جست‌وجوی استاد و پژوهشگر

Andrey Jivkovمشاهده پروفایل

استاد

• Solid Mechanics
• Fracture Mechanics
• Multiphysics Modelling
• +۵ مورد دیگر

Andrey Jivkov is a Professor of Solid Mechanics at the School of Engineering, University of Manchester. He specializes in multi-scale modeling of material behavior, fracture mechanics, and computational mechanics. His research integrates experimental and theoretical approaches to understand material degradation, deformation, and environmental effects. He holds a PhD from Lund University and has contributed to projects like the MaPoS initiative, focusing on mechanics and physics of solids. Education: PhD, Strain-assisted corrosion cracking, Lund University (2002) MPhil, Crack growth in functionally graded materials, Lulea University (2000) MSc, Earthquake-resistant structural design, University of Architecture, Civil Engineering and Geodesy (1994) Research Interests: Multi-scale modeling of solids Fracture mechanics and structural integrity Coupled multiphysics phenomena Advanced materials for nuclear and aerospace applications Grants & Projects: MaPoS: Mechanics and Physics of Solids (UKRI-funded) ParaGEMS: Integrating discrete exterior calculus into computational frameworks Awards: Chair of European Structural Integrity Society’s Technical Committee 2 (2018) EPSRC Fellowship in Geometric Mechanics of Solids (2016) Scientific Advisory Board Member, IASMiRT (2017) Advising: Currently supervising 8 PhD students across topics like nuclear graphite, peridynamic modeling, and porous media transport. Labs/Teams: Leads the Modelling and Simulation Centre and collaborates with the Dalton Nuclear Institute.

Egemen Kolemenمشاهده پروفایل

دانشیار

• Fusion Energy
• Plasma Physics
• Control Systems
• +۳ مورد دیگر

Egemen Kolemen is an Associate Professor at Princeton University’s Mechanical & Aerospace Engineering Department, with joint appointments at the Andlinger Center for Energy and the Environment and the Princeton Plasma Physics Laboratory (PPPL). He serves as Director of the Program in Sustainable Energy and holds the distinction of ITER Scientist Fellow. His research focuses on enabling economically feasible fusion reactors through engineering and physics analysis, with a strong emphasis on machine learning, real-time diagnostics, and control systems. Dr. Kolemen earned his B.S. from Bogazici University (2002) and Ph.D. from Princeton University (2008). His research integrates advanced computational tools like DESC and FreeMHD with experimental collaborations at KSTAR, NSTX-U, and DIII-D tokamaks. He leads labs developing liquid metal divertors and low-temperature plasma diagnostics, while also advancing software for stellarator optimization and fusion reactor economics. His work bridges plasma physics and control systems, addressing challenges like tearing mode stabilization, edge localized mode (ELM) control, and AI-driven plasma profile prediction. Recent trends in his publications highlight breakthroughs in hybrid physics-AI models for fusion reactor design and real-time plasma diagnostics. Awards: David J. Rose Excellence in Fusion Engineering Award, American Nuclear Society’s Technical Accomplishment Award. Grants/Advising: Oversees research groups and collaborates with international fusion facilities, focusing on long-pulse edge plasma control and liquid metal applications. Labs/Teams: Director of liquid metal divertor and plasma diagnostics labs, co-developer of the DESC computational framework.

• Reduced-Order Modelling
• Machine Learning for Scientific Applications
• Urban and Environmental Flows
• +۶ مورد دیگر

Claire Heaney is an Eric and Wendy Schmidt AI in Science Postdoctoral Fellow affiliated with both Imperial-X and the Department of Earth Science & Engineering within the Faculty of Engineering at Imperial College London . Her research focuses on applying advanced machine learning techniques to complex scientific problems in environmental and computational physics. Research Interests: Reduced-Order Modelling Machine Learning for Scientific Applications Urban and Environmental Flows Scientific Contributions: Claire's work demonstrates expertise in: Neural network-based solutions for partial differential equations Hybrid physics-ML models for environmental systems Uncertainty quantification frameworks Mesh adaptation techniques for improved computational efficiency Her research spans multiple disciplines including applied mathematics, computational fluid dynamics, and nuclear engineering. Scientific Awards: Co-author of one of Wiley's top cited articles (Jan 2021 - Dec 2022) Recipient of the prestigious Schmidt AI in Science Postdoctoral Fellowship Collaborative Research: Claire works at the intersection of earth science and engineering, collaborating across disciplines to develop AI solutions for environmental challenges. Her current research investigates the use of green infrastructure to mitigate air pollution in urban environments.

