جست‌وجوی استاد و پژوهشگر

• Geophysics
• Machine Learning
• Differential Equations
• +۵ مورد دیگر

Facu Sapienza is a Postdoctoral Scholar in Geophysics at Stanford University, focusing on interdisciplinary research that combines paleomagnetism , differential equations , machine learning , and quantum thermodynamics . His work bridges computational methods with Earth and planetary sciences, particularly through physics-informed machine learning models for glaciology and magnetospheric studies. His recent publications highlight expertise in Universal differential equations for geophysical modeling Statistical learning for remagnetization analysis Quantum thermodynamic resource theory Planetary magnetic field interactions (Mars) Distance learning algorithms with Fermat principles trends in applying Gaussian processes, causal inference, and differentiable programming to geoscience challenges. He maintains an active research profile with collaborations in computational geophysics and quantum information theory, though no formal awards or student advising details are publicly listed in the provided materials.

• Physical Chemistry
• Computational Chemistry
• Multiscale Modeling
• +۵ مورد دیگر

Oliviero Andreussi is an Associate Professor in the Department of Chemistry at Boise State University. His research focuses on computational science applied to chemistry, materials science, and biophysics, with an emphasis on developing multiscale models for environment effects in wet materials interfaces. He holds a Ph.D. and M.S. in Physical Chemistry from the Scuola Normale Superiore of Pisa, Italy. His work includes open-source software development, such as continuum embedding libraries and Python workflows for high-throughput materials analysis, and integrates machine learning to improve simulation accuracy. Research interests span electrocatalyst design (e.g., 2D materials for water splitting), solvent effects in biomolecular systems, and computational methods for electrochemical interfaces. He has received the NSF CAREER Award (2020) and led grants on topics like 'Multiscale and Machine-Learning Approaches for Electrified Interfaces' and 'First-Principles High-Throughput Analysis of Gas Hydrates'. Teaching includes advanced physics courses (Statistical Mechanics, Computational Physics) at the University of North Texas and chemistry education at the University of Pisa. His lab emphasizes undergraduate research, requiring 10 weekly hours over 3–4 semesters, with opportunities for conference presentations and co-authorship. Current projects involve Unix/terminal proficiency and scripting for computational workflows. Awards: NSF CAREER Award (2020) Grants: NSF OAC (MRI Cluster), ACS Petroleum Research Fund, NSF CSSI Program Labs/Teams: Focus on computational modeling, open-source software (Fortran/Python), and collaboration with experimental groups.

Eric Faulquesمشاهده پروفایل

پژوهشگر

• Smart Materials
• Solid-State Physics
• Optical Spectroscopy
• +۳ مورد دیگر

Dr. Eric Faulques is a CNRS Research Director affiliated with the University of Lille (IEMN) and previously held roles at the University of Nantes and other institutions. He earned his Ph.D. in Physics from the University of Nantes in 1986. His research focuses on smart materials, solid-state physics, optical spectroscopy, and nanotechnology, with recent work emphasizing quantum sensors and nanoscale material applications in photovoltaics and sensors. He has conducted postdoctoral research in Austria, the U.S., and the U.K., and led the NATO Quantum Sensor project. His teaching roles included adjunct lecturer positions at the Universities of Nantes and Poitiers. Current affiliations include the EPIPHY group at IEMN and leadership in thematic advisory committees for Nanomaterials journal. His expertise spans carbon-based materials, Raman spectroscopy, and computational modeling of nanostructures. Research activities include designing hybrid materials for optoelectronics, developing quantum sensor technologies, and studying confined systems like extreme nanowires in carbon nanotubes. He has pioneered methods for selective gas detection using quantum mechanisms and contributed to machine learning-driven material synthesis optimization. Key projects involve NATO-funded quantum sensor development and NATO SPS.MYP 985481 initiatives. Publications span 2025-2011, with recent emphasis on carbon nanotube composites, quantum sensor applications, and spectroscopic analysis of novel materials. His work bridges fundamental physics and applied nanotechnology, addressing energy, sensing, and environmental challenges. Current lab affiliations include the NCM and EPIPHY groups, where he collaborates on sub-wavelength photonics and nanoelectronics.

