جست‌وجوی استاد و پژوهشگر

Sunil Kishore Chakrapaniمشاهده پروفایل

دانشیار

• Nonlinear Ultrasonics
• Nondestructive Evaluation
• Sensor Development
• +۴ مورد دیگر

Dr. Sunil Kishore Chakrapani is an Associate Professor in the Department of Electrical and Computer Engineering at Michigan State University (MSU), with a joint appointment in the Department of Mechanical Engineering. He holds a Ph.D. in Engineering Mechanics from Iowa State University and has over a decade of experience in Nondestructive Evaluation (NDE), working at institutions like the Center for NDE and Indian Institute of Technology Madras. Education: B.E., Mechanical Engineering, Anna University, Chennai, India M.S., Engineering Mechanics, Iowa State University Ph.D., Engineering Mechanics, Iowa State University Research Interests: Nonlinear ultrasonics and vibrations Nondestructive material characterization (e.g., composites, additively manufactured materials) Ultrasonic sensor development (air-coupled systems, structural health monitoring) Finite element modeling for composites and wave propagation Acoustic nonlinearity parameter inversion and dislocation dynamics Recent Article Trends: Focus on advanced NDE techniques for additive manufacturing (e.g., laser deposition of Inconel/IN718), microstructural variability analysis in steels (P91), and hybrid sensor systems for infrastructure monitoring. Key methodologies include nonlinear ultrasonics, coda wave analysis, and machine learning-augmented defect characterization. Awards: Research Excellence Award from Iowa State University (2014) Advising & Grants: Leads research projects in NDE-driven design and composite materials. Active in developing NDE standards for aerospace and energy infrastructure components. Collaborates with industry partners on sensor development and failure analysis. Labs/Teams: Oversees research groups focused on nonlinear ultrasonics and additive manufacturing NDE within MSU’s College of Engineering.

• Biophysics
• Biomechanics
• Computational Mechanics
• +۵ مورد دیگر

Jose Javier Muñoz is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament de Matemàtiques and the LACÀN research group. His work focuses on computational mechanics, biomechanics, and mechanobiology, with applications to tissue morphogenesis, wound healing, and cancer progression. He earned his PhD in Aeronautics from Imperial College London and holds degrees from UPC and École Centrale Paris. Research interests include vertex methods, finite element analysis, and inverse problems in biological systems. Recent studies explore optimal control of contractile elastic bodies, mechanical stimuli in tissue growth, and stress-dependent morphogenesis. Muñoz advises multiple PhD and master’s students and collaborates internationally on projects funded by agencies like the European Union. His contributions bridge computational methods with biological systems, emphasizing mechanical and numerical modeling.

Nicky Whiteمشاهده پروفایل

استاد

• Mantle Convection
• Geodynamics
• Tectonics
• +۷ مورد دیگر

Professor Nicky White is a leading academic in the Department of Earth Sciences at the University of Cambridge. His research focuses on mantle convection dynamics, geodynamics, and tectonics, with a particular emphasis on vertical motions and river drainage patterns linked to mantle processes. He investigates the North Atlantic Ocean's stratigraphic evolution influenced by Icelandic plume activity and analyzes Africa's geological features tied to convective patterns. His work integrates field data, stratigraphic analysis, and computational modeling, with commercial applications in hydrocarbon exploration. Affiliations: Academic Staff member at the Department of Earth Sciences, affiliated with Bullard Laboratories. Research Projects: Includes uplift/denudation modeling, river mouth sediment flux analysis, Iceland plume evolution, and mantle structure studies under the British Isles. Key methodologies involve joint inverse modeling, teleseismic receiver functions, and denudation rate measurements. He collaborates closely with the hydrocarbon industry to apply geological insights to resource exploration. Professor White is actively involved in supervising PhD students and holds the phone number +44 (0) 1223 337063 for professional inquiries.

