جست‌وجوی استاد و پژوهشگر

C. Armando Duarteمشاهده پروفایل

استاد

• Computational Mechanics
• Structural Engineering
• Multiscale Modeling
• +۵ مورد دیگر

Prof. C. Armando Duarte is the Nathan M. Newmark Distinguished Professor in Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign (UIUC). He holds affiliations with the Computational Science and Engineering Program and the National Center for Supercomputing Applications (NCSA). His research focuses on computational mechanics, particularly the Generalized Finite Element Method (GFEM/XFEM), multiscale modeling, fracture mechanics, and hydraulic fracturing. He has authored/co-authored over 100 publications and co-edited books on computational methods. Education: Ph.D. (1996) and M.Sc. (1991) in Engineering Mechanics from the University of Texas at Austin and Federal University of Santa Catarina, respectively, and a B.Sc. in Mechanical Engineering from the Federal University of Pernambuco. Professional Roles: Professor at UIUC since 2015, previously at the University of Alberta and visiting roles at institutions in Brazil, Portugal, and the Netherlands. He serves on editorial boards of computational mechanics journals and chairs committees for professional societies like USACM and ASCE. Research Interests: Multiscale problems, computational fracture mechanics, meshfree methods, and multiphysics simulations. His work emphasizes 3D fracture analysis, hydraulic fracturing, and thermal gradient modeling. Awards: Recognitions include the Nathan Newmark Professorship, USACM Fellowship, and multiple best paper awards. His work has been cited over 9,000 times, with papers featured in top journals like Computer Methods in Applied Mechanics and Engineering . Teaching: Renowned for excellence in courses like Finite Element Methods, Structural Analysis, and Computational Plates and Shells. His teaching accolades span over two decades at UIUC.

Aiichiro Nakanoمشاهده پروفایل

استاد

• Computational Science
• Scientific Machine Learning
• Materials Simulation
• +۲ مورد دیگر

Aiichiro Nakano is Professor of Computer Science with joint appointments in Physics & Astronomy, Quantitative & Computational Biology, and the Collaboratory for Advanced Computing and Simulations at USC. He holds a Ph.D. in physics from University of Tokyo (1989) and has authored over 485 refereed publications in scalable algorithms, scientific machine learning, and computational materials science. Research develops AI-driven simulation methods for materials discovery, quantum computing applications, and exascale molecular dynamics. Recent work focuses on foundation models for molecular simulations, high-energy-density polymers, and nanocatalysis under extreme conditions. Publications show consistent contributions to computational science infrastructure, with accelerating focus on machine learning interatomic potentials and quantum-classical computing integration. Research bridges theoretical development with high-performance computing implementations. National Science Foundation CAREER Award

Aniket Ambekarمشاهده پروفایل

پژوهشگر ارشد

• Multiphase Flow
• Fluid Mechanics
• Computational Fluid Dynamics
• +۳ مورد دیگر

Aniket Ambekar is a Research Fellow at the Department of Chemical Engineering and Chemistry, Eindhoven University of Technology. His research focuses on multiphase flow dynamics in porous media, with expertise in computational fluid dynamics (CFD) and experimental validation techniques. He holds a PhD in Chemical Engineering from the Indian Institute of Technology Delhi (2022), an MSc in Computational Fluid Dynamics from National Institute of Technology (2016), and a BSc in Chemical Technology from the University of Pune (2013). Research interests include packed bed hydrodynamics, gas-liquid flow mechanisms, and the role of wettability in two-phase systems. His work combines high-resolution simulations (e.g., volume-of-fluid method) with experimental measurements to study flow regimes, interfacial dynamics, and phase distribution. Notable contributions address perforation effects in structured packings, particle aspect ratio impacts, and monolith gas-liquid interactions. He has received prestigious awards including the Marie Skłodowska-Curie postdoctoral fellowship (2022) and the Outstanding Ph.D. Thesis Award (2024). Collaborations span European institutions, focusing on energy-efficient separation processes and reactor design optimization.

