جست‌وجوی استاد و پژوهشگر

Jianhan Chenمشاهده پروفایل

استاد

• Computational Biophysics
• Molecular Modeling
• Biomolecular Simulation
• +۱۲ مورد دیگر

Jianhan Chen is a Professor in the Department of Chemistry at the University of Massachusetts Amherst . He is affiliated with the Graduate Program in Molecular & Cellular Biology and the Institute for Applied Life Sciences (IALS), where he leads the Chen Research Group focused on computational biophysics and biomaterials. Ph.D., University of California, Irvine (2002) B.S., University of Science and Technology of China (1998) His research centers on theoretical and computational methods for studying biophysical and biomedical systems. Key areas include intrinsically disordered proteins , biomolecular condensates , ion channel gating , and multiscale modeling of proteins and RNAs. He has developed advanced algorithms for conformational sampling, implicit solvent models, and GPU-accelerated simulations, with tools such as CHARMM/OpenMM , MMTSB , and HyRes widely distributed. The recent publications (2021–2025) reflect a strong focus on ion channel dynamics (BK, TRP, HCN, TMEM16), phase separation , and machine learning applications in protein function prediction. His work integrates computational modeling with experimental collaboration to study neurodegenerative diseases, drug delivery, and single-molecule dynamics. He has no listed scientific awards in the provided materials. Jianhan Chen actively mentors students and postdoctoral researchers. His lab maintains significant computational infrastructure, including a dedicated GPU cluster ( Pikes ) and access to institutional and national high-performance computing resources. He is involved in training the next generation of computational scientists and encourages applications from students with backgrounds in biochemistry, biophysics, and programming. The Chen Research Group operates within the Life Science Laboratories and is part of broader interdisciplinary initiatives at UMass Amherst, including Models to Medicine and Center for Bioactive Delivery .

Patrick Charcharمشاهده پروفایل

پژوهشگر

• Theoretical and Computational Chemistry
• Analytical Chemistry
• Medicinal and Biomolecular Chemistry
• +۳ مورد دیگر

Dr. Patrick Charchar is a Researcher in the School of Engineering at RMIT University, specializing in the Materials Modelling and Simulation Group. His research focuses on the physics-based molecular modeling of biomolecules and nanomaterials, particularly their interfaces in biomedical and industrial contexts. He holds a Postdoctoral Fellow position and supervises Master's and PhD students in topics like protein misfolding and aggregation phenomena. His work integrates computational and experimental approaches to advance nanomaterial design for drug delivery, biosensors, and contamination-resistant surfaces. Research interests include Theoretical Chemistry, Analytical Chemistry, Medicinal Chemistry, and Biomedical Engineering. Key projects involve developing nanoscale materials for diagnostics, drug delivery, and antimicrobial applications. Collaborations with industry partners like BlueScope (Australia) aim to enhance industrial sustainability and biomedical innovation. Dr. Charchar's research has been recognized through high-impact publications in journals such as Nature Communications , ACS Nano , and Journal of the American Chemical Society . He actively contributes to interdisciplinary teams exploring nanomaterials' mechanical and optical properties, leveraging supercomputing for predictive modeling. His group's work bridges fundamental science and applied engineering, with practical outcomes in healthcare and environmental sustainability.

• Fluid Dynamics
• Computational Physics
• Complex Systems
• +۳ مورد دیگر

Sauro Succi is a Researcher and Research Director at the Istituto dei Sistemi Complessi (CNR, Rome, Italy), concurrently serving as a Research Associate at Harvard University's Physics Department. He holds a visiting fellowship at the Freiburg Institute for Advanced Studies (FRIAS) within the School of Soft Matter Research. His expertise spans computational modeling of complex systems, with emphasis on fluid dynamics across scales—from quantum flows to biopolymer translocation and nanoscale phenomena. Education: BSc in Nuclear Engineering from the University of Bologna, PhD in Plasma Physics from École Polytechnique Fédérale de Lausanne (1987). He has held visiting positions at institutions including Yale, University of Paris, and Queen Mary College London. Research focuses on lattice Boltzmann methods, multiscale simulations, and soft matter physics. Key projects include modeling biological nanopore translocation, carbon nanotube gas flows, and micro-emulsion rheology. His work bridges mesoscopic theory with practical applications in biophysics and nanotechnology. Scientific recognition includes Fellow of the American Physical Society, Alexander von Humboldt Award, and Killam Award. His 200+ publications include seminal works on lattice Boltzmann equations and multiscale fluid dynamics.

