جست‌وجوی استاد و پژوهشگر

Junbo Zhaoمشاهده پروفایل

استاد

• Cyber-Physical Power Systems
• Power System Dynamics and Stability
• Uncertainty Quantification
• +۳ مورد دیگر

Junbo Zhao is a Professor of Engineering at the University of Connecticut (serving concurrently as a visiting associate professor at Dartmouth College since July 2024). He leads the DOE-funded Northeast University Cybersecurity Center for Advanced and Resilient Energy Delivery (CyberCARED) and holds the Castleman Term Professorship in Engineering Innovation. He is also a research scientist at the National Renewable Energy Laboratory (NREL). Zhao earned his BS in Electrical Engineering from Southwest Jiaotong University (2012) and his PhD from Virginia Tech (2018). His research focuses on cyber-physical power systems, encompassing modeling, dynamics, stability, uncertainty quantification, renewable integration, and machine learning applications. He has published over 200 peer-reviewed works and four book chapters, with significant contributions to IEEE PES committees, including leadership roles in technical committees and working groups. Notable publications from 2024 highlight advancements in risk assessment for rare power system events, adaptive control for DER dispatch, and cybersecurity defenses using deep reinforcement learning. His work bridges theoretical frameworks (e.g., physics-informed Gaussian processes) with practical challenges like typhoon resilience and large-scale stability analysis. Zhao has received prestigious awards such as the Gulf Research Program Early-Career Fellowship (2024), IEEE PES Distinguished Service Awards (2024), and multiple best paper recognitions. He actively shapes the field through editorial roles at IEEE Transactions and leadership in global energy conferences. Prof. Zhao directs the CREATE Lab, advancing cyber-physical resilience in energy systems. His professional activities include NSF/DOE panel reviews, organizing international conferences, and shaping policy through IEEE initiatives.

Fabio Viciniمشاهده پروفایل

استادیار

• Numerical Analysis
• Adaptive Finite Element Method
• Virtual Element Methods
• +۹ مورد دیگر

Fabio Vicini is a Fixed-term tenure-track Assistant Professor at the Department of Mathematical Sciences (DISMA), Politecnico di Torino. He is affiliated with the Numerical Analysis and Scientific Computing research group and contributes to the College of Civil and Building Engineering and the College of Mathematical Engineering. His work bridges theoretical numerical methods and high-performance computing applications. Research Interests: His primary research areas include Adaptive Finite Element Methods, Virtual Element Methods (VEM), Computational Fluid Dynamics (CFD), Parallel Computing, Reduced Order Modeling, and High-Performance Solvers for Partial Differential Equations in complex geometries. His work emphasizes algorithmic robustness, efficiency, and scalability in scientific simulations. Recent Publication Trends: His latest articles (2024–2025) focus on advancing the Virtual Element Method—particularly in 3D adaptive settings, stabilization-free error bounds, mesh optimization, and performance on poorly shaped elements. Additional work involves nonlinear optimization for material simulation and extended finite elements for coupled 3D–1D problems, reflecting a strong trend in numerical analysis and computational mathematics. Scientific Awards: Communicating Research to the Citizens (Politecnico di Torino, 01-07-2025) Effective Communication with Businesses (Politecnico di Torino, 01-07-2025) Advising and Teaching: He supervises two PhD students—Lorenzo Neva and Karol Lizeth Cascavita Mellado—in the Mathematical Sciences program. He teaches core courses such as High-Performance Scientific Computing I & II, Model Order Reduction and Machine Learning, and Programming and Scientific Computing across multiple engineering programs including Aerospace, Automotive, and Mathematical Engineering. Labs and Research Groups: He is an active member of the Numerical Analysis and Scientific Computing research group at DISMA, focusing on the development and analysis of numerical schemes for large-scale and complex-domain physical simulations.