Atif Abueidaمشاهده پروفایل

استاد

• Graph Theory
• Design Theory
• Combinatorics
• +۵ مورد دیگر

Atif Abueida is a Professor and Chair of the Department of Mathematics in the College of Arts and Sciences at the University of Dayton. He has been a full-time faculty member since 2000 and also contributes to the Premedical Programs by teaching relevant mathematics courses. His research focuses on discrete mathematics, particularly in Graph Theory , Design Theory , and Complex Analysis . He has made significant contributions to the study of graph decompositions, multidecompositions, cycle extendability, Hamiltonian cycles in chordal graphs, and equitable colorings in combinatorial designs. The recent publications, spanning from 2010 to 2025, highlight a sustained research trajectory in combinatorics and graph theory, with increasing focus on Johnson graphs, starlike trees, and structural properties of chordal and multipartite graphs. His work often involves deep combinatorial analysis and structural investigations, with applications in design theory and graph labeling. Dr. Abueida has delivered numerous invited and contributed talks at national conferences such as the Joint Mathematics Meetings and the Cumberland Conference, demonstrating active engagement with the mathematical community. Though specific student names are not listed, his role as a professor and advisor is evident from his long tenure and research output. Ph.D. in Mathematics, Auburn University, 2000 M.S. in Mathematics, East Tennessee State University (ETSU), 1996 B.Sc. in Mathematics, UAE University, 1987 He previously worked as a high school mathematics teacher for eight years before pursuing his graduate studies. His scholarly service includes reviewing and collaborative research, as seen in co-authored publications with colleagues across institutions.

Herbie Leeمشاهده پروفایل

استاد

• Bayesian statistics
• Computer models
• Spatial inverse problems
• +۷ مورد دیگر

Herbie Lee is a Professor in the Department of Statistics at the Jack Baskin School of Engineering, University of California, Santa Cruz. He also serves as the Interim Dean of Social Sciences. His faculty office is located in 537A Baskin Engineering, and he can be reached at 831-459-1655 (though email is preferred). Lee completed his educational journey with a strong foundation in mathematics and statistics: B.S. in Mathematics from Yale University with a specialty in statistics Ph.D. in Statistics from Carnegie Mellon University (1998), advised by Larry Wasserman Post-doctoral work at Duke University's ISDS department Professor Lee's research focuses on Bayesian statistics, particularly in the areas of computer models, spatial inverse problems, simulator emulation, adaptive experimental design, and optimization. His work bridges theoretical statistics with practical applications across diverse domains including cosmology (dark energy modeling), aircraft damage detection, electronic health records analysis, and environmental monitoring. He has made significant contributions to the understanding of neural networks within a statistical framework. An analysis of his recent publications reveals a strong emphasis on Gaussian process modeling, Bayesian optimization, and nonstationary spatial statistics. His work increasingly addresses complex real-world problems requiring sophisticated statistical approaches for mixed data types, constrained optimization, and real-time decision making. The interdisciplinary nature of his research is evident in collaborations with institutions like Lawrence Livermore National Laboratory and the Naval Postgraduate School. Among his notable achievements: Supervised PhD student Bobby Gramacy won the prestigious Savage Award Authored two books on Bayesian optimization and multiscale modeling Published over 50 peer-reviewed articles in top statistics and machine learning journals Professor Lee has supervised numerous graduate students, with his most recent PhD student graduating in 2024. His research has been supported by various grants, though specific funding sources aren't detailed in the provided text. His teaching portfolio includes courses on Bayesian statistics, design and analysis of computer simulation experiments, and statistical methods for biological, environmental, and health sciences. He is actively involved in several professional statistical societies including the International Society for Bayesian Analysis (ISBA), American Statistical Association (ASA), and Institute of Mathematical Statistics (IMS).