Larry W. Burggrafمشاهده پروفایل

استاد

• Nuclear Physics
• Quantum Chemistry
• Materials Science
• +۶ مورد دیگر

Dr. Larry W. Burggraf is a Professor of Engineering Physics at the Air Force Institute of Technology (AFIT) within the Graduate School of Engineering's Department of Engineering Physics (ENP). He has held academic and research roles since 1970, including positions at the U.S. Air Force Academy and the Air Force Office of Scientific Research. His expertise spans nuclear measurements, positron spectroscopy, radiation chemistry, and quantum chemistry, with applications in gamma imaging and materials science. Education: Ph.D., Chemistry, University of Denver (1981) Postdoctoral Associate, Computational Chemistry, Iowa State University (1993) M.A., Mathematics, University of West Florida (1977) M.S., Chemistry, The Ohio State University (1971) B.A., Chemistry, Olivet Nazarene University (1968) Research Interests: Dr. Burggraf's research focuses on advanced materials, nuclear radiation measurements, and quantum phenomena. Key areas include positron annihilation spectroscopy, additive manufacturing of materials, electro-optical systems, and quantum entanglement technology. His work bridges theoretical and experimental approaches, with applications in defense, environmental monitoring, and aerospace engineering. Articles Trends: Recent publications emphasize innovations in gamma detection systems, silicon-carbon cluster modeling, and nanoscale material characterization. His work often integrates computational chemistry (e.g., coupled-cluster methods) with experimental techniques like positron spectroscopy and atomic force microscopy. Advising & Grants: While no students are explicitly listed, Dr. Burggraf has led research teams at AFIT and AFTAC, focusing on technology transfer and R&D in materials science and nuclear security. His collaborative projects include work with Nobel laureates Ahmed Zewail (femtochemistry) and Richard Smalley (buckyball discovery). Labs & Teams: He contributes to AFIT's ENP department, leading initiatives in the Materials Science Curriculum and advanced measurement technologies. His lab work includes development of gamma detection systems and characterization of novel materials like colloidal quantum dots and silicon carbide crystals.

Karim Chichaklyمشاهده پروفایل

استاد مدعو

• System Dynamics
• Computer Science
• Complex Systems
• +۵ مورد دیگر

Dr. Karim Chichakly is an Adjunct Professor of Computer Science at Capitol Technology University and Adjunct Professor of System Dynamics at Worcester Polytechnic Institute. He serves as Co-President of isee systems, Inc., a leader in System Dynamics software, where he has led product development and architectural design for over two decades. His work spans modeling projects in healthcare, public policy, environmental systems, and uncrewed systems, with recent focuses on climate change, HIV studies, and suicide prevention. Dr. Chichakly holds a Ph.D. in Computer Science and Complex Systems from the University of Vermont and master's degrees from Worcester Polytechnic Institute (System Dynamics) and Dartmouth College (Electrical and Software Engineering). Education : Ph.D. Computer Science and Complex Systems, University of Vermont (2013) M.S. System Dynamics, Worcester Polytechnic Institute (2010) M.E. Electrical and Software Engineering, Dartmouth College (1986) B.E. Electrical and Software Engineering, Dartmouth College (1981) B.A. Mathematics, Skidmore College (1980) Research Interests : Dr. Chichakly specializes in System Dynamics modeling, simulation for decision support, and the application of computational methods to complex systems. His work emphasizes translating theoretical models into practical tools for policy analysis, project management, and public health. He has pioneered the XMILE standard for model interoperability and contributed to interdisciplinary projects in nanomedicine, environmental systems, and global health. Publications & Presentations : His recent work includes studies on nanomedicine, pandemic response strategies, and public policy coherence. He frequently presents at international conferences, such as the System Dynamics Society meetings, and has led training workshops for Brazilian government agencies on systems thinking in policy design. Service : Dr. Chichakly has held leadership roles in the System Dynamics Society, including Co-Chair of the XMILE Technical Committee and Program Chair for multiple international conferences. He mentors early-career researchers and volunteers for the Brazilian Chapter of the System Dynamics Society. Affiliations : He is actively involved in national and international initiatives, including the National Socio-Environmental Synthesis Center (SESYNC) and the U.S. Department of Energy’s Nuclear Fuel Cycle Simulator project.