Raymond A. Adomaitisمشاهده پروفایل

استاد

• Thin-film manufacturing
• Alternative energy
• Nanomanufacturing
• +۵ مورد دیگر

Raymond A. Adomaitis is a Professor and Associate Chair for Undergraduate Studies in the Department of Chemical and Biomolecular Engineering at the University of Maryland, with a joint appointment at the Institute for Systems Research (ISR). He holds affiliations with the Maryland NanoCenter and the University of Maryland Energy Research Center (UMERC). His research focuses on simulation and design of thin-film manufacturing processes, particularly in microelectronics, alternative energy, and nanomanufacturing. Key areas include atomic layer deposition (ALD) reaction kinetics modeling and advanced reactor design for thin-film deposition. Dr. Adomaitis earned his B.S. and Ph.D. in Chemical Engineering from the Illinois Institute of Technology, followed by postdoctoral research at Princeton University and the ISR. He has received numerous awards, including Fellow of the American Institute of Chemical Engineers (2011), NSF Young Faculty Award (1995), and multiple University of Maryland teaching awards. His research interests emphasize developing physically based models for thin-film deposition processes, including Si CVD, III-V compound epitaxy, and ALD of metal oxide films. He has pioneered techniques like 'nearest uniformity producing profile' optimization for film uniformity control and full-wafer response-surface modeling. Adomaitis teaches undergraduate and graduate courses in solar energy, chemical engineering computations, and process design. His work spans over 50 publications and 10 patents, including innovations in spatially programmable CVD systems and process sensing technologies.

Sara Rozas Azconaمشاهده پروفایل

پژوهشگر

• Atomistic modeling and multiscale simulation of materials
• Energy storage
• Artificial Intelligence and Machine Learning
• +۳ مورد دیگر

Sara Rozas Azcona is a computational chemistry researcher affiliated with the University of Burgos, where she completed her PhD in 2024. Her work focuses on the in silico design of advanced materials for industrial applications, including gas separation and CO 2 conversion. Education: Degree in Chemistry (University of Burgos, 2016) Master's in Advanced Chemistry, specializing in Novel Materials PhD in Computational Chemistry (University of Burgos, 2024) Her research combines quantum methodologies (Density Functional Theory) and classical approaches (Molecular Dynamics) to develop low-melting-point eutectic solvents. She has contributed to European projects like H2020 CO2MPRISE and Horizon WORLD through international research stays in Greece, Argentina, and Italy. Her scientific interests span atomistic modeling , multiscale simulation , energy storage , and the application of AI/ML in material design. She was supported by a grant during her predoctoral stage with the Fluid Analysis and Molecular Simulation Research Group. Labs & Collaborations: Fluid Analysis and Molecular Simulation Research Group (University of Burgos) Monolithos Ltd. (Greece) National Atomic Energy Commission (Argentina) Politecnico di Milano (Italy) Her work aligns with European initiatives to advance sustainable industrial processes through computational chemistry and novel material design.

Emmanuel Alejandro Flores Johnsonمشاهده پروفایل

عضو هیئت علمی

• Composite and hybrid materials
• Metals and alloy materials
• Numerical modelling
• +۹ مورد دیگر

Dr. Emmanuel Alejandro Flores Johnson is an Adjunct Senior Lecturer at the School of Mechanical and Manufacturing Engineering, Faculty of Engineering at the University of New South Wales (UNSW), and a Senior Structural Modeller at the Australian Nuclear Science and Technology Organisation (ANSTO). His research focuses on the performance of advanced structural materials under extreme conditions for applications in the nuclear industry and non-nuclear energy-generation systems using numerical modelling. Dr. Flores Johnson has extensive expertise in developing finite element simulations of non-linear material behaviour, including plasticity, damage and fracture mechanics, impact, and shock behaviour. His work spans various engineering materials and structures, including composites, metal alloys, polymers, concrete and bioinspired materials. He has been involved in international multi-disciplinary collaborations, industry-oriented projects, and defence projects requiring numerical modelling and experimental testing expertise. His research interests include: Composite and hybrid materials Metals and alloy materials Numerical modelling and mechanical characterisation Modelling and simulation Finite element analysis of non-linear material behaviour Plasticity, damage and fracture mechanics Dr. Flores Johnson's publication record demonstrates a strong focus on applying numerical methods to solve complex structural engineering problems, particularly in extreme environments. His recent work shows increasing emphasis on nuclear applications and non-nuclear energy systems, reflecting the growing importance of these sectors in materials research. Dr. Flores Johnson has received recognition for his contributions to structural modelling and materials science through various research collaborations and projects. His work bridges theoretical modelling with practical applications in critical industries. With over a decade of experience in both academic and research organization settings, Dr. Flores Johnson has developed a robust research program that combines advanced numerical techniques with experimental validation to address challenging problems in structural materials science.

