جست‌وجوی استاد و پژوهشگر

• Crystal Plasticity
• Materials Science
• Computational Materials Engineering
• +۵ مورد دیگر

Martin Diehl is a computational materials scientist affiliated with KU Leuven (Departments of Computer Science and Materials Engineering) and the Max-Planck-Institut für Eisenforschung GmbH in Germany. His work focuses on crystal plasticity simulations, computational materials engineering, and multi-physics modeling of metallic systems. Research interests include: Crystal plasticity finite element method (CPFEM) and spectral solvers Microstructure evolution and damage mechanics Machine learning applications in materials design Development of the DAMASK simulation toolkit Multi-phase steel alloys and heterogeneous deformation Integrated computational materials engineering (ICME) Key trends in his publications since 2021 highlight advancements in: Multi-physics DAMASK framework for coupled chemo-mechanical and thermal simulations AI-driven inverse design of steel microstructures Damage modeling in dual-phase steels Collaborative software development for materials science Experimental-simulation integration for stress-strain partitioning High-resolution spectral methods for finite strain analysis He actively collaborates with institutions like Harbin Institute of Technology, University of Oxford, and research groups across Europe and Asia.

Stephen Keltyمشاهده پروفایل

استاد

• Physical Chemistry
• Computational Chemistry
• Materials Science
• +۳ مورد دیگر

Stephen Kelty, Ph.D., is a Professor in the Department of Chemistry and Biochemistry at Seton Hall University, where he leads the Kelty Research Group. His work focuses on computational and physical chemistry, particularly in modeling solid-state and molecular systems using advanced methods like DFT and molecular dynamics. He is affiliated with the Center for Computational Research, leveraging its resources for interdisciplinary projects. Dr. Kelty’s research spans heterogeneous catalysis, defect analysis in oxides (e.g., YSZ, HfO₂), and photoactive materials for energy applications. Education: Ph.D., Chemistry, Harvard University (1993) M.Phil., Chemistry, Columbia University (1991) B.S., Chemistry, University of Cincinnati (1979) Research Interests: Dr. Kelty’s group investigates electronic and structural properties of materials at atomic and molecular scales. Key areas include: Computational modeling of catalytic mechanisms Defect engineering in oxides (e.g., YSZ thin films) Design of photoactive materials for solar energy conversion Ab initio and DFT studies of functionalized molecules Recent Trends in Publications: Recent work emphasizes computational analysis of ferroelectric hafnia, phase transitions in niobium germanate thin films, and enhanced performance in La/SrCoO₃ electrodes. Collaborations include studies at Los Alamos National Lab and presentations at the Organic Reactions Catalysis Society. Advising & Labs: Guided students like Sara Lamcaj (Los Alamos intern) and Frank Hung (APS presenter) Leverages the Center for Computational Research for high-performance simulations

• Control of Dynamic Systems
• System Identification
• Optimal Estimation and Control
• +۳ مورد دیگر

David M. Bevly is an Assistant Professor in the Department of Mechanical Engineering at Auburn University, where he has been on the faculty since 2001. He directs the GPS and Vehicle Dynamics Laboratory (GAVLAB) and teaches a range of courses spanning system dynamics, vehicle dynamics, optimal estimation and control, and GPS navigation. Education Ph.D. Mechanical Engineering, Stanford University, 2001 M.S. Mechanical Engineering, Massachusetts Institute of Technology, 1997 B.S. Mechanical Engineering, Texas A&M University, 1995 Research Interests His research integrates control theory with real-world vehicle applications, focusing on control of dynamic systems, optimal estimation and control, GPS and sensor fusion, vehicle dynamics and control, and vehicle state estimation . Combining low-cost GPS receivers with inertial sensors, he develops algorithms that enable precise state estimation for passenger cars, agricultural tractors, and off-road platforms, enhancing safety and autonomy. Publication Trends Between 1999 and 2004, Bevly authored or co-authored more than a dozen journal and conference papers that collectively advance the fields of GPS-aided vehicle control and precision agriculture. The works explore theoretical contributions—such as dead-reckoning error analysis and yaw-dynamic modeling—and demonstrate practical implementations on farm tractors and high-speed ground vehicles. Awards & Recognition Best Paper of Session, 2000 ION-GPS Meeting SAE Arch T. Colwell Award (Myers Award) for Outstanding Student Paper, 2000 Laboratory & Teams As head of the GPS and Vehicle Dynamics Laboratory (GAVLAB) at Auburn, Bevly leads interdisciplinary projects that integrate mechanical design, real-time embedded systems, and field experimentation. The lab collaborates with industry partners and federal agencies to transition research results into commercial vehicle-safety and agricultural-autonomy products.