• Ultrahigh Field MRI
• RF Engineering
• Antenna Design
• +۳ مورد دیگر

Alexander JE Raaijmakers is an Assistant Professor with a joint appointment at Eindhoven University of Technology (Department of Biomedical Engineering, Medical Image Analysis group) and University Medical Center Utrecht (7 Tesla Research group, Radiology Department). His research focuses on RF engineering for ultrahigh field MRI, including antenna design, body imaging, and RF safety protocols. He leads multiple projects involving 5 PhD students and 1 postdoc. Education: MSc in Applied Physics, University of Groningen (2004) PhD in Radiotherapy Physics, University Medical Center Utrecht (2008) Research Focus: His work bridges electromagnetic physics with clinical MRI applications, developing hardware/software solutions for ultrahigh field systems. Key innovations include dipole antenna arrays for MRI and safety frameworks for medical implants. Recent work integrates deep learning for image correction. Awards: Casimir Grant (2008-2010) for RF coil development at Philips Medical Systems Leadership: Directs the 7T Research Group at UMC Utrecht and collaborates on MRI education at TU/e. His team focuses on clinical translation for cardiac, prostate, and abdominal imaging.

• Mathematical Biology
• Mathematical Cell Biology
• Developmental Biology
• +۷ مورد دیگر

Maria-Veronica Ciocanel is an Assistant Professor of Mathematics (Primary) and Biology (Joint) at Duke University's Trinity College of Arts & Sciences, where she has held appointments since 2020. Her research sits at the intersection of mathematical biology, cell biology, and computational modeling, with a particular focus on intracellular transport mechanisms and protein organization in cells. Her research interests include mathematical cell and developmental biology, emergent dynamics in intracellular transport, multiscale modeling of filamentous protein organization, parameter inference for models of biophysics experiments, applied dynamical systems, and applied topological data analysis. She develops mathematical and computational techniques to uncover the basic functions of intracellular proteins in development and injury, with applications to RNA transport in frog oocytes, radial glial cells, and neurons. Her work combines differential equations, stochastic modeling, and topological data analysis to address fundamental questions in cell biology. Her recent publications demonstrate a consistent focus on mathematical approaches to biological problems, particularly in cytoskeleton dynamics, intracellular transport, and symmetry analysis in developmental systems. She also maintains an active research program in social justice applications, particularly analyzing racial disparities in federal sentencing through mathematical and statistical approaches. Lee A. Segel Prize for the Best Paper in the Bulletin of Mathematical Biology (2025) for 'Parameter identifiability in PDE models of fluorescence recovery after photobleaching' Red Sock Award (SIAG/Dynamical Systems) for best poster presentation Ciocanel actively mentors undergraduate students through various research programs including DOmath, PRUV, and Muser. Two of her former students, Anna and Niny, have gone on to become Assistant Professors at University of New Mexico and San Francisco State University, respectively. She has secured significant research funding including grants from the National Science Foundation and Pennsylvania State University for projects on microtubule behavior and membrane-actin cortex adhesion. She is also involved in the RTG: Training Tomorrow's Workforce in Analysis and Applications program as a Co-Principal Investigator. Her laboratory focuses on mathematical modeling of intracellular transport processes, with particular emphasis on microtubule dynamics in neurons and mRNA transport mechanisms. She collaborates extensively with experimental biologists at institutions including Brown University, Penn State University, and Duke University to ensure her mathematical models remain grounded in biological reality.

Divya Bhaskaranمشاهده پروفایل

استادیار

• Sports Biomechanics
• Rehabilitation Science
• Neuromodulation Devices
• +۳ مورد دیگر

Divya Bhaskaran is an Assistant Professor in the Exercise Science program at Hamline University, specializing in lower extremity sports biomechanics and exercise-based rehabilitation. Her research integrates clinical trials with biomechanical analyses to explore rehabilitation techniques and neuromodulation technologies. Education: PhD in Rehabilitation Science from the University of Minnesota Prior Appointments: Post-Doctoral Associate at Mayo Clinic and University of Minnesota Her research focuses on: Sports biomechanics in athletic populations Rehabilitation science through clinical trials Neuromodulation device applications Lower extremity kinematics during dynamic movements Publications show expertise in: Prosthetic device evaluation (2018) Vibro-tactile neuromodulation (2024) Ankle/knee kinematic analyses (2012-2016) EMG and surface perturbation studies (2015) Her lab provides students with hands-on experience analyzing athlete biomechanics, bridging theory and real-world application in sports science education.