• Numerical Analysis
• Optimal Control
• Multi-Agent Systems
• +۵ مورد دیگر

Giacomo Albi is an Associate Professor in Numerical Analysis at the Department of Computer Science, University of Verona. He holds a PhD in Mathematics and Computer Science from the University of Ferrara (2014) and has conducted research at TU München under an ERC project on optimal control. His expertise spans numerical methods for kinetic equations, optimal control of high-dimensional systems, and mathematical modeling of multi-agent systems in socio-economic and biological contexts. Teaching includes modules like Numerical Analysis I, Logistic Optimization, and Foundation of Data Analysis. He leads research in contemporary applied mathematics, focusing on multi-scale particle systems and PDEs. Projects include data-driven control strategies, efficient numerical schemes for PDEs, and computational social dynamics. Active in the INdAM Research Unit, he also contributes to third mission activities and oversees internationalization efforts in Erasmus programs. Research groups involve advanced methods for transport phenomena, high-dimensional control, and computational social dynamics. Key interests include plasma confinement control, opinion-epidemic modeling, and evacuation strategies using multi-scale models.

• Computer Science
• Machine Learning
• Operations Research
• +۵ مورد دیگر

Sam O'Neill is a Lecturer in Computer Science at the College of Science and Engineering. His academic work focuses on applied computational methods across engineering and industrial domains, with strong affiliations to computer science and interdisciplinary research teams. Research interests span: Machine Learning & AI : Development of microservice frameworks for biomedical research and reinforcement learning systems Industrial & Nuclear Engineering : Modular reactor design, off-site construction optimization, and plant layout Operations Research : Network flow modeling, traffic equilibrium, and MILP applications Applied Mathematics : Algorithm design and sequence analysis Publication analysis reveals three primary thematic clusters: Recent focus (2021-2024) on modular nuclear systems and machine learning microservices Sustained work in optimization techniques (MILP formulations, network flows) Foundational research in algorithmic learning theory and mathematical sequences

• Energy Harvesting
• Nonlinear Dynamics
• Vibration Control
• +۳ مورد دیگر

Uchenna Diala is a Senior Lecturer in Electronic and Electrical Engineering at the College of Science and Engineering. His research focuses on energy harvesting, nonlinear dynamics, vibration control, and mathematical modeling of disease spread. He has contributed extensively to advancements in electromagnetic energy harvesters, vibration isolation systems, and acoustic resonance analysis in engineering systems. His work integrates theoretical analysis with practical applications, such as optimizing energy harvesters for low-frequency excitations and developing models for co-circulating diseases like dengue, HIV, and COVID-19. He also explores sustainable technologies, including recycled carbon fiber composites for sensors and renewable energy integration with modular reactors. Key research trends include the use of vibrational resonance to enhance harvester performance, geometric nonlinear damping for vibration control, and data-driven modeling of multiphase reservoirs. His interdisciplinary approach bridges engineering, mathematics, and public health, addressing challenges in energy systems and disease management. Uchenna Diala has published widely in journals such as Nonlinear Dynamics , Scientific Reports , and International Journal of Non-Linear Mechanics . His collaborative projects span industry and academia, emphasizing practical solutions for real-world problems.