• Theoretical Chemistry
• Catalysis
• Molecular Dynamics Simulations
• +۴ مورد دیگر

Prof. Eckhard Spohr is a Professor of Theoretical Chemistry at the University of Duisburg-Essen, Germany. He leads Project A6 in the Collaborative Research Centre/TRR 247, focusing on molecular dynamics simulations of transition metal oxide-water interfaces to understand catalytic activity correlations. His research integrates theoretical and computational methods across electrochemistry, materials science, and nanotechnology. Education: 1995: Habilitation in Theoretical and Computational Chemistry, Ulm University 1986: PhD from Johannes Gutenberg-Universität Mainz 1983: Diploma in Chemistry from Johannes Gutenberg-Universität Mainz His research interests span molecular dynamics simulations, catalysis mechanisms, and surface-electrode interactions. Recent work emphasizes computational studies of transition metal oxides, photocatalytic materials, and nanoengine design. He has pioneered studies on proton transfer dynamics, silver deposition kinetics, and doped nanomaterials for energy applications. Awards include the Merckle Research Prize (2008), Feodor-Lynen Fellowship (1989-1990), and Otto-Hahn Medal (1988). His contributions bridge theoretical models with experimental catalytic systems, fostering advancements in sustainable energy materials. Grants and collaborations include leadership in TRR247 involving Max Planck institutes and Ruhr-University Bochum. Current projects focus on operando catalytic interfaces and photocatalytic water splitting systems. His theoretical frameworks underpin experimental efforts in energy conversion and nanotechnology.

• Phenomenology of Psychopathology
• Schizophrenia
• Qualitative Research Methods
• +۳ مورد دیگر

Elizabeth Pienkos is an Adjunct Associate Professor of Psychology at Clarkson University. She holds a Psy.D. from Rutgers University (2014). Her research focuses on phenomenological psychopathology, particularly schizophrenia and related disorders, emphasizing first-person experience analysis through methods like the Examination of Anomalous World Experience (EAWE) interview. She teaches courses including Introduction to Psychology and Clinical Psychology. Her work examines disturbances in self-world relations, perceptual salience, and hallucinatory experiences. Recent conference presentations address topics such as phenomenological methodology in psychosis research, mental health in rural communities, and stigmatization of psychiatric conditions. Pienkos has co-developed qualitative assessment tools and contributed to cross-cultural adaptation of clinical instruments. Her publications span journals like Philosophical Psychology and Schizophrenia Bulletin , focusing on qualitative analysis of psychiatric symptomology. She has also presented at international conferences including the World Congress of Psychiatry and the Schizophrenia International Research Society. Contact: epienkos@clarkson.edu | Office: Science Center 177

Theodoula N. Grapsaمشاهده پروفایل

دانشیار

• Numerical Analysis
• Optimization Methods
• Systems of Nonlinear Equations
• +۳ مورد دیگر

Theodoula N. Grapsa is an Associate Professor in the Department of Mathematics at the University of Patras, Greece. She is affiliated with the Division of Computational Mathematics and Informatics within the department. Her office is located at B/M 243, and she can be reached at grapsa@math.upatras.gr or theodoula.grapsa@gmail.com. Dr. Grapsa's research focuses on several key areas in computational mathematics: Numerical Analysis and Optimization Methods Systems of Nonlinear Equations Interval Analysis and Global Optimization Neural Networks and Machine Learning Algorithms Computational Mathematics and Numerical Algorithms Her recent work shows a strong emphasis on developing and improving optimization algorithms, particularly for unconstrained optimization problems. She has made significant contributions to Newton's method modifications, conjugate gradient approaches, and hybrid techniques that combine forecasting with optimization. Her research bridges theoretical mathematics with practical computational applications, particularly in the areas of neural network training and solving complex nonlinear systems. Dr. Grapsa has supervised numerous graduate students throughout her career, including PhD candidates and MSc students. Her past PhD students include Dimitris G. Sotiropoulos, John A. Nikas, and Aristotelis E. Kostopoulos. Current PhD students under her supervision are Eleftheria N. Malihoutsaki, Athanasia N. Papanikolaou, and Christina D. Nikolakakou. She has authored two books: "Εισαγωγή στην Ανάλυση Διαστημάτων - Interval Analysis" (2012) "Προγραμματίζοντας με Fortran'90" (2012) Dr. Grapsa is actively involved in teaching, including the course "Basic Principles of Programming," for which she organized an educational visit to the Patras Science Centre in Rio for first-year mathematics students in April 2013.