• Geophysics
• Inverse Theory
• Electromagnetic Methods
• +۴ مورد دیگر

Michael S. Zhdanov is a Distinguished Professor in the Department of Geology and Geophysics at the University of Utah, where he has served since 1993. As Director of the Consortium for Electromagnetic Modeling and Inversion (CEMI) since 1995, he leads industry-sponsored research in non-seismic geophysics. He holds a Ph.D. from Moscow State University and previously held prominent roles at the Moscow Academy of Oil and Gas and the Russian Academy of Sciences. Research Focus Dr. Zhdanov pioneered regularized focusing inversion for geological imaging and developed the Gramian-based joint inversion framework for multiphysics data integration. His work bridges geophysics, machine learning (e.g., diffusion models, ResU-Net++), and computational methods to solve inverse problems in mineral exploration, subsurface imaging, and electromagnetic modeling. Key domains include salt dome reconstruction, basin analysis, and airborne EM/IP inversion. Publication Trends Recent work (2023–2025) demonstrates a strong emphasis on AI-driven geophysical inversion , with neural networks (ResU-Net++, EfficientNetV2) applied to gravity/magnetic data for salt dome detection, basement relief mapping, and mineral targeting. Over 50% of publications integrate machine learning with traditional inversion theory. Awards and Honors IEEE Senior Member (2024) SEG Honorary Membership (2013) Gauss Professorship, Gottingen Academy (1990) University of Utah Distinguished Scholarly Award (2009) Full Member, Russian Academy of Natural Sciences (1991) Leadership and Funding As CEMI Director, Zhdanov collaborates with 30+ industry partners (e.g., Shell, ExxonMobil, BHP). Secured grants from NSF, DOE, and industry for projects on 3D EM inversion, mineral exploration, and airborne survey technologies. Actively advises graduate students in inversion theory and EM methods. Facilities Leads the CEMI Consortium, developing advanced computational tools for multiphysics data fusion used globally in resource exploration.

• Data Compression
• Medical Image Processing
• Cryptography
• +۵ مورد دیگر

Huseyin Kocak is a Professor at the University of Miami in the College of Arts and Sciences with a joint appointment in Mathematics and Computer Science. His scholarly work bridges theoretical mathematics with practical applications in data compression and security, establishing him as a significant contributor to both computational mathematics and applied computer science. Dr. Kocak's research program encompasses several interconnected domains of computational science: Advanced data compression techniques for medical imaging and color photography Integration of encryption protocols within compression algorithms Mathematical modeling of dynamical systems and chaos phenomena Development of specialized algorithms for medical diagnostics and genomic analysis Theoretical foundations of differential and difference equations with biological applications Analysis of Dr. Kocak's publication trajectory reveals a strategic evolution from fundamental mathematical research toward increasingly applied computational techniques. His early work focused on rigorous theoretical problems in dynamical systems, particularly homoclinic orbits in differential equations as evidenced by his 2021 publication on Shilnikov Saddle-Focus Homoclinic Orbits. More recently, his research has centered on solving critical healthcare challenges through innovative computational approaches, with his 2025 paper addressing FDA compliance requirements for medical image compression. His most significant contribution appears to be the development of BWIC (Burrows-Wheeler Inversion Coder), which demonstrates superior performance compared to industry standards like JPEG 2000 across multiple image types, particularly for medical applications where data integrity is paramount. Dr. Kocak's scholarly impact extends beyond pure compression research through his innovative work combining security with compression efficiency. His concurrent encryption approach, which uses the inversion frequency vector as a secure key, represents a paradigm shift in how data security is implemented within compression pipelines, offering substantial computational savings while maintaining robust security.