Michael G. Schmidtمشاهده پروفایل

استاد

• Hospital-Acquired Infections Control
• Pandemic Preparedness
• Bacterial Pathogenesis
• +۳ مورد دیگر

Michael G. Schmidt is a tenured Professor in the Department of Pharmacology & Immunology at the Medical University of South Carolina (MUSC). He holds academic affiliations with the Colleges of Dentistry, Graduate Studies, and Medicine at MUSC. His primary research focuses on controlling hospital-acquired infections through antimicrobial copper surfaces, pandemic preparedness, and bacterial pathogenesis. He earned his Ph.D. in Microbiology from Indiana University, Bloomington. Schmidt leads interdisciplinary teams investigating microbial transmission in clinical environments, notably demonstrating that copper alloys reduce healthcare-associated infections by 58% through sustained microbial burden reduction. His professional roles include serving as immediate past Chair of the Council for Microbial Sciences (2019-2020), contributing to global summits on SARS-CoV-2, and co-chairing ASM public engagement initiatives. Notably, his work with copper surfaces has been featured in Smithsonian Magazine and Vice , alongside a TEDxCharleston talk. He actively participates in educational missions, reviews scientific literature, and co-hosts the This Week in Microbiology podcast. Research interests extend to phage therapy, mineralization of vapor solvents, and disaster preparedness. His work has been funded by NIH, the Department of Defense, and the Department of Justice. Key achievements include patents on copper-iodide dental materials and antimicrobial adhesives, as well as collaborations with architects and engineers to design infection-resistant clinical environments. Major awards include Fellowships in the American Academy of Microbiology and the American College of Dentists. His interdisciplinary approach bridges microbiology, public health, and clinical practice, addressing critical challenges in infection control and global health emergencies.

• 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.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Jia Liu is a Professor at Tsinghua University's School of Information Science and Technology, Department of Computer Science, with a distinguished research career spanning multiple disciplines in computer science and engineering. Her extensive publication record demonstrates leadership in artificial intelligence, machine learning, and their applications across diverse domains. Dr. Liu's research interests encompass the development and application of advanced computational techniques to solve complex real-world problems. She has pioneered innovative approaches in neural network architectures, medical imaging analysis, remote sensing applications, and multi-agent systems. Her work on Asym-UNet and ThreeF-Net has significantly advanced breast lesion segmentation techniques, while her contributions to digital twin technology have enhanced nuclear reactor operations and Martian exploration systems. Analysis of Dr. Liu's recent publications reveals a strong trend toward interdisciplinary research that bridges theoretical computer science with practical applications in healthcare, environmental monitoring, defense technology, and education. Her work demonstrates consistent innovation in algorithm development, particularly in adapting machine learning techniques to domain-specific challenges. Dr. Liu maintains an active research program with numerous collaborations across academia and industry. Her work on federated learning for dual carbon initiatives reflects her commitment to addressing global sustainability challenges through technological innovation. As an educator, Dr. Liu has developed innovative teaching methodologies that integrate virtual reality and game-based learning, particularly in language education. Her research on interactive e-learning environments demonstrates her dedication to improving educational outcomes through technology.

Zachary Hilliardمشاهده پروفایل

استادیار

• Partial Differential Equations
• Finite Element Methods
• Optimization

Zachary Hilliard is an Assistant Professor in the Science & Mathematics department at Regent University. He holds a Ph.D. in Mathematics (2020) and a B.S. in Mechanical Engineering (2014), both from Washington State University. Previously, he held a post-doctorate position at Oregon State University (2022) and worked at the Pacific Northwest National Laboratory (PNNL). He also taught at Grove Christian School. His research focuses on Partial Differential Equations, Finite Element Methods, and Optimization. Education: B.S. Mechanical Engineering, Washington State University (2014) Ph.D. Mathematics, Washington State University (2020) Research Interests: Partial Differential Equations Finite Element Methods Optimization His work applies mathematical models to fluid dynamics, porous media, and nuclear waste management. Awards: Researcher of the month (W-NAGPS, March 2019) Lab/Team Affiliation: Active in SIAM (Society for Industrial and Applied Mathematics).