Monika Nedaمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Turbulence
• Numerical Methods for Partial Differential Equations
• +۴ مورد دیگر

Monika Neda is a Professor in the Department of Mathematical Sciences and Associate Dean for Research at the University of Nevada, Las Vegas (UNLV). She holds a Ph.D. in Mathematics from the University of Pittsburgh (2007) and a B.S. in Mechanical Engineering from the Technical Faculty Mihajlo Pupin in Serbia (2001). Her research focuses on theoretical and computational fluid dynamics, turbulence modeling, and numerical methods for partial differential equations, with particular emphasis on Navier-Stokes equations and sensitivity analysis. Her work explores model derivation, numerical stability, finite element error estimates, and computational simulations of fluid flow problems. She also investigates educational strategies to improve STEM students' foundational math skills through game-based and activity-based instruction. Neda is affiliated with UNLV's Center for Applied Math & Statistics and has contributed to interdisciplinary projects involving engineering education and photovoltaic panel efficiency. Recent research trends highlight advancements in stabilization techniques for fluid models (e.g., time relaxation, deconvolution operators) and innovative pedagogical approaches leveraging technology platforms like Canvas. Her publications span computational mathematics, turbulence closure models, and education-focused interventions. Neda's academic leadership includes roles in curriculum development and institutional research, reflecting her dual commitment to scholarship and academic administration.

Ignacio Castilloمشاهده پروفایل

استاد

• Facility Location
• Operations Research
• Supply Chain Management
• +۳ مورد دیگر

Ignacio Castillo is a Professor and Associate Dean of Business (Graduate Academic Programs) at the Lazaridis School of Business and Economics, Wilfrid Laurier University. His expertise spans facility location optimization, supply chain management, and sustainable operations. He holds a leadership role in graduate academic programming and teaches courses in operations and statistics. Research focuses on optimizing facility layouts, material handling systems, and closed-loop supply chains. He has developed frameworks for multi-objective facility design and advanced packing optimization algorithms. His work bridges theoretical models with real-world applications in manufacturing and retail sectors. Publications emphasize nonlinear optimization techniques, packing problems, and supply chain coordination strategies. Recent work explores irregular object configurations and retail category space optimization. His textbooks include Business Statistics for Contemporary Decision Making and Operations Management , emphasizing practical decision-making tools. Office: LH4001M | Languages: English, Spanish

Ahmet Avsarمشاهده پروفایل

استادیار

• Spintronics
• 2D Materials
• Quantum Devices
• +۳ مورد دیگر

Dr. Ahmet Avsar is an Assistant Professor and NRF Fellow in the Department of Material Science and Engineering at the National University of Singapore (NUS), appointed since September 2022. Prior to this, he served as an Assistant Professor of Physics at Newcastle University (UK) and held an EPFL Fellowship (co-funded by the European Marie Curie COFUND) at the Swiss Federal Institute of Technology Lausanne (EPFL, Switzerland) from 2016 to 2020. He completed his PhD in Physics at NUS. His research focuses on exploiting quantum degrees of freedom (spin, pseudospin, valley) in atomically thin materials for energy-efficient information technologies. This includes fabricating mesoscopic devices with 2D heterostructures and studying their electronic, magnetic, and optical properties at low temperatures. His work emphasizes sustainable computing through spin, magnon, and superconducting quasiparticle-based information processing. Key research areas include spintronics in graphene and 2D materials, van der Waals magnetism, excitonic devices, and low-temperature characterization. His recent projects explore anisotropic spin transport in black phosphorus, valleytronics, and logic-in-memory systems using atomically thin semiconductors. Dr. Avsar has been recognized as an NRF Fellow and EPFL Fellow. His research is supported by the National Research Foundation (NRF) of Singapore. He has authored or co-authored numerous high-impact publications in journals like Nature Materials , Nature Nanotechnology , and Review of Modern Physics . His academic trajectory includes postdoctoral research at EPFL and prior roles in the UK, reflecting a trajectory of excellence in quantum materials and nanotechnology research.