• Flow in underground porous media
• Geoenergy
• Underground energy storage
• +۱۲ مورد دیگر

Dario Viberti is a Full Professor at the Polytechnic University of Turin, affiliated with the Department of Environmental, Land and Infrastructure Engineering (DIATI). He is a member of the Interdepartmental Center Ec-L - Energy Center Lab and actively contributes to the Master's and Continuing Education School. He serves as Coordinator for both Master’s levels I and II of the Natural Resources Development and Storage program and participates in doctoral colleges for Civil and Environmental Engineering and Materials, Sustainable Processes, and Systems for the Transition. His research focuses on flow in underground porous media , geoenergy , and underground energy storage , particularly hydrogen and CO₂ storage. His expertise spans numerical modeling, reservoir engineering, fluid mechanics, well testing, and energy transition systems. He is involved in commercial research projects with ENI Corporate University and leads initiatives related to sustainable energy applications. His recent publications reveal a strong trend in underground hydrogen storage , biogeochemical modeling , pore-scale simulation , and PVT analysis of gas mixtures . These works emphasize safety, efficiency, and long-term integrity of subsurface storage systems using advanced computational and experimental methods. Scientific Manager, Underground CO2 Storage Project (2022) Scientific Manager, Reservoir Modeling Project (2022) Coordinator, Master’s Program in Natural Resources Development and Storage Member, SEASTAR Competence Center Committee (2020–2025) He mentors several PhD students, including Michel Tawil, Marialuna Loffredo, Alice Raeli, and Alice Massimiani, supporting research in microfluidics, Lattice Boltzmann simulations, and thermodynamic characterization. He teaches courses such as Numerical Modeling for Multiphase Flow , Underground Energy Storage , and Well Logging and Testing across multiple degree programs. His work aligns with UN SDGs 7 (Affordable and Clean Energy), 9 (Industry, Innovation, and Infrastructure), and 13 (Climate Action).

Helmut Schwarzمشاهده پروفایل

استاد

• Gas-phase ion chemistry
• Physical organic chemistry
• Organometallic chemistry
• +۱۲ مورد دیگر

Prof. Dr. Helmut Schwarz is a distinguished faculty member at the Technische Universität Berlin , where he holds a professorship in the Field of Organic Chemistry within the Institute of Chemistry. He is also a key member of the UniCat Cluster of Excellence , a leading interdisciplinary research initiative focused on catalysis. His work bridges experimental and theoretical chemistry, with a strong emphasis on gas-phase ion chemistry and reaction mechanisms. His research interests include gas-phase ion chemistry, physical organic chemistry, organometallic chemistry, selective bond activation by transition-metal species, mass spectrometry, and computational chemistry . He investigates fundamental processes such as methane and CO2 activation, C-H bond functionalization, and redox reactions using cluster ions and single-atom systems. His approach combines advanced mass spectrometric techniques with theoretical modeling to elucidate reaction mechanisms at the molecular level. His recent publications highlight trends in metal-mediated and metal-free bond activation, ligand and doping effects in clusters, spin-selective reactions, and the role of oxygen-centered radicals . A recurring theme is the activation of small molecules like methane, ammonia, and carbon dioxide under ambient or thermal conditions , with implications for sustainable catalysis and energy conversion. Helmut Schwarz has received numerous scientific honors, including: Eni Award (2015) Karl Ziegler Award (2015) Schrödinger Medal from WATOC (2015) Blaise Pascal Medal (2011) Wilhelm Manchot Professorship (2012) Foreign Honorary Member, American Academy of Arts and Sciences (2012) Honorary doctorate from Kliment Ochridski University, Sofia He has mentored numerous students and collaborators, though specific names are not listed in the provided text. His research is supported by major academic institutions and collaborative frameworks like UniCat. He leads a research group focused on mechanistic studies using mass spectrometry and maintains strong collaborations with theoretical chemists. His laboratory employs advanced techniques including ion-trap mass spectrometry, gas-phase spectroscopy, and computational modeling to explore transient reactive species and catalytic cycles.