• lasers
• optics
• high power lasers
• +۳ مورد دیگر

Gonçalo Figueira is an Associate Professor at the University of Lisbon, affiliated with the Institute of Plasmas and Nuclear Fusion. His research focuses on advanced laser technologies, including high-power lasers, ultra-short lasers, and nonlinear optical phenomena. He teaches courses such as Optics and Lasers, Introduction to Experimental Physics Laboratory, and Music and Mathematics. His work emphasizes spectral broadening, pulse compression, and parametric amplification in various optical systems. Figueira has contributed to the development of ultrafast laser systems and their applications in fields like plasma physics and optical diagnostics. His scientific interests span laser amplification, nonlinear optics, and the design of high-energy laser systems. Recent activities include studies on mid-infrared OPCPA systems, thermal lens analysis in diode-pumped lasers, and pulse front tilt control. Figueira collaborates extensively on projects involving femtosecond pulses, harmonic generation, and advanced laser diagnostics. His research often intersects with plasma physics, exploring phenomena like photon acceleration and relativistic ionization fronts. Despite no explicitly listed awards or grants, his publications reflect significant contributions to laser science and technology. Key technical areas include the optimization of Yb-doped laser amplifiers, dispersion compensation in high-power systems, and the use of nonlinear crystals such as BiBO and YCOB for ultra-broadband applications. Figueira’s work aims to advance laser capabilities for applications in high-intensity physics, optical communications, and fundamental studies of light-matter interactions.

Joanna Panecka-Hofmanمشاهده پروفایل

استاد مدعو

• Molecular Modeling
• Drug Design
• Enzyme Dynamics
• +۳ مورد دیگر

Dr. Joanna Panecka-Hofman is an Adjunct Professor at the Faculty of Physics, University of Warsaw, within the Division of Biophysics at the Institute of Experimental Physics. Her research focuses on molecular modeling for drug design, particularly targeting trypanosomatid parasites. She has held roles at the Centre of New Technologies (Warsaw) and the Heidelberg Institute for Theoretical Studies (Germany), contributing to projects like NMTrypI and the SONATA NCN grant-funded PTR1 dynamics study. Education & Career: PhD under Prof. Joanna Trylska (Faculty of Physics, University of Warsaw) Postdoc in Prof. Rebecca Wade's group (Heidelberg Institute for Theoretical Studies) Collaborations with BIOMS (Heidelberg University) and the Interdisciplinary Centre for Mathematical and Computational Modelling (Warsaw) Research Interests: Mechanisms of enzyme activity modulation, particularly PTR1 and nucleotidases Allosteric regulation and drug binding dynamics Computational tools for predicting protein flexibility (e.g., TRAPP webserver) Grants & Projects: Principal Investigator of SONATA NCN grant (2017–2022) on PTR1 dynamics EU-funded New Medicines for Trypanosomatidic Infections (2015–2016) TEAM grant participant (FNP, 2009–2012) on antisense PNA antibiotics Labs & Teams: A core member of the Biomolecular Machines Laboratory at Warsaw's Centre of New Technologies, focusing on antibiotic and antiparasitic drug discovery through molecular dynamics simulations and structure-based design.

Isabelle Baraffeمشاهده پروفایل

استاد

• Stellar Astrophysics
• Planetary Physics
• Exoplanets
• +۷ مورد دیگر

Isabelle Baraffe is a Professor of Astrophysics at the University of Exeter (UK) since 2010, on secondment from her previous role as Professor at the Centre de Recherche Astrophysique de Lyon (CRAL) in France. She holds a PhD from the University of Paris VII and University of Göttingen. Her research focuses on stellar and planetary physics, exoplanets, and brown dwarfs, with groundbreaking contributions to evolutionary models of substellar objects. She has led the Astrophysics Group at Exeter (2010–2020) and secured two Advanced ERC grants (2012, 2018) and multiple STFC grants. Her work includes developing MUltidimensional Stellar Implicit Code (MUSIC) for 3D stellar modeling and the ATMO 2020 atmosphere models for cool stars and exoplanets. Key achievements involve explaining brown dwarf observational properties, predicting exoplanet evolution, and advancing accretion physics for low-mass stars. She serves on committees including the European Southern Observatory (ESO) Science Advisory Committee and the Max-Planck Institute for Astrophysics Scientific Board. Awards: 2024 Fred Hoyle Medal, 2023 Lodewijk Woltjer Lecture, 2020 Viktor Ambartsumian Prize Grants: Two ERC Advanced Grants, STFC grants (2012, 2018, 2024) Labs/Teams: Leading the Exeter Astrophysics Group; involved in international collaborations like MUSIC and ATMO projects