Jasmin Jahicمشاهده پروفایل

پژوهشگر

• Concurrent Computing
• Software Engineering
• Embedded Systems
• +۳ مورد دیگر

Jasmin Jahic is a Researcher at the Computer Architecture Group of the University of Cambridge, working under Timothy M. Jones. She holds a PhD in 'Supervised Testing of Embedded Concurrent Software' from the University of Kaiserslautern (2020) and has extensive experience as a researcher and project manager at the Fraunhofer Institute for Experimental Software Engineering. Her research focuses on concurrency in embedded systems, software engineering, AI integration, and low-power systems. Education: PhD in Computer Science from the University of Kaiserslautern (2020). Prior roles include Project Manager at Fraunhofer IESE and Coordinator of the European Master Program in Software Engineering. Research Interests: Concurrent computing, embedded systems architecture, AI applications in software engineering, and low-power system design. She explores concurrency bugs, synchronization mechanisms, and software architecture evolution in the context of Industry 4.0 and autonomous systems. Professional Activities: Co-Organizer of SAMOS workshops (2018–2021), Reviewer for IEEE/ACM conferences, and contributor to European Strategic Research Agendas for embedded systems. Teaches courses on software architectures for embedded systems and supervises numerous graduate students. Key Contributions: Frameworks like BOSMI for multithreaded software testing, FERA for concurrency bug detection, and research on AI adoption in traditional embedded systems. Active in HiPEAC conferences and industry partnerships.

• Cold-Formed Steel Structures
• Buckling and Post-Buckling Behavior
• Meshfree Methods
• +۶ مورد دیگر

Dr. Mani Khezri is a Lecturer in the School of Civil Engineering at The University of Sydney since 2014, specializing in structural mechanics and innovative numerical methods. His research focuses on cold-formed steel structures, buckling behavior of plates and laminated assemblies, and functionalizing buckling for structural morphing. He holds a Ph.D. in Structural Engineering from UNSW, an M.Sc. from SUT, and a B.Sc. from IUT. Key research areas include extending cold-formed steel applications to mid-rise structures through built-up sections, analyzing buckling and post-buckling behaviors, and leveraging buckling for smart technologies like kinetic façades. He collaborates with industry to develop affordable, prefabricated structures and sustainable materials through additive manufacturing. His work bridges theoretical analysis (e.g., meshfree methods) with practical applications, such as optimizing ventilation systems via buckling-induced airflow control. He leads grants like 'Solid-State Additive Manufacturing For Recycled Aluminium Alloys' and 'Complete limit state analysis of steel structural framework.' Students include Pouya AFSHAR IMANI (additive manufacturing), Cynthia LIU (built-up columns), Emad TAYARANINAJJARAN (floor systems), and Ruilin ZHANG (serviceability analysis). His lab, the Centre for Advanced Structural Engineering, explores advanced structural systems and computational mechanics.

Nabil Kahaleمشاهده پروفایل

دانشیار

• Financial Derivatives
• Monte Carlo Methods
• Optimization
• +۳ مورد دیگر

Nabil Kahale is an Associate Professor of Finance at ESCP Business School in Paris. His research focuses on financial derivatives, Monte Carlo methods, optimization, and machine learning. He holds a PhD in theoretical computer science from MIT (1993) and an HDR (French habilitation) from Université Paris 1 Panthéon-Sorbonne (2020), enabling him to supervise PhD students. His academic career includes prior roles in theoretical computer science and consulting for banks. He has published widely in top journals such as Mathematical Finance , Management Science , and SIAM Journal on Computing . Education: Bachelor of Science in Engineering, École Polytechnique (1987) PhD in Theoretical Computer Science, MIT (1993) HDR in Economics, Université Paris 1 Panthéon-Sorbonne (2020) Research Interests: His work bridges finance and computational methods, emphasizing practical applications of stochastic models and algorithmic efficiency. Key areas include derivative pricing, risk management, and the integration of machine learning into financial systems. Professional Contributions: He has served as a consultant for banking institutions and a referee for the French Ministry of Economy and Finance. His research also intersects with social and economic policy analysis, such as evaluating the economic impact of public health measures. Labs/Teams: While no specific lab affiliation is mentioned, his collaborations span interdisciplinary teams in finance, computer science, and applied mathematics through his publications and consulting work.

