a PhD in Bioprocess Development from De Montfort University (2004). She held a Postdoctoral Research Associate position at King’s College London before joining Leeds in 2012 as a Lecturer in Microbiology. Research Interests: Prof. Do’s work investigates oral microbiota diversity, functional biology of biofilms, and applications of metagenomics/RNA-Seq. Key projects include studying rheumatoid arthritis links to oral dysbiosis, root caries mechanisms, and developing microbiome-based therapies. She also explores antimicrobial materials and regenerative endodontics. Editorial & Leadership: She serves as Associate Editor for multiple journals including Oral Diseases and Frontiers in Oral Health. She chairs IADR committees on new investigator awards and science communication. Her work bridges dental microbiology with systemic health, emphasizing interdisciplinary collaboration. Advising & Training: Supervises postgraduate students in microbiology and dentistry. Teaches Microbiology modules to dental undergraduates. Active in mentoring early-career researchers through editorial roles and conference initiatives.

Stepan Paulمشاهده پروفایل

دانشگاهی

• Mathematics Education
• Scholarship of Teaching and Learning
• 3D Modeling in Education
• +۵ مورد دیگر

Stepan Paul is an Associate Teaching Professor in the Department of Mathematics at North Carolina State University (NC State), where he has been since 2020. He holds a BS in Mathematics from Duke University (2007) and a PhD in Mathematics from the University of California, Santa Barbara (2013). His primary research focuses on the scholarship of teaching and learning (SoTL) in mathematics, particularly how spatial and visualization skills influence student success in calculus and the impact of 3D manipulatives in active learning environments. He is also deeply involved in mathematical illustration, designing physical and digital tools to enhance the understanding of advanced mathematical concepts, such as non-Euclidean geometry and differential geometry. Paul’s work includes collaborations on projects like Manipulative Calculus , which developed 3D models for multivariable calculus education, and the Flat Klein Bottle sculpture, a curved-crease origami piece displayed at the National Museum of Mathematics. He has published extensively on calculus pedagogy, resource utilization in teaching, and the application of 3D printing in education. His contributions to the Illustrating Mathematics program at ICERM (2019) further highlight his commitment to bridging mathematical research and educational outreach. Education: BS Mathematics, Duke University, 2007 PhD Mathematics, UC Santa Barbara, 2013 Key Projects: Non-Euclidean paper thermoforming for geometry education Desmos applets for calculus visualization Thingiverse 3D print designs (e.g., Sudanese Möbius Band, Siefert Surface) Awards/Grants: Funded by NSF Grant DMS-1439786 and Sloan Foundation (2019) His teaching and research emphasize innovative methods to make abstract mathematical concepts accessible, leveraging technology and hands-on tools to improve student engagement and achievement.

Peter Winterمشاهده پروفایل

پزشک-پژوهشگر

• Particle Physics
• Muon Physics
• Precision Measurements
• +۳ مورد دیگر

Peter Winter is a physicist in the High Energy Physics Division at Argonne National Laboratory, serving as Intensity Frontier Group Leader since 2019 and Co-Spokesperson for the Muon g-2 Collaboration since 2023. He earned a Dr. rer. nat. (2005) and Dipl. Phys. (2001) from the University of Bonn, Germany. Research Interests: Winter focuses on precision measurements in muon physics to test fundamental symmetries and the Standard Model. His work includes the Muon g-2 experiment, investigating anomalous magnetic moments, and developing advanced magnetometry techniques for particle physics applications. Scientific Awards: DOE Office of Science Early Career Research Award (2015) Günther-Leibfried Award (2001) Notable Contributions: Winter has led key advancements in magnetic field calibration for muon experiments, improved understanding of muon decay dynamics, and optimized detector systems for precision measurements.

• X-ray Astronomy
• Active Galactic Nuclei (AGN)
• Radiative Transfer
• +۲ مورد دیگر

Bert Vander Meulen is a Research Fellow at the European Space Agency (ESTEC), specializing in high-energy astrophysics. He focuses on Active Galactic Nuclei (AGNs) in X-rays, particularly the AGN torus and X-ray reprocessing in circumnuclear media. His work involves extending the 3D radiative transfer code SKIRT for X-ray applications and analyzing observational data from missions like XRISM, XMM-Newton, IXPE, NuSTAR, and Chandra. His research emphasizes complex AGN obscuration models and the application of SKIRT simulations to astrophysical phenomena. He collaborates on projects involving AGNs, X-ray binaries (XRBs), galaxies, and stars, with a strong emphasis on computational methods and space-based observatories. Key trends in his publications include advancements in X-ray radiative transfer, polarization modeling, and intrinsic line shape analysis for XRISM data. His work bridges theoretical simulations with observational X-ray astronomy, contributing to understanding AGN environments and galactic structures.