Alex Rienscheمشاهده پروفایل

استادیار

• Additive Manufacturing
• Process Simulation
• Digital Twin
• +۴ مورد دیگر

Alex Riensche is a Research Assistant Professor at the University of Oklahoma's College of Engineering, Department of Industrial & Systems Engineering. His work focuses on advanced manufacturing, particularly in additive manufacturing (AM) process simulation, control, digital twin development, and fault detection and prevention in laser powder bed fusion (LPBF) and directed energy deposition (DED) processes. Ph.D. in Industrial & Systems Engineering from Virginia Tech B.S. in Mechanical & Materials Engineering from the University of Nebraska-Lincoln Riensche's research centers on feedforward control of part quality in AM, utilizing modeling approaches to control thermal history and digital twin techniques for real-time property detection and control. His work addresses defect mitigation, microstructure evolution, and material property prediction in LPBF processes. His publications highlight trends in additive manufacturing and process control , with a focus on physics-guided modeling , machine learning , and sensor data integration . His work bridges industrial engineering principles with advanced manufacturing technologies. Riensche is affiliated with the Sooner Advanced Manufacturing Laboratory, where he conducts research on AM modeling and property predictions. His publications appear in journals such as Additive Manufacturing , Materials and Design , and International Journal of Heat and Mass Transfer .

• marine big data storage
• workflow and business process management
• service computing
• +۳ مورد دیگر

Qi He is an Associate Professor at the College of Information Technology, Shanghai Ocean University, serving as a master's tutor and member of the Shanghai Branch of the Chinese Computer Society (CCF). Her academic career bridges computer science and marine applications through interdisciplinary research. Her educational background includes: Ph.D. in Computer Software and Theory from Fudan University Her research focuses on marine big data storage , workflow and business process management , service computing , and cloud computing . She pioneers applications of deep learning in ocean informatics, developing novel frameworks for sea surface temperature forecasting, coastal change detection, and ocean front analysis using multimodal data fusion and transformer architectures. Recent publications (2024-2025) reveal a consistent trend toward transformer-based models and ensemble networks for oceanographic time series prediction and remote sensing. Key contributions address subseasonal forecasting (10-30 day horizon), multiscale periodic pattern recognition, and multimodal entity extraction, demonstrating strong integration of computer vision with marine science challenges. As a master's tutor, she mentors graduate students in ocean informatics. Her active publication record in high-impact journals (including IEEE JSTARS and Applied Sciences) indicates sustained research funding in marine big data infrastructure and computational oceanography, though specific grant details aren't provided in source materials.

Franz M. Geigerمشاهده پروفایل

استاد

• Geochemistry
• Atmospheric Chemistry
• Biophysics
• +۵ مورد دیگر

Franz M. Geiger is a Professor at the Department of Chemistry, Weinberg College of Arts and Sciences, Northwestern University . He serves as the Director of Graduate Curriculum and Executive Editor of The Journal of Physical Chemistry (A, B, C). His affiliations include the Paula M. Trienens Institute for Sustainability and Energy , the International Institute for Nanotechnology , and the Applied Physics Graduate Program . Education: Ph.D., Georgetown University Vordiplom, Technische Universität Berlin Research Interests: Geiger’s group employs laser spectroscopy , mass spectrometry , and computational techniques to study surfaces and interfaces in geochemistry , atmospheric chemistry , and biophysics . Key areas include understanding interfacial water dynamics, dark oxygen production at seafloors, and atmospheric aerosol chemistry. Publication Trends: Recent work spans interfacial charge transfer , water oxidation mechanisms , and terpene autoxidation , published in journals such as Nature Communications , Science Advances , and JACS . Techniques like SHG , SFG , and operando spectroscopy dominate his group’s output. Scientific Awards: ACS National Award Canvassing Committee (2021—2024) Friedrich Wilhelm Bessel Prize (2017) NSF-CAREER Award (2004—2009) Sloan Fellowship (2007—2009) ACS Nobel Laureate Signature Award (2021) Faculty Diversity Award (2016) Advising and Grants: His group has produced notable advisees like Emilie Lozier (Buffett Global Impacts Fellow) and Mavis Boamah (now at PNNL). Grants include NSF-CAREER and NOAA Climate Fellowship . Labs and Collaborations: The Geiger Group collaborates with institutions like PNNL and ANL , focusing on environmental interfaces and interdisciplinary science.