Tequila A. L. Harrisمشاهده پروفایل

استاد

• Manufacturing
• Fluid Mechanics
• Polymer Processing
• +۳ مورد دیگر

Tequila A. L. Harris is a Professor in the Department of Mechanical Engineering at Georgia Institute of Technology. Her research focuses on manufacturing processes, fluid mechanics, and polymer thin film processing, with applications in energy systems, flexible electronics, and environmental technologies. Education: Ph.D., Rensselaer Polytechnic Institute (2006) M.S., Rensselaer Polytechnic Institute (2003) B.S., Lane College (2000) Dr. Harris investigates the relationship between manufacturing processes and the durability of polymer thin films, particularly in energy systems like polymer electrolyte membrane fuel cells (PEMFCs). Her work combines simulations and experimentation to study defect formation, fluid transport in porous media, and hybrid manufacturing techniques for scalable production. Recent publications highlight her expertise in wetting phenomena, computational modeling of polymer membranes, and fluid dynamics in gas diffusion layers. Her research addresses challenges in manufacturing efficiency, material sustainability, and system optimization. Scientific Awards: National Science Foundation Faculty Early Career Award Lockheed Inspirational Young Faculty Award ISCST L.E. Scriven Young Investigator Award United Negro College Fund Young Alumnus Award of the Year General Electric Faculty of the Future Fellow Dr. Harris advises a research group working on roll-to-roll manufacturing systems, with recent milestones including successful thesis defenses and program acceptances by her students. She leads the Highly Advanced Roll-to-Roll iManufacturing Systems (HARRiS Group), which explores scalable production methods for flexible electronics and energy systems.

Gerd Masselinkمشاهده پروفایل

استاد

• Coastal Geomorphology
• Climate Change Impacts
• Extreme Storm Dynamics
• +۵ مورد دیگر

Professor Gerd Masselink is a leading authority on coastal geomorphology at the University of Plymouth, specifically in the School of Biological and Marine Sciences. He heads the Coastal Processes Research Group (CPRG), the largest such group in the UK, specializing in extreme storm impacts, climate change adaptation, and coastal management. His work spans global research, including coral reef islands, sediment dynamics, and beach hazard mitigation. He holds a PhD from Sydney University and has over 25 years of field and numerical modeling expertise, with 150+ publications (h-index 68). Current projects include the EA-funded 'Making Space for Sand' and UKRI's ARISE project on atoll resilience. He co-founded CMAR consultancy and authored textbooks like Introduction to Coastal Processes and Geomorphology . Research focuses on extreme storms' coastal effects, including erosion, flooding, and dune dynamics. He supervises 25+ PhD students and collaborates internationally on rip current forecasting, sediment budgets, and climate adaptation strategies. His work informs coastal policy and safety, such as RNLI beach hazard research and UK National Marine Park initiatives.

Jonathan Hurstمشاهده پروفایل

استاد

• Robotics
• Legged Locomotion
• Biomechanics
• +۴ مورد دیگر

Jonathan W. Hurst is a Professor of Robotics at Oregon State University's College of Engineering, Mechanical, Industrial, and Manufacturing Engineering department. He co-founded the Oregon State University Robotics Institute and serves as CTO and co-founder of Agility Robotics. He holds degrees from Carnegie Mellon University: B.S. in Mechanical Engineering, and M.S./Ph.D. in Robotics. His research focuses on legged locomotion fundamentals, merging machine learning with traditional control methods to achieve advanced robotic mobility. Education: B.S. Mechanical Engineering (Carnegie Mellon), M.S. and Ph.D. Robotics (Carnegie Melllon). Research emphasizes numerical studies, animal data analysis, simulation models, and physical robot prototyping. Key areas include dynamic gaits, passive compliance in movement, and bio-inspired design. His work aims to enable robots to navigate environments like humans, with commercial applications via Agility Robotics. Awards include the 2018 OSU Faculty Innovator Award, Engelbrecht Young Faculty Award (2014), and Popular Mechanics Breakthrough Innovators recognition (2012). He leads the Dynamic Robotics Laboratory and collaborates on projects such as the Cassie robot. Grants and industry partnerships support his research, advancing robotics for economic productivity and quality-of-life improvements. His lab integrates academic and applied research, producing both scholarly publications and commercializable technologies.