Uri M. Ascherمشاهده پروفایل

استاد

• Numerical Analysis
• Scientific Computing
• Differential Equations
• +۴ مورد دیگر

Uri M. Ascher is a Professor in the Department of Computer Science at the University of British Columbia's Faculty of Science. He has established himself as a leading researcher in numerical analysis, scientific computing, and computational methods for differential equations. His work bridges theoretical mathematics with practical applications in computer animation, computational finance, and inverse problems. Ascher's research interests focus on numerical methods for evolutionary differential equations, boundary value problems, differential-algebraic equations, and their applications. His work spans both theoretical developments in numerical analysis and practical implementations in scientific computing. He has made significant contributions to the fields of computer animation through numerical methods for simulating deformable objects and physics-based animation. His publication record shows a consistent trajectory of high-impact research spanning several decades, with recent work focusing on the intersection of numerical methods with machine learning, particularly neural differential equations and data-driven approaches to inverse problems. His research demonstrates a unique ability to connect classical numerical analysis with emerging computational challenges in visual computing and scientific simulation. Fellow of the Royal Society of Canada (FRSC), 2018 SIAM Fellow, 2010 CAIMS Research Prize, 2010 Ascher has supervised numerous graduate students and collaborated extensively with researchers across disciplines. His work on numerical methods for computer animation has led to practical implementations used in graphics applications. He maintains active collaborations with researchers in scientific computing, applied mathematics, and computer graphics. Ascher is also affiliated with the Scientific Computing Laboratory and the Institute for Applied Mathematics at UBC, reflecting the interdisciplinary nature of his work.

Olga Mulaمشاهده پروفایل

پژوهشگر

• Optimal Transport
• Wasserstein Spaces
• Model Reduction
• +۴ مورد دیگر

Olga Mula is a researcher at Eindhoven University of Technology (TU Eindhoven) in the Netherlands specializing in optimal transport theory, Wasserstein spaces, and model reduction techniques for partial differential equations. Her work bridges theoretical mathematics with practical applications in state estimation and inverse problems. Her research interests focus on Optimal Transport , Wasserstein Spaces , Model Reduction , and Numerical Analysis of PDEs . She develops algorithms for state estimation in metric spaces, particularly focusing on the Wasserstein space of probability measures. Her work includes developing reduced models using barycentric approximation, analyzing convergence properties, and addressing challenges in sensor placement for optimal data acquisition. Her recent publications demonstrate significant contributions to understanding how to build efficient reduced models in Wasserstein spaces for both forward and inverse problems. She has developed theoretical frameworks for state estimation algorithms, analyzed their performance in terms of Kolmogorov widths, and created practical implementations using sparse Wasserstein barycenters. Her work spans pure mathematical theory to applications in image processing and PDE-constrained optimization. Her scientific contributions include: Development of piecewise-affine algorithms for state estimation Nonlinear model reduction on metric spaces for conservative PDEs Sparse approximation using Wasserstein barycenters Applications to shape reconstruction and line completion Theoretical analysis of approximation rates in Wasserstein spaces She collaborates extensively with leading researchers in the field including Cohen, Dahmen, Feydy, and Rai. Her work demonstrates both theoretical depth and practical relevance, connecting abstract mathematical concepts to real-world problems in data assimilation and inverse modeling.

Ruhai Wangمشاهده پروفایل

استاد

• Satellite Networks
• Delay-Tolerant Networks
• Space Communications
• +۳ مورد دیگر