• Computer Science
• Artificial Intelligence
• Cybernetics
• +۳ مورد دیگر

Dilip Sarkar serves as an Associate Professor in the Department of Computer Science at the College of Arts and Sciences, University of Miami. His academic profile demonstrates a strong research focus across multiple domains of computer science with particular emphasis on theoretical foundations and practical applications. Dr. Sarkar's research interests include: Artificial Intelligence and Cybernetics Parallel Algorithms and Programming Combinatorics Image Processing and Compression Internet of Things Security Machine Learning Applications in Healthcare Quantum Computing Approaches His publication record from 2018-2024 reveals a researcher engaged with cutting-edge computational challenges. Recent work spans quantum tensor networks for time series analysis, security frameworks for single sign-on systems, efficient computation in belief theoretic models, and machine learning applications for traumatic brain injury recovery prediction. His research demonstrates consistent integration of theoretical computer science with practical problem-solving across diverse application domains. As a member of CCS (Center for Computational Science) at the University of Miami, Dr. Sarkar participates in interdisciplinary research initiatives that bridge computational methods with scientific discovery across multiple fields. His technical expertise spans both theoretical frameworks and practical implementations, with notable contributions to image compression techniques, particularly for medical applications, and security protocols for modern web and IoT environments.

Nina Maherndlمشاهده پروفایل

استادیار

• Cloud Microphysics
• Mixed-phase Clouds
• Riming Processes
• +۳ مورد دیگر

Nina Maherndl serves as Assistant Professor for Ground-based Remote Sensing of Clouds at the Department of Geoscience & Remote Sensing within Delft University of Technology's Faculty of Civil Engineering and Geosciences, a position she assumed in 2025 after completing her PhD at Leipzig University. Her research focuses on microphysical processes in mid- and high-latitude mixed-phase clouds. Her educational background includes: PhD in Meteorology, Leipzig University (2024) Dr. Maherndl specializes in ice formation and growth mechanisms , with particular emphasis on riming processes in mixed-phase clouds. Her work investigates how these microphysical phenomena drive spatial variability in ice and snowfall distribution, bridging observational cloud physics and ground-based remote sensing methodologies to improve atmospheric modeling. Current efforts focus on quantifying riming effects through airborne campaign data and developing advanced parameterizations for snowflake scattering. Her 2023-2024 publications demonstrate consistent innovation in riming quantification techniques , leveraging data from the HALO-(AC)3 aircraft campaign and developing novel parameterizations for remote sensing applications. These studies integrate cloud microphysics , airborne instrumentation , and radiative transfer modeling to address precipitation formation challenges in mixed-phase systems. Dr. Maherndl operates within TU Delft's Geoscience & Remote Sensing (GRS) Laboratory framework and has participated in international field campaigns including HALO-(AC)3. No information regarding student supervision or grant funding was provided in the source materials.

Elizabeth M.Y. Leeمشاهده پروفایل

استادیار

• Materials Science
• Quantum Technologies
• Energy Sustainability
• +۳ مورد دیگر

Elizabeth (Liza) Lee is an Assistant Professor at the Samueli School of Engineering , University of California, Irvine (UCI), with joint appointments in Materials Science and Engineering and Chemical and Biomolecular Engineering . Her research program focuses on theory and computational modeling of materials formation, breakdown, and transport to design sustainable solutions for quantum and energy technologies. Ph.D. , MIT, Chemical Engineering M.S. , MIT, Chemical Engineering Practice B.S./B.A. , Johns Hopkins University, Chemical and Biomolecular Engineering and Chemistry Lee’s research bridges ab initio calculations , machine learning , and molecular simulations to study functional materials. Key areas include catalytic plastic waste deconstruction , quantum defects in semiconductors , and computational method development using statistical mechanics and machine learning. Her work has implications for sustainable synthesis , quantum information science , and energy technologies . Her recent publications (2025–2024) span nanostructure modeling , electrocatalysis , machine learning in materials science , and solid-state electrolytes , reflecting her interdisciplinary approach. Notable awards include the NSF CAREER Award , UCI Samueli Faculty Development Chair , and DOE ASCR Leadership Computing Challenge Award . NSF CAREER Award UCI Samueli Faculty Development Chair DOE ASCR Leadership Computing Challenge Award NSF Graduate Research Fellowship AIChE Electronics and Photonics Materials Award UCI Engineering Student Council’s Professor of the Year Award Maria Lastra Postdoctoral Mentor Award