• Complex Systems Modeling
• Computational Mathematics
• Applied Mathematics
• +۷ مورد دیگر

Yannis Kevrekidis is a Professor at Princeton University with a distinguished career in computational mathematics and chemical engineering. He is currently a Hans Fischer Senior Fellow at the Technical University of Munich (TUM-IAS) and has held visiting positions at institutions like the Zuse Institute Berlin and Caltech. Education : National Technical University of Athens (Chemical Engineering) University of Minnesota (PhD in dynamical systems) Research Interests : Equation-Free and Variable-Free Modeling Complex Systems Dynamics Multiscale Computation Integration of Machine Learning with Scientific Computing Pattern Formation & Instability Analysis Key Article Trends : Advanced data-driven modeling of dynamical systems Manifold learning for reaction coordinates Projective integration methods Coarse-grained modeling across disciplines Applications in epidemiology, neuroscience, and fluid dynamics Scientific Awards : Guggenheim Fellowship Humboldt Research Award Computing in Chemical Engineering Award (AIChE) Bodossaki Academic Award Allan P. Colburn Award Collaborations : Extensive international collaborations with institutions in Germany, Austria, and the UK Key role in the Complex Systems Modeling and Computation focus group at TUM-IAS

Joe Geunesمشاهده پروفایل

استاد

• Production Planning
• Supply Chain Management
• Logistics
• +۳ مورد دیگر

Joe Geunes is a Professor and Associate Department Head for Graduate Affairs in the Department of Industrial & Systems Engineering at Texas A&M University, holding the Mike and Sugar Barnes Professorship. His research focuses on production planning, supply chain management, logistics, and operations optimization. He earned his Ph.D. in Business Administration (Management Science & Operations Research) and M.B.A. from The Pennsylvania State University in 1999 and 1993, respectively. Dr. Geunes has received notable accolades including Fellow of the Institute of Industrial Engineers (2015), Marilyn and L. David Black Faculty Fellow (2022), and Best Reviewer Award from Omega (2022). His work spans infrastructure network restoration, supply chain resilience, and optimization algorithms for logistics systems. Recent projects address railcar operations, distribution network fortification, and disaster response strategies. Education: Ph.D., Business Administration (Management Science & Operations Research), The Pennsylvania State University – 1999 M.B.A., The Pennsylvania State University – 1993 Awards: Fellow, Institute of Industrial Engineers – 2015 Marilyn and L. David Black Faculty Fellow – 2022 Best Reviewer Award, Omega – 2022 Best Application Paper, IISE – 2018 His research integrates mathematical modeling and computational methods to address real-world challenges in supply chain design, inventory management, and infrastructure resilience. Recent publications emphasize multi-modal logistics, robust optimization under uncertainty, and post-disaster network recovery strategies.

• Aerospace Engineering
• Fluid Dynamics
• Computational Fluid Dynamics
• +۳ مورد دیگر

Di Zhou is a Researcher specializing in aerospace engineering and fluid dynamics, focusing on turbulence modeling, aeroacoustics, and computational fluid dynamics (CFD). His work integrates advanced numerical methods such as large-eddy simulation (LES) with machine learning techniques like reinforcement learning to address challenges in wall modeling and flow prediction. Current affiliations are not explicitly stated, but his research involves collaborations in turbulence, rotor noise, and high-Reynolds-number flows. Research interests span turbulent boundary layers, adverse pressure gradients, and rotor aeroacoustic response. He has pioneered the application of multi-agent reinforcement learning for wall modeling in LES, advancing accuracy in simulating complex flows over periodic hills and Gaussian bumps. His studies also explore optimal sensor placement for lift prediction under gust loads and noise generation mechanisms in rotor systems. Recent trends in his publications highlight machine learning-driven turbulence modeling, sensitivity analysis of LES closure models, and computational analysis of rotor ingestion noise. Despite no listed awards, his work contributes significantly to both fundamental fluid dynamics and applied aerospace problems. No specific advising roles or labs are mentioned, but his research likely involves collaboration with experimental and numerical groups in aerodynamics and acoustics.