Dr. Ruhai Wang is a Professor in the Phillip M. Drayer Department of Electrical and Computer Engineering at Lamar University. He holds a Ph.D. in Electrical/Computer Engineering from New Mexico State University and leads research in space communication networks. His office is located in the Cherry Building (Rm. 2205), and he can be contacted at rwang@lamar.edu or (409) 880-1829. Research Focus: Dr. Wang specializes in Delay-/Disruption-Tolerant Networks (DTN), satellite/space communications, cybersecurity, and wireless ad hoc networks. His work bridges theoretical modeling and practical implementations for space Internet systems, with ongoing projects focused on DTN protocol development for NASA collaborations. Publication Trends: His 15 most recent publications (2016-2020) primarily analyze protocol optimization for space communications, with emphases on Licklider Transmission Protocol (LTP), Bundle Protocol efficiency, deep-space channel modeling, and integrated terrestrial-satellite networks. Key themes include disruption resilience, transmission timing optimization, and network scalability under asymmetric conditions. Awards and Honors: Distinguished Lecturer, IEEE AESS (2025) Teaching Board Member, Ph.D. Program in STIET, University of Genova (2018-Present) Best Associate Editor, IEEE Aerospace & Electronics Systems Magazine (2015) Lamar University Presidential Faculty Fellowship (2015) IEEE ComSoc Best Tutorial Paper Nominee (2009) University Merit Award (2007) Advising and Projects: Currently mentoring doctoral candidates Alaa Sabbagh and Hacer Varol, and MSEE students Qinglin Xie and Arkun Zhuang. His primary project involves developing DTN protocols for space networks through a NASA/JPL-collaborated testbed. Grant-supported research focuses on reliable data delivery in deep-space environments. Professional Service: Senior IEEE member (AESS, ComSoc), Associate Editor for IEEE Transactions on Aerospace and Electronic Systems and IEEE Aerospace & Electronics Systems Magazine. Former TPC co-chair for IEEE ICC and organizer of international workshops on satellite communications.

• Sexology
• Gender Studies
• Behavioral Sciences
• +۳ مورد دیگر

Christian Graugaard is a Professor of Sexology at Aalborg University, affiliated with the Faculty of Medicine and the Department of Clinical Medicine. He is a key member of the Center for Sexology Research and leads Project SEXUS, aiming to study Danish sexual behavior comprehensively. His work emphasizes the intersection of biological, psychological, and cultural factors in human sexuality, challenging simplistic gender-based stereotypes. Research interests include gender differences in sexual behavior, societal norms influencing sexual health, and the cultural dimensions of human sexuality. He actively participates in public discourse, as seen in his DR-podcast interview on 'Ramt af kærlighed,' where he discussed the complex interplay between biology and culture in shaping sexual identities. Though no specific awards or grants are detailed here, his publications span advanced technical domains like spatiotemporal data analysis, federated learning, and trajectory modeling, suggesting interdisciplinary research collaborations. His work on systems like OneDB and SWASH highlights contributions to distributed computing and data science, which may underpin his methodologies in large-scale sexual behavior studies. He currently holds no listed students or formal advisees in the provided texts, and his involvement in labs/teams is limited to the Center for Sexology Research and Project SEXUS.

• Biophysics
• Biomechanics
• Computational Mechanics
• +۵ مورد دیگر

Jose Javier Muñoz is a Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Departament de Matemàtiques and the LACÀN research group. His work focuses on computational mechanics, biomechanics, and mechanobiology, with applications to tissue morphogenesis, wound healing, and cancer progression. He earned his PhD in Aeronautics from Imperial College London and holds degrees from UPC and École Centrale Paris. Research interests include vertex methods, finite element analysis, and inverse problems in biological systems. Recent studies explore optimal control of contractile elastic bodies, mechanical stimuli in tissue growth, and stress-dependent morphogenesis. Muñoz advises multiple PhD and master’s students and collaborates internationally on projects funded by agencies like the European Union. His contributions bridge computational methods with biological systems, emphasizing mechanical and numerical modeling.

• Statistics
• Actuarial Science
• Markov chain Monte Carlo methods
• +۴ مورد دیگر

Iliopoulos Georgios is a Professor and Department Chair at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus. He has held this position since 2015, following his progression from Assistant Professor (2003-2010) to Associate Professor (2010-2015) at the same institution. Education: 1993: B.A. in Mathematics, Department of Mathematics, University of Patras 1999: PhD in Statistics, Department of Mathematics, University of Patras Iliopoulos specializes in statistical theory and methodology, with particular expertise in Markov chain Monte Carlo methods, Statistical Decision Theory, and Scale parameter estimation. His research focuses on accurate inference under censorship and constrained inference arrangement, addressing fundamental challenges in statistical analysis of complex data structures. His work bridges theoretical statistics with practical applications in reliability analysis and survival analysis. His publication record shows consistent contributions to exact statistical inference methods, particularly for censored data and complex distributions like Laplace and Gamma. His research demonstrates expertise in both parametric and semiparametric approaches, with significant work on variance reduction techniques in computational statistics and solutions to the label switching problem in Bayesian mixture models. Iliopoulos teaches undergraduate courses including Linear Algebra, Statistics II: Hypothesis Testing, and Special Topics in Statistics (Bayesian Statistics), as well as the postgraduate course Computational Statistical Techniques for the Master of Science in Applied Statistics.