• Hydrogeology
• Saturated-Unsaturated Flow
• Water-Gas Two-Phase Flow
• +۳ مورد دیگر

Kuang Xingxing is an Associate Professor at the School of Environmental Science and Engineering, Southern University of Science and Technology . His research focuses on saturated-unsaturated flow, water-gas two-phase flow, solute transport modeling, and groundwater response to climate change. PhD in Hydrogeology (2012) from the University of Hong Kong M.Eng in Hydrology and Water Resources (2008) and B.Eng in Hydrology and Water Resources Engineering (2007) from China University of Geosciences (Beijing) His work improves parameter models for groundwater flow and solute transport, with studies published in leading journals like Water Resources Research and Geophysical Research Letters . He also investigates climate change impacts on Qinghai-Tibet Plateau groundwater systems. Recent publications highlight his contributions to two-phase flow mechanisms in aquifers, solute transport modeling in deltaic systems, and permeability-depth relationships in Earth’s crust. His research integrates laboratory experiments, numerical simulations, and field data. Scientific Awards : AXA Research Fund Post-Doctoral Fellowships (2014) Beijing Outstanding Graduate (2007) China University of Geosciences Outstanding Graduate (2007) SINOPEC Scholarship (2005) National Second Class Scholarship (2004) He serves as Associate Editor of Hydrogeology Journal and reviews for top journals. Teaching includes undergraduate courses in Hydraulics , Hydraulic Experiment , and Introduction to Earth Science .

• Biostatistics
• Environmental Dose-Response Modeling
• Quantitative Risk Assessment
• +۷ مورد دیگر

Paul J. Catalano is a Senior Lecturer in the Department of Biostatistics at the Harvard T.H. Chan School of Public Health. He is affiliated with the Dana-Farber Cancer Institute, where he serves as a statistician for clinical trials and collaborates on cancer research. His research focuses on biostatistical methods for analyzing multiple outcomes and repeated measures in environmental dose-response modeling, quantitative risk assessment, and neurotoxicity studies. He also develops software for implementing modeling algorithms and investigates experimental design in low-dose risk estimation. Recent publications highlight collaborations in immunotherapy for urothelial carcinoma radiation therapy for brain metastases pediatric neuroblastoma treatment AI-driven MRI segmentation . Dr. Catalano's work extends to clinical trials in colorectal, genito-urinary, and breast cancer, with emphasis on prognostic factor identification and translational research.

• Materials engineering
• Mechanical engineering
• Machine learning
• +۱۲ مورد دیگر

Professor Nick Birbilis serves as the Executive Dean of the Faculty of Science Engineering and Built Environment at Deakin University. With a distinguished career spanning materials science, corrosion engineering, and machine learning applications, he leads one of Australia's most innovative academic faculties. His research has significantly impacted the fields of materials engineering, particularly in corrosion science, alloy development, and advanced manufacturing techniques. Professor Birbilis's educational background includes a Doctor of Philosophy, Graduate Certificate of Higher Education, and Bachelor of Engineering (with Honours) in Materials Engineering, all from Monash University. His research interests span materials engineering, mechanical engineering, machine learning, metals and alloy materials, electrochemistry, and glass technology. His recent publications demonstrate a strong focus on the intersection of traditional materials science with cutting-edge computational approaches. The research trends show increasing integration of machine learning techniques for alloy design and property prediction, alongside continued fundamental work on corrosion mechanisms in advanced materials including multi-principal element alloys, magnesium alloys, and additively manufactured components. Fellow, ASM International (2022) Fellow, Engineers Australia (2021) Fellow, International Society of Electrochemistry (2020) H.H. Uhlig Award, The Electrochemical Society (2020) Batterham Medal, Academy of Technological Sciences and Engineering (2017) Lee Hsun Award, Chinese Academy of Science (2015) Professor Birbilis currently supervises multiple doctoral students working on cutting-edge projects including sustainable engineering models, 3D printed glass behavior, corrosion-resistant coatings, and biomolecular extraction techniques. His research is supported by significant grants from the Australian Research Council, Department of Education, Office of Naval Research USA, and industry partners including Advanced Alloy Holdings, InfraBuild, and Bluescope Steel. These projects focus on hydrogen economy applications, corrosion-resistant alloys, advanced protective coatings, and steel innovation.