• Predictive Maintenance
• Mixed Reality Applications
• Human-Robot Collaboration
• +۵ مورد دیگر

Bernard Schmidt is an active researcher at the University of Skövde's School of Engineering Science, specializing in Production and Automation Engineering. His work bridges cutting-edge mixed reality applications with industrial predictive maintenance systems, focusing on sustainable manufacturing solutions. Affiliated with the Virtual Systems Research Centre (closed 2017) and Virtual Engineering Research Environment, he contributes to multiple research profiles including VF-KDO and Virtual Production Development. His research interests center on predictive maintenance methodologies , human-robot collaboration interfaces , and cloud-enhanced manufacturing systems . Schmidt develops mixed reality training environments that reduce production line disruption while improving operator safety. His work integrates double ball-bar measurements with machine learning to create population-based maintenance models that achieve 40% cost reduction compared to traditional approaches. Current projects include ACCURATE (2021-2025) and VF-KDO (2019-2026), funded by Sweden's Knowledge Foundation. Analysis of Schmidt's 15 most recent publications reveals a strong trend toward real-time industrial decision support systems using mixed reality visualization. His work consistently addresses sustainable manufacturing through energy-efficient robotics and predictive maintenance frameworks that leverage cloud computing. Key subfields include virtual sensor integration, collision avoidance algorithms, and multi-objective optimization for robotic cells - demonstrating practical applications in automotive and elevator manufacturing. Research funding highlights include: Knowledge Foundation (KKS) projects: ACCURATE (2021-2025), VF-KDO (2019-2026), Virtual Factory with Knowledge-Driven Optimization (2018-2026) European Commission grant (637107) IPSI Industrial Research School collaboration with Volvo GTO and Volvo Cars Schmidt actively supervises bachelor's degree projects at ASSAR Industrial Innovation Arena in Skövde, with recent work involving Natalia Sempere Maciá and Celia Redondo Verdú. His research integrates with ABB Robotics systems through partnerships with experts like Tommy Y. Svensson. Current laboratory work focuses on HoloLens 2 implementations for robotic cell visualization and safety system development for human-robot collaborative environments.

• Digital Human Modeling
• Virtual Reality
• Human-Robot Interaction
• +۵ مورد دیگر

Maurice Lamb is a researcher at the University of Skövde , affiliated with the Interaction Lab (ILAB) and the School of Informatics . His work bridges digital human modeling (DHM) , virtual reality , and human-robot interaction (HRI) with applications in automotive design and cognitive science . Research interests include: Automated design optimization using simulation-based multi-objective methods Collaborative tools for remote design reviews and CAD integration Cognitive implications of inverse kinematics solvers (FABRIK) in motor planning Impact of XR technologies on motor skill learning and human-agent coordination Methodological challenges in NARS (Negative Attitude toward Robots Scale) application Key projects include PLENUM (Vinnova-funded) and OKAVIM (AFA Insurance-funded), focusing on remote collaboration , ergonomics , and cognitive support in VR/XR . His publications span IEEE , Springer , and Elsevier journals, often co-authored with experts like Francisco Garcia Rivera, Erik Billing, and Dan Högberg.