• Computational Materials Science
• Semiconductor Nanostructures
• Quantum Mechanics
• +۵ مورد دیگر

Dr. Hulusi Yilmaz is an Assistant Professor of Physics at Harrisburg University of Science and Technology. His research focuses on computational studies of atomic and electronic properties of semiconductor materials and nanostructures, including wide-bandgap semiconductors, carbon nanomaterials, topological materials, and photovoltaic cells. He integrates machine learning techniques into materials science to advance emerging technologies. Dr. Yilmaz holds a Ph.D. in Physics and teaches a broad range of physics, mathematics, and engineering courses. His work explores quantum mechanical methods to uncover material characteristics, with recent emphases on Sb₂Se₃ nanostructures, GaN nanotubes, and ferroelectric-semiconductor solar cells. His publications span topics like nanowire orientation effects, electronic bandgap engineering, and nanoscale interconnects. While no formal awards or grants are listed, his research portfolio demonstrates expertise in computational materials modeling, nanotechnology, and interdisciplinary applications of physics. He advises students in experimental and theoretical aspects of materials science and contributes to advancing energy-efficient technologies through his work on photovoltaic systems.

• Mathematical Modelling of Infectious Diseases
• Computational Materials Science
• Theoretical Semiconductor Physics
• +۵ مورد دیگر

Dr. Maja Krcmar is a Professor of Physics at Grand Valley State University (GVSU), part of the College of Liberal Arts & Sciences. She holds a Ph.D. in Physics (Condensed Matter Theory) from Texas A&M University (2001) and has been with GVSU since 2004, progressing from Adjunct Faculty to her current rank. Her research spans computational materials science, theoretical semiconductor physics, and recently mathematical modeling of infectious diseases. She teaches a wide range of physics courses including computational physics, solid-state physics, and advanced mechanics. Education: Ph.D., Texas A&M (2001); M.S., Texas A&M (1998); B.S., University of Belgrade (1995). Research interests include structural phase transformations in alloys, ferroelectric oxides, and nanocluster dynamics. She collaborates on projects involving first-principles calculations and molecular dynamics simulations. Dr. Krcmar has advised numerous undergraduate research projects in computational physics and materials modeling. Selected publications highlight work on shape-memory alloys, semiconductor carrier dynamics, and phase stability in intermetallic systems. Her recent focus on infectious disease modeling reflects an adaptation to pandemic-era challenges in applied physics.

• Heat Transfer
• Thermodynamics
• Mechanical Engineering
• +۳ مورد دیگر

Bahman Litkouhi is a Professor of Mechanical Engineering at Manhattan University, leading the Freshman Engineering Program since 1996. He previously chaired the Mechanical Engineering Department and directed its graduate program (1985-87). His expertise spans heat transfer, inverse problems, and thermal engineering applications. He holds a PhD and MS from Michigan State University in Mechanical Engineering. His teaching focuses on heat transfer, thermodynamics, and mechanical design. Research interests include computational heat transfer modeling, thermal management of automotive lighting systems, bioengineering modeling, and electronic cooling systems. He has consulted for Ford Motor Company since 1991 on thermal/moisture management of auto lamps. His publications address both fundamental heat transfer principles and applied engineering solutions, including seminal works on Green's functions and inverse heat conduction problems.

Kendra Letchworth-Weaverمشاهده پروفایل

دانشیار

• Computational Physics
• Renewable Energy Technology
• Solid-Liquid Interfaces
• +۳ مورد دیگر

