جست‌وجوی استاد و پژوهشگر

Khaled Mohammedمشاهده پروفایل

پژوهشگر

• Silicon Photonics
• Materials Science
• Photonics Integrated Circuits
• +۳ مورد دیگر

Dr. Khaled Mohammed is a Researcher at the University of Southampton, specializing in silicon photonics and advanced materials characterization. His work focuses on high-speed silicon photonic devices, photonic integrated circuits (PICs), and catalytic applications. He holds a PhD in Chemistry from the University of Southampton (2010–2014), following earlier degrees from Sohag University (BSc, 2001; MSc, 2007). His research interests include the characterization and optimization of modulators and photodetectors for optical communication systems, alongside the development of PIC design and simulation techniques for telecommunications and LiDAR applications. He also explores advanced testing methodologies for improving device reliability. Dr. Mohammed has published extensively in materials science and catalysis, with recent work focusing on palladium nanoparticles, photocatalytic Hg(II) removal, and supercapacitor electrode materials. His interdisciplinary approach bridges catalysis and photonics, leveraging expertise in synchrotron-based characterization methods (X-ray, IR spectroscopy). While no awards are explicitly listed, his active research collaborations and diverse publication topics highlight his contributions to interdisciplinary materials science. No grants or advising roles are noted in the provided information.

James Chapmanمشاهده پروفایل

استادیار

• Computational Materials Informatics
• Machine Learning
• Materials Science
• +۵ مورد دیگر

James Chapman is an Assistant Professor at Boston University, with a dual affiliation in the Departments of Mechanical Engineering and Materials Science & Engineering. His primary appointment is in Mechanical Engineering. He holds a PhD in Materials Science and Engineering from the Georgia Institute of Technology (2020). His research focuses on computational materials informatics, integrating machine learning with atomistic simulations to design novel catalysts and corrosion-resistant materials. Current work emphasizes high-entropy alloys for hydrogen production and pollution mitigation. Key honors include the Junior Faculty Fellow from the Hariri Institute for Computing (2024), the Trusted Reviewer Award from the Institute of Physics (2023), and the Lamar H. Franklin Fellowship (2020). His research lab, the Materials Informatics Lab, explores interdisciplinary approaches at the intersection of machine learning and materials science. Notable contributions include advancements in graph neural networks for material characterization and predictive modeling of atomic structures using diffusion models. Publications highlight themes such as topological message-passing algorithms, stratified data analysis, and multiscale modeling of defects in materials. His work bridges fundamental computational methods with practical applications in energy storage and environmental sustainability.

Brian Van Kotenمشاهده پروفایل

استادیار

• Applied Probability
• Numerical Analysis
• Computer Simulation of Molecular Systems
• +۴ مورد دیگر

Brian Van Koten is an Assistant Professor in the Department of Mathematics and Statistics at the University of Massachusetts Amherst. His research focuses on applied probability and numerical analysis, with applications to molecular systems simulation, variance reduction in statistical physics, and numerical methods for saddle point identification. He teaches courses such as Math 652 (Numerical Analysis II), emphasizing computational methods for partial differential equations and optimization in machine learning. Key research interests include computer simulations of biological and materials systems, rare event sampling techniques, and atomistic/continuum coupling methods. He has presented work at institutions like the Institute for Computational and Experimental Research in Mathematics (ICERM) and the Institute for Pure and Applied Mathematics (IPAM), focusing on topics like stratification for Markov chain Monte Carlo and the string method for minimum energy paths. Van Koten's work bridges theoretical numerical analysis with practical computational challenges, addressing issues in multiscale modeling and error analysis. His teaching philosophy integrates advanced numerical methods with real-world applications, supported by detailed course materials on topics like finite difference methods and optimization algorithms for large-scale data science problems.