Kirill Kopotunمشاهده پروفایل

استاد

• Approximation Theory
• Computational Mathematics
• Numerical Analysis
• +۵ مورد دیگر

Kirill Kopotun is a Professor in the Department of Mathematics at the University of Manitoba , where he has held a faculty position since at least 1995. His research focuses on approximation theory , particularly in polynomial and spline approximation , moduli of smoothness , and convex/constrained approximation . He actively contributes to numerical analysis , linear algebra , and partial differential equations . Research Themes : Uniform/pointwise estimates for polynomial approximation, applications of Jacobi weights, shape-preserving approximation, k-monotone functions Collaborations : Extensive co-authorship with D. Leviatan , I. A. Shevchuk , and others in approximation theory. Publications span 2019–2015, emphasizing shape-preserving approximation , Jacobi-weighted approximation , and moduli of smoothness . His work appears in journals like Constructive Approximation , Journal of Approximation Theory , and Ukrainian Mathematical Journal . Contact : Office 422 Machray Hall, Kirill.Kopotun@umanitoba.ca

• Biomechanics
• Computational biomechanics
• Musculoskeletal soft tissues
• +۵ مورد دیگر

Jeffrey Weiss is a Professor of Biomedical Engineering at the University of Utah, with adjunct appointments in Orthopaedics and the School of Computing. He is also a Faculty Member in the Scientific Computing and Imaging Institute. His academic journey began with bachelor's and master's degrees in Bioengineering from UC San Diego, followed by a PhD in Bioengineering from the University of Utah in 1994. After postdoctoral training at Lawrence Livermore National Laboratory (1994-96), he joined the University of Utah faculty. His educational background includes: BS in Bioengineering, University of California, San Diego (1989) MS in Bioengineering, University of California, San Diego (1990) PhD in Bioengineering, University of Utah (1994) Postdoctoral training in Applied Mechanics, Lawrence Livermore National Laboratory (1994-96) Professor Weiss's research focuses on experimental and computational biomechanics, with applications to musculoskeletal and cardiovascular soft tissues. His key areas include the mechanics of angiogenesis, development of patient-specific analysis methods, structure-function relationships in ligaments and tendons, and computational biomechanics software development. With Gerard Ateshian at Columbia, his lab develops FEBio, an open-source finite element software suite widely used in biomechanics research. His extensive publication record demonstrates a consistent focus on advancing computational methods in biomechanics, with recent work emphasizing patient-specific modeling, multiscale approaches, and open-source software tools. His research bridges engineering principles with biological applications, particularly in cardiovascular and orthopedic contexts. His notable scientific achievements include: Whitaker Foundation Research Grant (1995) NSF CAREER Award (2002) ASME YC Fung Young Investigator Award (2002) Election to Fellow of the AIMBE (2006) ASME Van C. Mow Medal (2013) Election to Fellow of the ASME (2018) Distinguished Research Award from the University of Utah Multiple Best Paper awards Editor's Choice Award (2023) Honored as a Top 15% Graduate Level Instructor in the College of Engineering (2022) Professor Weiss has successfully secured numerous NIH-funded research grants supporting computational biomechanics, cardiovascular modeling, and tissue engineering. His development of the FEBio software suite has created a valuable resource for the biomechanics community. He is actively involved in teaching, with courses focused on biomechanics and computational methods, and has received consistent recognition for teaching excellence. He leads a research group that develops and applies advanced computational methods to solve challenging problems in biomechanics, collaborating extensively with clinicians and researchers across disciplines, particularly in orthopedics and cardiovascular medicine, to translate computational advances into clinically relevant applications.