Kendra Letchworth-Weaver is an Associate Professor in the Department of Physics & Astronomy at James Madison University (JMU), where she has been since 2018. Her research focuses on computational modeling of solid-liquid interfaces critical to renewable energy technologies, including batteries and water filtration systems. She leverages JMU's high-performance computing resources and open-source software to study atomic-scale phenomena at material surfaces. Dr. Letchworth-Weaver earned her Ph.D. in Theoretical Physics from Cornell University (2016) and a BS in Physics & Mathematics from The College of William and Mary (2007). Her work bridges computational physics with experimental validation, particularly through X-ray reflectivity analysis and density functional theory (DFT). Research Interests: Computational modeling of electrochemical interfaces Materials for energy storage and sustainability Interfacial structure prediction using joint density functional theory (JDFT) Surface science and catalysis Development of computational tools for materials characterization Key Research Trends in Articles: Her publications emphasize computational-experimental synergy, advancing understanding of complex interfaces in energy systems. Recent work includes optimizing strontium titanate surfaces for heteroepitaxy, validating interfacial models via X-ray data, and developing machine learning approaches for materials discovery. Education-focused papers address diversity and inclusion in physics education. Labs & Resources: Her research uses JMU's Madison Accelerator Lab and high-performance computing cluster, complemented by collaborations in theoretical physics and computational chemistry. She actively contributes to open-source software like JDFTx.

Silvana Elena Radescu Cioranescuمشاهده پروفایل

دانشیار

• Applied Physics
• Materials Science
• Computational Physics
• +۳ مورد دیگر

Silvana Elena Radescu Cioranescu is an Associate Professor in the Department of Physics at the University of La Laguna, Spain. She is affiliated with the INM Institute and leads research in the ELSimMat group, focusing on electronic structure and ab initio simulations of materials. Her work bridges applied physics, computational modeling, and high-pressure material science. Dr. Radescu holds a Ph.D. from the University of La Laguna (1998), supervised by Dr. José Fernando Peraza Hernández, with a thesis on structural phase transitions using a 3D Phi4 Hamiltonian model. Her research interests emphasize high-pressure structural stability, electronic properties of novel materials, and computational methods like ab initio simulations. Key areas include semiconductor alloys (Si/Ge), fluorinated carbon nanomaterials, and nuclear waste immobilization materials. Recent studies explore metastable phases under extreme conditions and functional nanosheets prepared via exfoliation. Her publications span over two decades, from early work on scheelite tungstates (2000s) to recent advancements in layered topological semimetals and neutron reflectivity materials. Notably, her group investigates pressure-driven phenomena such as zero thermal expansion materials and sodium-ion dynamics in complex oxides. Labs/Teams: Active member of the ELSimMat group, specializing in first-principles modeling and high-pressure experimental techniques.

Marcello Carioniمشاهده پروفایل

استادیار

• Optimal Transport
• Inverse Problems
• Machine Learning
• +۴ مورد دیگر

Marcello Carioni is an Assistant Professor in Mathematics at the University of Twente, affiliated with the Mathematics of Imaging & AI (MIA) group and the SACS group within the Faculty of Electrical Engineering, Mathematics and Computer Science. His research focuses on optimal transport theory, inverse problems, calculus of variations, and their applications in machine learning and imaging. He holds a PhD in Mathematics from the Max-Planck Institute for the Mathematics in the Sciences (Leipzig), preceded by a M.S. and B.S. in Mathematics from the University of Parma. Education: B.S. (2009, University of Parma), M.S. (2012, University of Parma), PhD (2017, Max-Planck Institute) Research interests include: Dynamic optimal transport and preferential path analysis Sparsity in variational regularization Applications to medical imaging and neural networks Generalized conditional gradient methods Recent work emphasizes sparsity optimization for dynamic inverse problems, Lipschitz spaces in neural networks, and end-to-end reconstruction techniques. His 2025 preprints explore Wasserstein curves and distributionally robust optimization. He has advised PhD students including Christian Amend (2024) and Floor van Maarschalkerwaart (2024).

• Ab initio calculations
• Quantum materials
• Transition metal oxides
• +۵ مورد دیگر

Victor Pardo Castro is an Associate Professor at the Department of Applied Physics, Faculty of Physics, Universidade de Santiago de Compostela (USC). He holds a PhD in Physics from USC (2006), with a thesis on first principles studies of cobalt oxides. His research focuses on ab initio calculations of quantum materials, including transition metal oxides, interfaces, and their electronic, magnetic, and thermoelectric properties. He has held postdoctoral positions at institutions like UC Davis and was a Ramón y Cajal Fellow (2012–2016). Education : BSc in Physics (USC, 1997–2001), PhD in Physics (USC, 2006). Postdoctoral research at USC (2006–2007), UC Davis (2007–2011), and TU Wien (2004–2006). Research : Specializes in computational materials science, particularly in designing functional materials using ab initio methods. Key areas include topological phases in oxides, thermoelectric materials, and magnetism in layered systems. His work bridges theory with experimental validation, contributing to understanding quantum phenomena like charge ordering and phase transitions. Supervision : Advised numerous students, including PhD candidates like Alberto Piñeiro Rodriguez (2013) and Antía Sánchez Botana (2013), and MSc students such as José Luis Lado Villanueva (2013) and Pablo Villar Arribi (2015). Current group members include Adolfo Otero Fumega and Jan Phillips. Membership : Part of the Materials Institute (iMATUS) and the Strategic Grouping in Materials (AEMAT). Research group: LABSIS Systems Laboratory.