• Semiconductor Physics
• Quantum Dots
• Nanostructure Modeling
• +۴ مورد دیگر

Stefan Schulz is a Staff Researcher at the Tyndall Theory, Modelling & Design Centre, University College Cork. His research focuses on electronic and optical properties of semiconductor nanostructures, particularly nitride-based systems such as quantum dots and quantum wells. He holds a PhD and has held postdoctoral fellowships from the Alexander von Humboldt Foundation and the Irish Research Council. Key contributions include studies on polarization fields, alloy fluctuations, and strain effects in III-N materials. Grants include a €448k SFI Starting Investigator Research Grant (2014–2018) and a Royal Irish Academy/Royal Society exchange award (2016–2018). He has supervised doctoral students Miguel A. Caro (PhD 2013) and Patra Saroj Kanta (ongoing), and collaborates with institutions like the Universities of Cambridge, Manchester, and Bremen. Teaching roles include lecturing at UCC's Department of Physics and School of Mathematical Sciences, covering courses in quantum physics and mathematical modeling. His work bridges theoretical physics and materials engineering, with over 50 peer-reviewed publications and conference contributions globally.

Yuanyue Liuمشاهده پروفایل

استادیار

• Materials Science
• Energy Conversion
• Energy Storage
• +۳ مورد دیگر

Yuanyue Liu is an Assistant Professor in the Department of Mechanical Engineering at the University of Texas at Austin, affiliated with the Texas Materials Institute. His research focuses on developing atomistic modeling methods and computational tools to study electronic and energy materials for applications in energy conversion, storage, and next-generation electronics. Education: Bachelor of Science in Materials Science from the University of Science and Technology of China (2008) Doctor of Philosophy in Materials Science from Rice University (2014) Professional Background: Postdoctoral Fellow at the National Renewable Energy Laboratory (NREL) (2013–2014) Resnick Postdoctoral Fellow at Caltech (2014–2015) His research group emphasizes computational studies of novel materials, supported by custom codes like eTran2D. He collaborates with institutions such as the Texas Materials Institute to advance interdisciplinary materials engineering. Notable recognition includes the Resnick Postdoctoral Fellowship. Current affiliations include the Department of Mechanical Engineering and the Texas Materials Institute, with a focus on fostering innovation in energy and electronic materials through atomistic-scale modeling.

Avinash M. Dongareمشاهده پروفایل

استاد

• Computational Materials Science
• Materials in Extreme Environments
• Nanostructured Materials Mechanics
• +۵ مورد دیگر

Professor Avinash M. Dongare is a faculty member in the Department of Materials Science and Engineering at the University of Connecticut, with joint appointments in Mechanical Engineering and Physics. He holds a Ph.D. from the University of Virginia (2008). As Director for Graduate Studies, he oversees graduate programs while advancing research in extreme mechanics and materials science. His research focuses on computational modeling of materials behavior under extreme conditions (e.g., shock, high strain rates, pressures, temperatures). Key areas include: (1) atomistic simulations of phase transformations and spall failure in metals, (2) design of nanocrystalline composites for energy applications, and (3) mesoscale modeling of laser-material interactions. He employs advanced methods like molecular dynamics, density functional theory, and machine learning. Notable achievements include the NSF CAREER Award (2015), UTC Professorship (2018-2021), and TMS Young Leader Award (2015). His work bridges theory and experiment, collaborating with institutions like the US Army Research Laboratory and Oak Ridge National Lab. Over 100 peer-reviewed publications and active funding from NSF, DOE, and DOD highlight his impact in materials science. Current projects explore digital twins for materials processing, interfacial effects in layered systems, and ion-intercalation mechanisms in 2D materials. The Dongare Research Group (GEMMS) integrates computational and experimental approaches to address challenges in additive manufacturing and energy storage technologies.

Mitia Duerinckxمشاهده پروفایل

دانشیار

• Mathematical Physics
• Partial Differential Equations
• Stochastic Homogenization
• +۷ مورد دیگر