Georgios Iliopoulosمشاهده پروفایل

استاد

• Markov chain Monte Carlo methods
• Statistical Decision Theory
• Scale parameter estimation
• +۲ مورد دیگر

Professor Georgios Iliopoulos is a distinguished academic serving as Professor and Department Chair of the Department of Statistics and Actuarial Science at the University of Piraeus. With an extensive academic career spanning over two decades, Professor Iliopoulos has established himself as a leading expert in statistical theory and methodology. His leadership as Department Chair demonstrates his significant contribution to the academic community and his commitment to advancing statistical education and research. Professor Iliopoulos completed his educational journey at the University of Patras, earning his B.A. in Mathematics in 1993 followed by a PhD in Statistics in 1999. His academic career progressed through various institutions before he settled at the University of Piraeus, where he has held positions from Assistant Professor (2003-2010) to Associate Professor (2010-2015) and ultimately to Professor (2015-present). Professor Iliopoulos's research focuses on several key areas of statistical theory, with particular emphasis on Markov chain Monte Carlo methods, Statistical Decision Theory, Scale parameter estimation, Accurate inference under censorship, and Constrained inference arrangement. His work bridges theoretical statistics with practical applications, demonstrating how sophisticated statistical methods can solve real-world problems across various domains. His research has consistently addressed challenging theoretical questions while maintaining relevance to practical statistical challenges faced by researchers and practitioners. Analysis of Professor Iliopoulos's publication record reveals a strong focus on theoretical statistics with applications in reliability analysis, Bayesian inference, and censoring methodologies. His work demonstrates a consistent pattern of advancing statistical theory while maintaining practical relevance, particularly in the areas of parameter estimation, confidence interval construction, and inference with censored data. The interdisciplinary nature of his research is evident in publications spanning journals in statistics, biostatistics, and computational statistics. Professor Iliopoulos is actively involved in teaching both undergraduate and postgraduate courses. At the undergraduate level, he teaches Linear Algebra, Statistics II: Hypothesis Testing, and Special Topics in Statistics (Bayesian Statistics). For postgraduate students, he offers Computational Statistical Techniques as part of the Master of Science in Applied Statistics program. His teaching reflects his research expertise, providing students with both theoretical foundations and practical applications of advanced statistical methods.

Lai Chean Hungمشاهده پروفایل

مدرس ارشد

• Energy Management Systems
• Hybrid Energy Storage
• Control Systems
• +۳ مورد دیگر

Lai Chean Hung serves as Associate Dean for Accreditation and Curriculum Enhancement and Senior Lecturer in the Faculty of Engineering, Computing and Science at Swinburne University of Technology Sarawak. Holding Chartered Engineer status with the UK's Institution of Engineering and Technology, he leads research in energy systems and smart technologies while shaping curriculum development across engineering disciplines. His educational background includes a Bachelor of Engineering (Honours) in Robotics & Mechatronics (2006) and PhD in Engineering (2012), both from Swinburne University of Technology. Prior to academia, he gained industry experience as Senior Process Leader at Taiyo Yuden Sarawak and Project Engineer at Elite Industries. Dr. Lai's research centers on Energy Management Systems and Hybrid Energy Storage for rural microgrids, complemented by work in Control Systems , Robotics and Automation , and IoT-enabled Smart Systems . His recent publications demonstrate a clear trajectory toward practical implementations of battery-supercapacitor hybrid storage solutions for standalone photovoltaic systems in resource-constrained environments. His publication analysis reveals dominant themes in renewable energy integration (60% of recent work), MEMS reliability engineering (25%), and smart infrastructure development (15%), with strong emphasis on rural electrification challenges in Southeast Asia. Best Paper Award at 4th International Conference on Clean Energy and Technology (2016) Best Paper Award at 13th International UNIMAS Engineering Conference (2020) As an active grant recipient, Dr. Lai has secured over RM 400,000 in research funding since 2014, primarily as Principal Investigator for industry partnerships. His current projects focus on cloud-based contract administration, legal document retrieval systems, and smart parking solutions. While specific student counts aren't published, he explicitly invites PhD and Master's candidates in his core research areas, emphasizing practical applications for rural communities. Dr. Lai maintains strong industry connections through consultancy projects and collaborates internationally on ASEAN-focused renewable energy initiatives, bridging academic research with real-world engineering challenges in Sarawak and beyond.