Melanie Floryمشاهده پروفایل

پژوهشگر

• Neuroscience of Emotion
• Inclusive Design
• Creative Leadership
• +۳ مورد دیگر

Melanie Flory is a psychologist and neuroscientist leading research and innovation at the Helen Hamlyn Centre for Design (HHCD) at the Royal College of Art (RCA). She serves as the first Associate Director of Research, driving inclusive design methodologies and creative leadership programs. Her role includes developing HHCD’s doctoral and Master's research programs and co-leading initiatives like the creative leadership project integrating neuroscience insights. Previously, she founded MindRheo , a consultancy applying neuroscience and systems thinking to organizational performance. Before that, she held senior academic and clinical roles at Westminster University, the UK Ministry of Defence, and the Trauma Response Unit, focusing on PTSD and brain plasticity in emotion regulation. Her research bridges design, cognitive neuroscience, and systems thinking, with key interests in emotion-cognition interplay and cross-disciplinary innovation. Education & Professional Background Director of MindRheo (2009–present) Senior academic and research leadership roles (2000–2011) at Westminster University, MoD, and UK Trauma Response Unit Global research on war-related PTSD and emotion regulation mechanisms Key Research & Contributions Flory’s work emphasizes: Inclusive design methods in cross-disciplinary projects Neuroscience-driven creative leadership frameworks STEM-to-STEAM educational transitions Applications of emotion connectomics in design Her publications explore intersections between design and neuroscience, with recent focus on leadership transformation through interdisciplinary approaches. Awards & Recognition No explicit scientific awards listed, though her role at HHCD and MindRheo reflects industry and academic influence. Grants & Collaborations Custom executive education for Northumbrian Water Group Collaborations with RCA Schools and Research Centres International research networks in emotion neuroscience and design Labs & Teams Maintains a team at HHCD focused on creative leadership and inclusive design, and leads MindRheo’s organizational development projects.

Oleg Rubelمشاهده پروفایل

دانشیار

• Materials modeling
• Density functional theory
• Solar cells
• +۷ مورد دیگر

Dr. Oleg Rubel is an Associate Professor and Associate Chair (Undergraduate) in the Department of Materials Science and Engineering at McMaster University. His research group focuses on predictive computational modeling and supercomputing to evaluate material properties using first-principles methods, particularly density functional theory (DFT), targeting optoelectronic and quantum materials. Rubel holds a Ph.D. and M.Eng. from Zaporizhzhja Technical University and is a licensed Professional Engineer (P.Eng.) in Canada. His research specialization includes materials modeling, solar cells, lasers, LEDs, quantum materials, and 2D materials, with interdisciplinary applications in energy systems and biomaterials. Key methodologies involve advanced DFT simulations and high-throughput computational studies to explore material properties such as optical transitions, defect tolerance, and electrochemical stability. Dr. Rubel teaches courses such as MATLS 3M03 (Mechanical Behaviour of Materials), MATLS 4K06 (Senior Thesis), and MATLS 4NN3 (Computational Modelling in Materials Engineering at the Nano-scale). His recent publications span topics like kagome lattice analysis, 2D material optical transitions, and zinc-ion battery cathode design, reflecting a strong focus on computational materials discovery and energy storage solutions. While no scientific awards are explicitly listed, his work contributes to innovations in energy systems and nanotechnology. Advising and grants are tied to his research group’s activities, with a focus on training students in computational materials engineering. His research group actively explores labs and teams advancing computational approaches to material design, emphasizing interdisciplinary collaboration across energy, photonics, and nanotechnology domains.