Mitia Duerinckx is an Associate Professor in the Mathematics Department at Université Libre de Bruxelles (ULB), Belgium. He holds a joint appointment as CNRS Research Associate at Université Paris-Saclay (LMO), currently on leave since January 2022. His academic career includes positions as F.R.S.-FNRS Research Associate at ULB (2022-2024), Visiting Assistant Professor at UCLA (2020-2022), and various postdoctoral positions at ENS Lyon and ULB. Professor Duerinckx's research focuses on the role of microstructural disorder in mathematical physics, particularly in deriving effective equations and phenomenological laws of continuum physics rigorously from atomistic models, in the tradition of Hilbert's Sixth Problem. His work combines partial differential equations with tools from probability theory, with specific emphasis on particle systems, homogenization theory, scaling limits, and fluid-structure interactions. His current research is supported by an ERC Starting Grant (2023-2028) titled 'Scaling limits of particle systems and microstructural disorder' (PASTIS). His publication record demonstrates consistent contributions to the mathematical understanding of particle systems, homogenization, and effective properties of disordered media. Recent work includes rigorous derivations of effective sedimentation speed and viscosity for random suspensions, analysis of transport-Stokes models for sedimentation, and applications of hyperuniformity concepts to particle systems. His scientific achievements have been recognized through numerous awards including: ERC Starting Grant (2023) BMS Young Scholar Award (2021) Adolphe Wetrems Prize in Mathematics (2019) LMBP PhD Thesis Award (2019) Aguirre-Basualdo Prize (2018) Olbrechts-Tyteca PhD Thesis Award (2018) Professor Duerinckx actively supervises multiple postdoctoral researchers and research interns, currently including Fabrizio Caragiulo, Corentin Le Bihan, Matthieu Ménard, and Elise Bonhomme. He has established a productive research group focused on mathematical aspects of particle systems and microstructural disorder, supported by substantial research funding including the ERC grant and an ARC Advanced Grant 'Partial Differential Equations in Interaction'. He maintains an active presence in the international mathematical community through invited talks at major conferences and workshops, organization of research events, and service as a referee for leading mathematical journals.

Sarah Priceمشاهده پروفایل

استاد

• Physical Chemistry
• Theoretical Chemistry
• Computational Chemistry
• +۳ مورد دیگر

Sarah Price is a Professor of Physical Chemistry at the Department of Chemistry, University College London (UCL). Her research focuses on intermolecular forces, theoretical chemistry, and computational modeling of organic solids, particularly pharmaceutical compounds. She developed the DMACRYS software for predicting organic crystal structures and has collaborated extensively with European research groups to validate computational models against experimental data. Her work bridges quantum mechanics and atomistic modeling, advancing methods for predicting molecular properties in the solid state. Education: B.A. Natural Sciences (1974–1977), Clare College, Cambridge Ph.D. in Theoretical Chemistry (1977–1980), Clare College, Cambridge, supervised by Dr. AJ Stone Dr. Price’s research interests include the development of anisotropic atom-atom models for intermolecular forces, computational prediction of organic crystal structures, and the application of multi-scale modeling to pharmaceutical solids. She pioneered methods to integrate computational predictions with experimental crystallography, enabling the discovery of new polymorphs and guiding experimental efforts. Her work has been adopted by academic and industrial researchers globally. Her scientific accolades include the 2017 Royal Society Fellowship and the 2015 Royal Society of Chemistry Interdisciplinary Prize. She led the European Research Council’s MagnaPharm project (2016) on magnetic control of pharmaceutical polymorphism, demonstrating her leadership in interdisciplinary computational mineral physics. Key Contributions: Development of DMACRYS software Advancing computational methods for pharmaceutical solid-state prediction Collaborative efforts in crystal structure validation

Sukanta Bhowmickمشاهده پروفایل

پژوهشگر

• Tribology
• Materials Science
• Mechanical Engineering
• +۳ مورد دیگر

Sukanta Bhowmick is associated with the University of Windsor and affiliated with the College of Engineering . His research focuses on tribology , materials science , and surface engineering , particularly in the context of coatings technology and mechanical behavior of alloys . Peer Review Contributions to journals like Lubricants and Coatings Active in experimental and computational tribology since 2007 His recent publications highlight advancements in plasma electrolytic oxidation (PEO) , diamond-like carbon (DLC) coatings , and graphene-enhanced lubricants , addressing friction, wear, and machining efficiency in aluminum , magnesium , and titanium alloys . These works span high-temperature testing , nanoscale analysis , and industrial process optimization .