• Sports Technology
• Sustainability Science
• Systems Modeling
• +۳ مورد دیگر

Fredrik Ståhl serves as a Senior Lecturer at Mid Sweden University within the Faculty of Science, Technology and Media, specifically affiliated with the Department of Engineering, Mathematics and Subject Didactics. He holds a Doctor of Philosophy degree and maintains active research roles through the Sports Tech Research Centre, with physical presence in Östersund (Room Q281A). His educational foundation includes doctoral research completed at Umeå University, culminating in the 2000 dissertation At the edge of space and time - exploring the b-boundary in general relativity . This early work established his expertise in mathematical relativity before his research trajectory evolved toward applied interdisciplinary domains. Ståhl's research demonstrates a profound transition from theoretical physics to practical applications. Initial investigations centered on spacetime singularities and boundary constructions in general relativity, while recent work focuses on sports technology optimization and sustainability systems. His current projects—including Augmented Sports and the Mid Sweden Craft Brewing Lab —leverage mathematical modeling for athletic performance enhancement and regional sustainability frameworks, reflecting an integrative approach bridging engineering, environmental science, and human movement analysis. Analysis of his publication history reveals three distinct research phases: foundational work in mathematical relativity (1997-2002), transitional biomechanics studies (2008), and current sustainability/sports technology applications (2013-2015). This evolution showcases increasing interdisciplinary collaboration, particularly with sustainability researchers like Skytt and Nielsen, while maintaining rigorous mathematical methodology throughout his career. As an active member of the Sports Tech Research Centre, Ståhl contributes to projects examining human performance through computational modeling. His recent conference participations at the International Society for the Systems Sciences and Global Cleaner Production forums indicate strong engagement with global sustainability challenges, particularly through system modeling approaches for Anthropocene governance and long-term decision support tools.

• Robotics
• Point Cloud Registration
• Conformal Geometric Algebra
• +۴ مورد دیگر

Adam Leon Kleppe is an Associate Professor at the Norwegian University of Science and Technology (NTNU) , affiliated with the Department of ICT and Natural Sciences. He works extensively with MANULAB , focusing on robotic welding labs and Industry 4.0 labs , handling procurement, planning, installation, and maintenance. His research spans robotics, geometric algebra, point cloud processing, and automation technologies. Education : Master in Engineering Cybernetics with a specialization in robotics from NTNU (2013); Ph.D. (2018) on Point Cloud Registration for Assembly using Conformal Geometric Algebra. Research Interests revolve around robotics, including inverse kinematics, point cloud alignment, obstacle detection, and geometric algebra applications. He also explores automation in manufacturing and aquaculture, such as deformable body modeling for salmon equipment testing and machine vision for fish bin picking. Publication Trends show a consistent focus on geometric algebra-based solutions for robotic tasks, with recent work extending into biomechanical simulation and aquaculture automation. Teaching includes courses like Mechatronics and Systems Integration , Automation and Mechatronics , and Industrial Control Systems . He also contributes to outreach via program management for AI videos on platforms like YouTube and LinkedIn.

• Geophysics
• Seismology
• Full-Waveform Inversion
• +۵ مورد دیگر

Bao Xueyang is an Assistant Professor at the Department of Earth and Space Sciences (Faculty of Science) of Southern University of Science and Technology (SUSTech) , where he has worked since January 2019. His academic background includes a Ph.D. in Geology from the University of Missouri-Columbia (2011) , M.S. and B.S. degrees in Geophysics from the University of Science and Technology of China . Ph.D., Geological Sciences, University of Missouri-Columbia (2011) M.S., Earth and Space Sciences, University of Science and Technology of China (2005) B.S., Earth and Space Sciences, University of Science and Technology of China (2001) His research focuses on seismological full-waveform inversion , seismic wave attenuation measurement , and geophysical studies of tectonically active regions such as the Tibetan Plateau and Tethys domain. Methodologically, he develops techniques for: 3D full-waveform inversion Joint seismic-gravity inversion Seismic wave attenuation anisotropy Background noise tomography Wavefield simulation on complex topographies Seismic source parameter inversion Analysis of his recent publications reveals expertise in full-waveform sensitivity kernel development , ocean-bottom seismology , and cratonic lithosphere thermal structure through Rayleigh wave attenuation studies. His work spans both theoretical advancements in inversion algorithms and practical applications in energy resource characterization and tectonic studies. Scientific recognition includes: 2019 Shenzhen Overseas High-Level Talent 2022 Excellence Awards in Reviews of Geophysics and Planetary Physics He leads multiple National Natural Science Foundation projects while co-leading international research initiatives. His teaching portfolio includes undergraduate and graduate courses on geophysical inversion theory, covering both linear and nonlinear inversion methods with machine learning applications.