• Quantum Computing
• Hybrid Quantum-Classical Algorithms
• Workflow Scheduling
• +۳ مورد دیگر

Katarzyna Rycerz is a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków, Poland. She holds the academic rank of Lecturer as part of the assistant professors group, with her office located at D-17, ul. Kawiory 21, room II, 3.54. Her research spans quantum computing, hybrid quantum-classical algorithms, and distributed systems, with significant contributions to workflow scheduling and complex network optimization. Dr. Rycerz's primary research focuses on quantum optimization techniques, particularly quantum annealing and variational algorithms applied to combinatorial problems. Her work bridges theoretical quantum computing with practical high-performance computing challenges, including load rebalancing in HPC systems and community detection in complex networks. She has developed software tools like QHyper for hybrid quantum-classical optimization and explored quantum solutions for thermoelectric properties in graphene and quantum game theory paradoxes. Her 15 most recent publications (2019-2025) reveal a dominant trend toward quantum-classical hybrid methods, with 80% focused on quantum annealing applications for workflow scheduling, network analysis, and optimization problems. Key themes include D-Wave system implementations, quantum game theory extensions, and thermoelectric material simulations, demonstrating a consistent shift from earlier multiscale simulation work toward cutting-edge quantum computing applications. No scientific awards are documented in the available information. Details regarding student advising, research grants, laboratory affiliations, or collaborative teams are not provided in the source materials.

• Battery Components
• Lattice-Boltzmann Method
• Nanoscale Engineering
• +۴ مورد دیگر

Martin Lautenschläger is an Associate Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark (SDU Mechatronics), specializing in computational modeling and simulation of advanced engineering systems. His work bridges mechanical engineering and material science through high-performance computing, focusing on battery technologies, fluid dynamics, and nanoscale interactions. Academic Rank: Associate Professor Institution: University of Southern Denmark Research Focus: Battery microstructures, Lattice-Boltzmann methods, nanoscale lubrication, and multiphase flow simulations Research Trends: Recent publications emphasize pore-scale modeling of battery components, electrolyte filling processes, and multiscale approaches to optimize battery performance. His simulations span from molecular dynamics to continuum-level predictions, particularly in lithium-ion and lithium-sulfur systems. Collaborations: Active in interdisciplinary projects with institutions across Europe, focusing on energy storage, computational microstructure analysis, and manufacturing optimization. Teaching: Supervises master's and bachelor's theses in mechanical design, fluid dynamics, and battery technologies, while teaching core courses in mechanical engineering.

Hao Liمشاهده پروفایل

پژوهشگر ارشد

• Topology Optimization
• Mechanical Engineering
• Thermal Systems
• +۲ مورد دیگر

Hao Li is a MSCA Postdoc Fellow and Visiting Scholar at LIP6 , affiliated with the University of Southern Denmark in the Department of Mechanical Engineering . His research focuses on advanced computational methods for topology optimization in thermal, fluid, and structural engineering systems. Education: Not explicitly stated in the provided text. Current Projects: Leading EU-funded research on heat exchanger design using multiscale models and machine learning. Dr. Li's work spans multiscale topology optimization, level-set methods, and fluid-structure interaction, with applications in microchannel cooling, compliant mechanisms, and biodegradable composites. His recent publications highlight advancements in 3D conjugate heat transfer, adaptive meshing, and eigenfrequency maximization. The trends in his research output (2017–2025) emphasize thermal-fluid systems , high-resolution structural optimization , and manufacturable composite designs . Notable subfields include triply periodic minimal surfaces for cooling channels, nonlinear buckling analysis, and phasor-based dehomogenization techniques. Teaching & Supervision: Currently supervising projects on topology optimization frameworks for heat sinks and high heat flux cooling. His past projects (2018–2023) include research on piezoelectric transducers and thermal-fluid system design. Labs & Collaborations: Collaborates with institutions in Japan and France, focusing on experimental validation and industrial applications. His network includes partnerships with researchers in structural mechanics, computational fluid dynamics, and additive manufacturing.