• Computational Materials Science
• Nanomaterials
• Nanotechnology
• +۳ مورد دیگر

Alper Buldum is a Professor in the Department of Mechanical Engineering at the University of Akron's College of Engineering and Polymer Science. He joined the university in 2001 after completing his BS, MS, and PhD in Physics at Bilkent University, Turkey, followed by postdoctoral research at the North Carolina Center for Nanoscale Materials. He has held visiting scientist roles at IBM Almaden Research Laboratories and Harvard University's Department of Chemistry and Biochemistry. His research focuses on computational materials science, nanomaterials properties, and energy storage applications, supported by NSF and NIH grants. With over 50 publications and an h-index of 23, his work has been highlighted in talks by Nobel laureate Richard Smalley. Education : BS, MS, and PhD in Physics, Bilkent University, Turkey (1993-1998) Postdoctoral Research Associate and Research Assistant Professor, University of North Carolina at Chapel Hill (2001) Research Interests : Dr. Buldum investigates the mechanical, electronic, and transport properties of nanomaterials, including graphene, carbon nanotubes, and nanocomposites. His work addresses nanotribology, energy storage systems (e.g., lithium batteries), and molecular modeling of argyrodite electrolytes. He employs computational methods like first-principles calculations and molecular dynamics simulations to explore these phenomena. Grants & Contributions : His research has been funded by NSF and NIH grants. His studies on graphene-lithium interactions and nanotube heterostructures have advanced understanding of energy storage mechanisms. Collaborations with industry and academia (e.g., IBM, Harvard) enhance his experimental validation capabilities. Labs & Teams : While no specific lab name is mentioned, his work aligns with nanotechnology and materials science groups at the University of Akron. His interdisciplinary approach bridges physics, chemistry, and engineering disciplines.

Jiayu Pengمشاهده پروفایل

استادیار

• Materials Science
• Computational Chemistry
• Machine Learning in Materials
• +۴ مورد دیگر

Jiayu Peng is an Assistant Professor in the Department of Materials Design and Innovation at the University at Buffalo, affiliated with the Institute for Artificial Intelligence and Data Science and UB RENEW Institute. He holds a PhD in Materials Science and Engineering from MIT (2022) and a B.Sc. in Applied Physics from the University of Science and Technology of China (2017). His research focuses on combining data science, machine learning, and materials physics to design materials for chemical transformations and energy technologies. Key areas include electrochemical interfaces, catalyst stability, and sustainable materials. His lab develops physics-informed machine learning methods to optimize materials thermodynamics and surface kinetics using atomistic simulations and experimental data. Dr. Peng has been recognized with prestigious awards, including the Forbes 30 Under 30 Asia (2025), IUPAC Green Chemistry Award (2023), and ENFL Future Investigator (2023). His work bridges computational and experimental approaches, emphasizing interdisciplinary training for students in materials modeling, electrochemistry, and AI. His recent publications highlight advancements in machine learning interatomic potentials, cation ordering in perovskites, and confined-water catalysis. He actively collaborates with experimentalists to integrate simulations and data-driven methods for accelerated materials discovery.

• Nuclear Materials Modeling
• Plasma Physics
• Computational Physics
• +۳ مورد دیگر

Dr. Robert Anewandter is an Advanced Nuclear Materials Modelling Research Officer at Bangor University , affiliated with the School of Computing and Electronics . His research focuses on enhancing nuclear fusion reaction rates in hydrated metals through advanced computational methods. He specializes in Monte-Carlo simulations and atomistic modeling to study neutron interactions with materials. Education includes a PhD in Petroleum Engineering from Heriot-Watt University (working with Prof. Sebastian Geiger), where he developed novel methods for CO2 trapping in fractured aquifers. He also holds a Physics Diploma from the University of Hamburg, focusing on verification of underground nuclear explosions. Research interests span nuclear materials design, environmental applications of computational physics, and advanced simulation techniques. Recent work includes a 2024 presentation on Impact of Grain Size Variation of UO2 on Fission Gas Release .

• Computational Physics
• Material Science
• Molecular Dynamics Simulations
• +۳ مورد دیگر

Sami Paavilainen is a University Lecturer in Physics at the Department of Physics, specializing in computational physics and material science. His research focuses on atomistic simulations of nanomaterials, electronic states in nanostructures, and bio-inspired material systems. He holds a Doctor of Science (Technology) from Science and Engineering (2002) and a Master of Science in Engineering Physics (1998). Research interests include molecular dynamics simulations of cellulose nanomaterials, electronic band structures in graphene-like systems, and electron-phonon interactions in nanostructures. His work bridges computational methods with experimental techniques like scanning tunneling microscopy. Recent publications explore molecular graphene properties, cellulose nanofibril behavior, and electronic state formation in atomic vacancies. He actively reviews for journals like Applied Sciences , Carbohydrate Polymers , and Computational Materials Science .