Julie Wallمشاهده پروفایل

استاد

• Artificial Intelligence
• Advanced Computing
• Deep Learning
• +۱۲ مورد دیگر

Professor Julie Wall is a faculty member at the University of West London, serving as Professor of AI and Advanced Computing in the School of Computing and Engineering. She is actively engaged in research, teaching, and professional service, including her role as an expert at the British Standards Institution (BSI) in the domain of artificial intelligence. Research Interests: Julie Wall's research is centered on the design and application of intelligent systems for processing and modeling temporal data, particularly in speech and language. She leverages neural network architectures—ranging from biologically inspired models to computationally efficient deep learning systems—to analyze diverse data types such as audio, video, images, tabular data, and 3D features. Her work extends to developing production-grade deep learning and natural language understanding systems for immersive environments like virtual and augmented reality. Publications and Research Trends: Her body of work, comprising over 50 high-quality papers and multiple patents, reflects a strong trajectory in AI systems that integrate multimodal data with temporal dynamics. The research spans core areas of machine learning, natural language processing, and applied AI, with increasing focus on real-world deployment, efficiency, and intelligent interaction in extended reality platforms. Scientific Awards: US Patent UK Patent Advising and Grants: Julie Wall supervises research students across disciplines including forensic science and artificial intelligence. She contributes extensively to academic programs, teaching courses such as BSc and MSc in Computer Science, Artificial Intelligence, Data Science, and specialized AI programs in cybercrime and criminal justice. While specific grant details are not listed, her patent holdings and publication volume suggest sustained research funding and project leadership. Labs and Teams: As a leading researcher in AI and advanced computing, she is likely involved in or leads research groups focused on intelligent systems, deep learning, and multimodal AI at the University of West London, though specific lab names are not mentioned in the text.

Hansung Kimمشاهده پروفایل

دانشیار

• 3D Computer Vision
• Artificial Intelligence
• Virtual Reality
• +۶ مورد دیگر

Dr. Hansung Kim is an Associate Professor in the School of Electronics & Computer Science at the University of Southampton . With over 100 peer-reviewed publications (60+ as first author), he specializes in 3D computer vision, audio-visual machine perception, and immersive virtual reality technologies. School: School of Electronics & Computer Science University: University of Southampton Email: H.Kim@soton.ac.uk Research Focus : Dr. Kim’s work bridges computer vision, machine learning, and audio signal processing to advance real-time immersive VR experiences. His research addresses challenges in joint audio-visual scene understanding, human pose estimation, and depth estimation using omnidirectional cameras. Key applications include entertainment, training, and media production. Scientific Recognition : Best Paper Award & Nomination (2013, 2019) 3rd Prize at AHSC Competition (2020) Teaching Roles : He supervises courses such as COMP6223 Computer Vision , COMP1201 Algorithmics , and COMP6200 MSc Project , emphasizing technical rigor and practical implementation in computer vision and algorithmic design.

Yu Yinمشاهده پروفایل

استادیار

• Computer Vision
• Generative Models
• 3D Modeling and Animation
• +۷ مورد دیگر

Yu Yin is an Assistant Professor in the Department of Computer and Data Sciences at Case Western Reserve University (CWRU), joined in Fall 2023. Previously, they earned a Ph.D. (2023) and M.S. (2018) in Computer Engineering and Electrical & Computer Engineering from Northeastern University, and a B.E. (2016) in Electrical and Information Engineering from Wuhan University of Technology. Their research focuses on visual synthesis, 3D modeling/animation, and applications like face restoration, deepfake detection, and generative models. They teach courses including Deep Generative Models (CSDS 570) and Computer Vision (CSDS 465). Key achievements include a 2024 Teaching Award, NeurIPS 2024 Oral paper, and organizing workshops like ICCV-AMFG 2023. Active in program committees for CVPR, NeurIPS, and ICLR. Over 20+ publications in top venues (CVPR, AAAI, ACM MM) and 2 patents. Open to advising motivated students in machine learning and computer vision.

• Wildlife Ecology
• Behavioral Ecology
• Conservation Biology
• +۳ مورد دیگر

Daniel Crawford is a Senior Research Associate at the Warnell School of Forestry and Natural Resources, University of Georgia. His work focuses on wildlife behavioral ecology, predator-prey dynamics, and the impacts of environmental disturbances such as hurricanes and human activity on animal populations. His research integrates advanced technologies like LiDAR and telemetry to model species distribution and movement patterns. Crawford’s studies emphasize understanding how ecological disturbances—both natural and anthropogenic—affect risk landscapes for prey species. He investigates behavioral adaptations in prey species like white-tailed deer, ocelots, and wild pigs, particularly in response to predation pressure and human interventions such as hunting and habitat management. His work often explores the balance between conservation goals and sustainable resource use, such as managing Florida panthers and their prey. His articles highlight trends in predator-prey interaction dynamics, the role of technology in ecological monitoring, and the cascading effects of extreme climatic events on wildlife behavior. Notable contributions include insights into human activity as a 'super predator' influencing prey behavior and the development of models to assess habitat partitioning using LiDAR-derived canopy metrics. Crawford collaborates on interdisciplinary projects addressing conservation challenges, though specific grants or labs are not detailed in the provided information. His research underscores the importance of integrating behavioral ecology with spatial and technological approaches to address modern conservation issues.