• Control Systems
• Robotics
• Automation
• +۵ مورد دیگر

Professor Dariusz Horla is a faculty member at the Faculty of Automation, Robotics and Electrical Engineering at Poznań University of Technology, where he works in the Institute of Robotics and Machine Intelligence. He holds the title of Professor with a habilitation degree (dr hab. inż.) in automation and control engineering. His research focuses on advanced control systems, particularly anti-windup compensation techniques, model predictive control applications for nuclear power plants, UAV control systems, and fractional-order controllers. Professor Horla has published extensively across these domains, with recent work addressing challenges in cooperative control systems, optimization methods for control applications, and practical implementations of advanced control algorithms in real-world systems. Analysis of his recent publications (2015-2025) reveals a strong emphasis on practical control applications, particularly in nuclear power plant systems and unmanned aerial vehicles. His work bridges theoretical control methods with industrial implementation challenges, often focusing on optimization approaches and stability considerations in constrained systems. Professor Horla has supervised multiple doctoral students and has developed significant educational materials in control systems and automation. His intellectual property contributions include inventions related to UAV height control systems, demonstrating the practical impact of his research. His academic service includes participation in habilitation committees and development of educational materials that have shaped control engineering education at Poznań University of Technology.

Joshua Meggittمشاهده پروفایل

مدرس

• Vibro-acoustics
• Structural dynamics
• Transfer Path Analysis
• +۵ مورد دیگر

Dr. Joshua Meggitt is a Lecturer in Acoustical and Audio Engineering at the University of Salford's School of Science, Engineering & Environment, where he completed both his BEng in Acoustic Engineering (2015) and PhD in Acoustics (2017). He is a core member of the Acoustics Innovation Institute and leads the EPSRC-funded xDEA project in collaboration with University of Nottingham and major industry partners including Airbus, Siemens, and BAE Systems. His research focuses on vibro-acoustics and structural dynamics, specializing in: Component-based simulation methodologies Transfer Path Analysis and blocked force techniques Uncertainty quantification in experimental acoustics Hybrid experimental-numerical modeling approaches Recent work explores vibration-induced noise in electric aircraft systems, structural health monitoring using transmissibility functions, and sound insulation of timber building elements. Dr. Meggitt received the prestigious Tyndall Medal in 2023 for his contributions to acoustics as an early-career researcher. His work bridges academic research and industrial applications through collaborations with Boeing, Bentley, Dyson, and Bosch across automotive, aerospace, and consumer product sectors. He teaches Acoustic Labs to first-year students and Microphone/Loudspeaker Design to second-years while supervising final-year projects and PhD candidates. As early career representative for the IOA Noise and Vibration Engineering Committee and UK Acoustic Network's SIG-VA, he actively shapes the acoustics research community.

Etienne Balmesمشاهده پروفایل

دانشیار

• Structural Dynamics
• Damping
• Model Reduction
• +۶ مورد دیگر

Etienne Balmes is an Associate Professor at Arts et Métiers ParisTech and Professor at SDTools, specializing in structural dynamics and damping. His affiliations include MIT (PhD), CentraleSupélec, and ONERA. He leads the DISCOH research team at PIMM laboratory, focusing on industrial applications like brake squeal and railway systems. His research integrates viscoelastic damping , model reduction , and experimental modal analysis . Key areas include: Design of viscoelastic treatments for aerospace/automotive systems Parametric testing under temperature/pressure variations Friction-induced vibration (e.g., brake squeal) Homogenization of composite materials Recent publications emphasize brake NVH analysis, railway dynamics, and model reduction techniques. Trends show a shift toward real-time simulation of non-linear systems and industrial validation of damping solutions. At DISCOH lab, he collaborates with SNCF, ONERA, and automotive partners, leveraging tools like SDT for vibration testing. Teaching includes courses on mechanical vibrations and modal analysis at ENSAM/CentraleSupélec.