• Quantum Optics
• Ultracold Atoms
• Condensed Matter Physics
• +۴ مورد دیگر

Gediminas Juzeliūnas is a Distinguished Professor at the Institute of Theoretical Physics and Astronomy within the Faculty of Physics at Vilnius University. His research spans quantum optics, ultracold atoms, and condensed matter physics, with particular expertise in quantum simulations and synthetic gauge fields. Professor Juzeliūnas's research program focuses on creating artificial gauge fields for neutral atoms, enabling quantum simulation of complex condensed matter phenomena. His seminal Reviews of Modern Physics article on artificial gauge potentials has become foundational in the field. Current research explores subwavelength optical lattices, topological quantum matter, and spin-orbit coupling phenomena in ultracold atomic systems. His theoretical work often bridges fundamental concepts with experimental feasibility, making it highly influential in both theoretical and experimental communities. Analysis of his recent publications reveals a clear trajectory toward exploring topological phenomena in ultracold atomic systems through subwavelength structures and Raman lattices. Juzeliūnas has pioneered approaches to create and manipulate synthetic gauge fields that simulate condensed matter physics, with applications ranging from quantum simulation to precision measurement technologies. His work frequently addresses the interplay between geometrical frustration, long-range interactions, and topological order in quantum many-body systems. True member of the Lithuanian Academy of Sciences (since 2019) Jucys Prize for Theoretical Physics (2014) Vilnius University Rector's award (2010, 2025) National State Prize for Science of Lithuania (2007) Professor Juzeliūnas has supervised multiple doctoral students including Edvinas Gvozdiovas (working on subwavelength optical lattices), Tomas Andrijauskas (researching artificial magnetic fields), and Hamid Reza Hamedi (studying slow light phenomena). He currently leads four major research projects funded by the Lithuanian Research Council, including "Ultracold atoms in unconventional optical lattices" (2024-2027) and "Quantum dynamics of interacting ultracold atoms in complex sub-wavelength potentials" (2024-2026), demonstrating his leadership in advancing quantum simulation techniques. His research group at the Institute of Theoretical Physics and Astronomy collaborates extensively with international partners, including Japanese, Latvian, and Taiwanese scientists, reflecting the global significance of his work. Professor Juzeliūnas regularly presents at major international conferences and has chaired significant events including the Humboldt Kolleg on Synthetic Quantum Matter (2023) and the 14th European Conference on Atoms Molecules and Photons (2022).

Günther Grünمشاهده پروفایل

استاد

• Stochastic Partial Differential Equ (SPDE)
• Free Boundary Problems
• Continuum Mechanics
• +۵ مورد دیگر

Prof. Dr. Günther Grün is a faculty member at the University of Erlangen-Nuremberg , specializing in Applied Mathematics . His work bridges rigorous mathematical analysis, numerical methods, and applications in continuum mechanics , fluid dynamics , and free boundary problems . He serves as Spokesperson for the DFG Research Training Group IntComSin (2022–2027), focusing on interfaces, complex structures, and singular limits in mathematical modeling and simulation. Education Diploma in Mathematics (1991), University of Bonn PhD in Mathematics (1994), University of Bonn Habilitation in Mathematics (2001), University of Bonn Research Interests center on degenerate parabolic equations (e.g., porous-medium and thin-film equations), stochastic SPDEs with multiplicative noise, diffuse interface models for two-phase flow with surfactants, and dimension-reduced models via singular limits. His work combines calculus of variations , homogenization , and Gamma-convergence for multi-scale analysis, alongside finite-element/finite-volume schemes for efficient simulations. Scientific Awards Marie Curie Research Fellowship (1996), Universita di Tor Vergata, Rome Advising Legacy includes mentoring doctoral candidates such as Dr. Fabian Klingbeil (Accenture), Dr. Jürgen Becker (Fraunhofer Institute), and Prof. Dr. Julian Fischer (IST Austria), who have pursued careers in academia, industry, and research institutions.