• Corrosion Engineering
• Additive Manufacturing
• Material Microstructure
• +۳ مورد دیگر

Reynier Inocente Revilla Castillo is a postdoctoral researcher in Sustainable Materials Engineering, specializing in corrosion mechanisms of additively manufactured materials. His work focuses on understanding microstructural effects on corrosion resistance, particularly in stainless steels and nickel-based alloys. He has contributed to projects such as EUOA2 (Open Corrosion Data for Additively Manufactured Alloys) and collaborated on AFM-based nanobiotechnology platforms (HERC52/OZR3564/OZR3587). His research integrates electrochemical analysis, microstructural characterization, and materials engineering to address challenges in corrosion mitigation and material durability. He has presented findings at international conferences, including discussions on lithium-ion battery characterization via Kelvin Probe Force Microscopy. Primary affiliations: Sustainable Materials Engineering Department Key technical areas: Pitting corrosion, passivity mechanisms, additive manufacturing repair, and microstructural analysis Recent studies investigate carbon variation effects in Alloy 718 and heat treatment impacts on 316L stainless steel. His work aligns with EU-funded initiatives promoting open corrosion data and durable materials innovation.

• Machine Learning
• Computational Neuroscience
• Data Science
• +۳ مورد دیگر

UnivProf. Dr. Fabian Sinz is a Professor at the Institute of Computer Science, University of Göttingen, heading the Machine Learning group. His research focuses on interdisciplinary applications of machine learning in computational neuroscience, data science, and neuroscience. He teaches courses such as Data Science I and leads seminars on Machine Learning and Computational Neuroscience. His work bridges theoretical machine learning with empirical neuroscience, particularly in modeling neural activity and connectomics. Research interests include neural population coding, generative models for neural data, and applying machine learning to understand brain function. Notable contributions involve developing methods like TRACE and NEURD for analyzing neural datasets and predicting visual cortex responses. Recent publications emphasize foundational models for neural activity prediction and cross-modal learning. Dr. Sinz collaborates on large-scale projects like the Dynamic Sensorium Competition, advancing reproducibility in predictive modeling of brain activity. He has advised on machine learning applications in health informatics and biomechanical reconstruction. His lab’s work frequently intersects with computer vision, computational biology, and neuroimaging technologies.

Stephen Wroeمشاهده پروفایل

استاد

• Palaeontology
• Biomechanics
• Evolutionary Biology
• +۷ مورد دیگر

Stephen Wroe is a Professor in Evolutionary Biology at the School of Environmental and Rural Science, Faculty of Science, Agriculture, Business and Law, University of New England (UNE), Australia. He is the Director of the Function, Evolution & Anatomy Research (FEAR) Lab, a multidisciplinary team collaborating with researchers from the University of Newcastle and University of New South Wales. His research integrates 3D imaging, finite element analysis, and biomechanics to explore evolutionary patterns in living and extinct animals. His primary research areas include: Palaeontology Physical Anthropology Biomechanics Cranial Mechanics Evolution of Carnivores and Marsupials 3D Modeling of Fossil and Extant Species Wroe’s recent research publications (2018–2021) reveal a strong trend in computational biomechanics and geometric morphometrics, applied to diverse taxa such as raptors, marsupials, primates, crocodiles, and early birds. His work frequently involves finite element analysis to simulate feeding behavior, cranial stress, and locomotion, contributing to understanding evolutionary adaptations. He has developed extensive 3D models from CT scans, enabling digital 'crash-testing' of skulls to assess functional performance. His scientific honors include: ARC Discovery Outstanding Researcher Award Fellow (2014–2016) ARC QEII Research Fellow at the University of New South Wales (2006–2010) U2000 Postdoctoral Fellow at the University of Sydney (2000–2005) Wroe has supervised over two dozen higher degree research students, serving as primary supervisor for 14 PhD and 3 Honours students, and co-supervisor for 10 PhDs. He has been awarded five major Australian Research Council grants, supporting his innovative research in evolutionary biomechanics. He also coordinates the course ZOOL100 at UNE and mentors students in palaeontology and zoology. He leads the FEAR Lab, which uses cutting-edge 3D modeling and biomechanical simulation to investigate functional anatomy across evolutionary time. The lab collaborates widely and encourages student-led projects on diverse taxa, provided CT scan data is available.