Evgeniy Redekopمشاهده پروفایل

دانشیار

• Catalysis
• Chemistry
• Energy
• +۷ مورد دیگر

Evgeniy Redekop is an Associate Professor at the University of Oslo , Department of Chemistry. His research focuses on sustainability-relevant catalytic reactions, combining time-resolved perturbation-enhanced kinetics (TAP) , in situ spectroscopy (AP-XPS, IR, XAS) , and multiscale modeling to decode molecular mechanisms. His work spans University of Oslo collaborations, including projects like NanoReactor, TAPXPS, TOMOCAT, and intriCAT. Research interests include: Zeolite- and MOF-catalyzed alkene conversion Metal/oxide-catalyzed CO 2 hydrogenation Selective oxidation on bimetallic surfaces Dynamic processes in reaction/diffusion systems Next-generation materials characterization tools Recent publications highlight 2024 studies on CO 2 hydrogenation zeotypes and 2023 work on ZnZrOx catalyst volatility , alongside 2022 investigations into TAP-AP-XPS synergy for ALD-derived catalysts. His methodologies bridge transient kinetics and surface spectroscopy , advancing understanding of material stability and catalytic efficiency . Contact: evgeniyr@smn.uio.no | Office: ØU40, Department of Chemistry, Sem Sælands vei 26, Oslo

Yi-Lung Moمشاهده پروفایل

استاد

• Structural Engineering
• Seismic Engineering
• Composite Materials
• +۶ مورد دیگر

Yi-Lung Mo , Ph.D., P.E., is a Moores Professor at the University of Houston in the College of Engineering , Department of Civil and Environmental Engineering. With a Ph.D. in Structural Engineering from the University of Hannover (1982), he has held academic and leadership roles, including Director of the Thomas T.C. Hsu Structural Research Laboratory (2003–2016) and Advisor to the National Center for Research on Earthquake Engineering (2003–2009, 2011–2016, 2019–Present).

• Molecular Computer Simulations
• Force Field Development
• Coarse-Grained Modeling
• +۷ مورد دیگر

Alexander Lyubartsev is a Professor at the Department of Chemistry in Stockholm University, specializing in Molecular Computer Simulations . His research bridges fundamental physical chemistry with applied computational modeling, focusing on biomembranes, DNA-chromatin structures, inorganic surfaces, and multiscale method development. He teaches courses like Physical Chemistry (15 hp) and Chemical Modeling (7.5 hp) , mentoring students in computational approaches for molecular systems. Education: PhD in Molecular Biophysics (1988), St. Petersburg State University Academic Positions: 1988-1992: Researcher, St. Petersburg State University 1993-2001: Research Associate, Stockholm University 2001-2007: Associate Professor, Stockholm University 2007-present: Professor, Stockholm University His research interests center on developing computational methods for molecular systems. Key areas include: Force Field Development : Slipids for lipids, inorganic surfaces (TiO2, ZnO), zeolite interactions Coarse-Grained Modeling : DNA, nucleosome core particles, and multiscale approaches using inverse Monte Carlo Advanced Sampling : Expanded ensemble techniques, metadynamics for free energy calculations Software Development : MDynamix for molecular dynamics, MagiC for coarse-graining The articles reflect his focus on: Modeling G-quadruplex elasticity under variable ionic conditions (2017) Extending Slipids force field to polyunsaturated lipids (2016) Analyzing polyelectrolyte conformational transitions with Monte Carlo methods (2017) Investigating ion-DNA binding specificity through molecular dynamics (2016) Developing transferable potentials for gas adsorption in zeolites (2016) Studying TiO2 nanoparticle wetting mechanisms via ab initio simulations (2016) His methodological contributions include inverse Monte Carlo coarse-graining, systematic force field optimization, and multiscale approaches for chromatin components. The research directly impacts drug design, nanotoxicity modeling, and materials science applications.