Zihe Gaoمشاهده پروفایل

استادیار

• Optics
• Integrated Photonics
• Quantum Optics
• +۵ مورد دیگر

Zihe Gao serves as a tenure-track Assistant Professor in the Department of Electrical and Computer Engineering at Auburn University's College of Engineering since August 2023, following postdoctoral research at the University of Pennsylvania and industry experience at Meta (Facebook Reality Labs). His academic foundation includes: PhD in Electrical and Computer Engineering, University of Illinois Urbana-Champaign (2018) MS in Physics, University of Illinois Urbana-Champaign (2012) BS in Physics, Nanjing University (2011) Dr. Gao's research integrates optics, microelectronics, and physics to develop programmable photonic systems. His work focuses on controlling collective behaviors in multi-element photonic systems for scalable integrated chips, with applications spanning dynamically steerable laser sources and reconfigurable quantum optical platforms . Key methodologies include non-Hermitian physics, topological photonics, and spin-orbit coupling engineering. Analysis of his 2023-2025 publications reveals dominant trends in non-Hermitian photonic switching , high-dimensional quantum state manipulation , and topological semiconductor laser arrays . His team pioneers lithography-free reconfigurable photonics and spin-orbit microlasers for quantum key distribution, demonstrating strong industry-academia translation from prior Meta work on AR/VR structured-light systems. His scholarly trajectory shows continuous progression from VCSEL array fundamentals (PhD under Prof. Kent Choquette) to quantum-topological photonics (postdoc with Prof. Liang Feng), now establishing independent research at Auburn with emphasis on integrated quantum-classical hybrid systems.

Edward V. DiBellaمشاهده پروفایل

استاد

• Advanced MRI Imaging
• Positron Emission Tomography
• Image Processing
• +۵ مورد دیگر

Edward V. DiBella, PhD, is a Professor in the Department of Radiology & Imaging Sciences at the University of Utah School of Medicine, where he serves as director of the Utah Center for Advanced Imaging Research (UCAIR). He holds adjunct faculty appointments in Bioengineering and is affiliated with the Center for Arrhythmia Research and Management (CARMA) and the Experimental Therapeutics Program in the Huntsman Cancer Institute. Dr. DiBella leads the Cardiovascular MRI Group, focusing on developing advanced imaging techniques for cardiac applications. Dr. DiBella's educational background includes a Master's degree from the University of Vermont and a PhD from the Georgia Institute of Technology, followed by postdoctoral training at the University of Utah Department of Radiology. His research spans over two decades of contributions to medical imaging science. His primary research interests center on improving MRI acquisition, reconstruction, and post-processing techniques, with particular emphasis on cardiac, cancer, and stroke applications. Dr. DiBella's work addresses fundamental challenges in medical imaging including motion artifacts, image reconstruction from undersampled data, quantitative perfusion analysis, and advanced techniques for cardiac imaging. His group has pioneered radial simultaneous multi-slice (SMS) approaches for myocardial perfusion MRI that enable whole-heart coverage without gating. Analysis of Dr. DiBella's recent publications reveals a strong focus on deep learning applications in MRI reconstruction, quantitative myocardial perfusion techniques, and advanced diffusion imaging for stroke recovery prediction. His work demonstrates a consistent trajectory toward more efficient, accurate, and clinically applicable imaging methods that address real-world challenges in cardiac MRI. Dr. DiBella has mentored numerous graduate students and postdoctoral researchers who have gone on to successful careers in academia and industry. His laboratory maintains active collaborations with cardiology, electrophysiology, and bioengineering departments, reflecting the interdisciplinary nature of modern medical imaging research. Current projects in Dr. DiBella's Cardiovascular MRI Group include Deep Learning for Radial SMS Reconstruction, Diffusion imaging for predicting stroke recovery, Quantitative myocardial perfusion, and Radial SMS for myocardial perfusion MRI. The group's work is particularly relevant to heart failure, coronary artery disease, and atrial fibrillation diagnosis and management, addressing the fact that heart disease remains the leading cause of death worldwide.