Kun Luمشاهده پروفایل

دانشیار

• Natural Language Processing
• Information Retrieval
• Text Mining
• +۳ مورد دیگر

Kun Lu is an Associate Professor in the School of Library and Information Studies (an iSchool) at The University of Oklahoma, serving as Co-Director of the Data Scholarship Program. His research focuses on applied natural language processing (NLP), information retrieval, text mining, and science informatics. He develops NLP methods for domains like oncology clinical trials, materials science, and Native American literature analysis. His work emphasizes interdisciplinary applications, including improving patient-clinical trial matching and accelerating materials discovery through machine learning. Dr. Lu teaches courses such as Information Retrieval & Text Mining and Database Design, and has secured grants totaling over $750,000 from NIH and institutional seed funds. Key projects include NIH-funded work on clinical trial optimization ($717,666), seed-funded studies on LLM applications in materials design, and HathiTrust-based Native American literature analysis. His award-winning research includes a 2011 Highly Commended Award for health information retrieval interface evaluation. Publications span 35+ peer-reviewed articles in top journals like Scientometrics , Journal of the Association for Information Science and Technology , and PLOS ONE , with recent focus on generative AI, domain-specific NLP, and scientific literature analysis. Affiliations: School of Library and Information Studies, Data Scholarship Program, Dodge Family College of Arts and Sciences Grants: NIH grant (2024-2026), OU seed funds for materials science and clinical trials projects Research Themes: NLP applications, scientometrics, health informatics, interdisciplinary data science

Paolo Raiteriمشاهده پروفایل

استاد

• Computational geochemistry
• Nucleation and growth in aqueous solution
• Materials for energy storage
• +۵ مورد دیگر

Professor Paolo Raiteri is a distinguished academic at Curtin University, serving as a Professor in the School of Molecular and Life Sciences within the Faculty of Science and Engineering. His research focuses on atomistic simulations and free energy calculations, with applications in materials science and computational geochemistry. He has established himself as an expert in computational approaches to understanding mineral dissolution and growth from solution. PhD in Materials Science, University of Milano-Bicocca (Italy), 1999-2003 B Sc(Hon)/MSc in Materials Science, University of Milano-Bicocca (Italy), 1994-1999 Professor Raiteri's research spans multiple areas of computational chemistry and materials science. His primary expertise lies in computational geochemistry, particularly studying dissolution and growth of minerals from solution. He has developed advanced computational techniques including molecular dynamics simulations, free energy calculations, and force field development. His work bridges theoretical approaches with practical applications in materials for energy storage and biomineralization processes. He maintains expertise in programming (Fortran and scripting languages) to implement and optimize computational methods for complex materials systems. Professor Raiteri's publication record demonstrates consistent contributions to computational materials science, with a focus on mineral-water interfaces, nucleation processes, and force field development. His work often involves collaborative research with international teams, applying advanced simulation techniques to understand fundamental processes in geochemistry and materials science. Recent publications show an expanding scope into areas like perovskite materials and computational workflows for complex systems. 2013 ARC Future Fellowship 2013 Senior Research Fellowship, Curtin University 2011 Visiting Professorship from Regione Sardegna, Italy 2009 Australian Research Council Research Fellowship (ARF) 2008 Targeted Research Fellowship, Curtin University 2002 Young Physicist Award, Italian Physics Society 2001 Young Scientist Award, European Materials Research Society 2001 Young Scientist Award, Italian Institute for the Physics of Matter 1999 PhD Scholarship from the Italian Ministry for University and Scientific Research Professor Raiteri has secured significant research funding through prestigious fellowships including ARC Future Fellowships and Research Fellowships. His research program involves close collaboration with computational and experimental groups worldwide. While specific details of his student supervision aren't provided in the profile, his extensive publication record with multiple co-authors suggests active mentoring of graduate students and postdoctoral researchers in computational materials science. Professor Raiteri's research is conducted within the computational chemistry and materials science community at Curtin University. His work leverages high-performance computing resources for molecular simulations and collaborates with experimental groups to validate computational findings. He is actively involved in developing and applying the PLUMED software for enhanced sampling in molecular dynamics simulations, contributing to an important international computational chemistry initiative.