جست‌وجوی استاد و پژوهشگر

Nicola Salvatiمشاهده پروفایل

دانشیار

• Survey Sampling
• Model-Assisted Inference
• Robust Regression
• +۴ مورد دیگر

Nicola Salvati is an Associate Professor in Statistics at the University of Pisa's Department of Economics and Management. He holds a PhD in Applied Statistics from the University of Florence (2004). His research focuses on survey sampling, model-assisted inference, robust regression, quantile and M-quantile regression, spatial statistics, and applications to poverty mapping and Big Data. He contributes to interdisciplinary studies bridging statistics with socio-economic analysis and environmental science. Research interests include developing methodologies for small area estimation, handling linked data, and addressing challenges in causal inference. His work is supported by grants from the European Union and Italy's Ministry of Research. He is a Fellow of the Italian Statistical Society and affiliated with the International Business and Human Rights focus area. Key publications emphasize temporal M-quantile models, causal small area estimation, and applications of statistical methods in air quality and healthcare analysis. His articles frequently address policy-relevant topics like poverty measurement, unemployment, and enterprise sustainability. Advances in his work include methodologies for bias correction, spatial semiparametric modeling, and robust regression techniques. He collaborates on projects involving hedonic pricing, nursing home performance evaluation, and environmental exposure assessment.

Angeliki Karperakiمشاهده پروفایل

مدرس

• Fluid-Structure Interaction
• Marine Engineering
• Coastal Engineering
• +۵ مورد دیگر

Dr. Angeliki Karperaki is a Lecturer in Civil Engineering at Aston University's College of Engineering and Physical Sciences. She specializes in Fluid-Structure Interaction, Marine Engineering, and Computational Mechanics with a focus on hydroelastic analysis of floating structures and wave-structure interactions. Her research addresses challenges in offshore and coastal environments, including noise propagation from marine propulsion systems and structural dynamics under extreme conditions. Education: PhD in Hydroelasticity of Floating Structures, National Technical University of Athens (2021) MSc in Computational Mechanics, National Technical University of Athens (2014) MSc in Construction Project Management, Edinburgh Napier University (2012) MSc in Structural Engineering and Mechanics, University of Glasgow (2010) Research Interests: Her work integrates advanced numerical methods like BEM-FEM coupling and finite element analysis to study fluid-structure interactions in marine and coastal systems. Key areas include optimization of flapping-foil thrusters, hydroelastic behavior of very large floating structures (VLFS), and wave dynamics in variable bathymetry regions. She explores environmental impacts such as noise generation from marine propulsion and long-wave impacts on coastal infrastructure. Grants & Advising: While specific grants or advisory roles are not detailed, her extensive publication record (19 outputs) reflects sustained research activity. Teaching includes courses like 'Introduction to Civil Engineering' and 'Sustainable Materials and Design.' Labs/Teams: Collaborates within Aston's EPS Education and Professional Practice Academic Research Group, focusing on computational mechanics and offshore engineering challenges.

Muftooh Siddiqiمشاهده پروفایل

مدرس ارشد

• Smart Manufacturing
• Industry 4.0
• Advanced Manufacturing
• +۷ مورد دیگر

Muftooh Siddiqi is a Senior Lecturer and Programme Director of the MSc Smart Manufacturing program at the School of Mechanical, Biomedical & Design Engineering, part of the College of Engineering and Physical Sciences at Aston University. His research focuses on Smart Sustainable Manufacturing, Advanced Manufacturing Technologies, Industry 4.0 integration, and Remanufacturing. He holds a PhD in Manufacturing from the University of Strathclyde. Research Interests: Industry 4.0 and Smart Manufacturing Systems 3D Printing and Additive Manufacturing Material Characterization and Composite Materials Robotics and Reverse Engineering Hydropower and Wind Energy Systems AI-driven Automation in Manufacturing His recent publications (2021–2025) highlight advancements in AI integration for manufacturing processes, optimization of renewable energy systems, and material science innovations. He supervises self-funded PhD students in areas like advanced manufacturing technologies and sustainable production methods. Key contributions include developing metrology processes for precision manufacturing, optimizing turbine designs for energy efficiency, and applying machine learning to industrial control systems. His work bridges traditional manufacturing with cutting-edge technologies like Industry 4.0 and IoT integration.

Aidin Delgoshaeiمشاهده پروفایل

استاد

• Digital Project Management
• Agile Methodologies
• Time and Cost Management
• +۲ مورد دیگر

Aidin Delgoshaei is Professor of the Practice in Project Management at the University of Kansas. His research integrates digital project management, optimization algorithms, and machine learning to address complex scheduling and supply chain challenges. Dr. Delgoshaei applies innovative methodologies including nature-inspired metaheuristics and fuzzy logic to industrial systems. Research Focus: Current work develops advanced algorithms for robotic trajectory planning, supply chain optimization, and construction management. His frameworks address dual-resource constraints, sustainable supply chains, and market uncertainties through computational intelligence approaches.

• Nonlinear Control
• Automotive Systems
• Robotics
• +۴ مورد دیگر

Antonella Ferrara is a Full Professor of Automatic Control at the University of Pavia's Department of Electrical, Computer and Biomedical Engineering (ECBE). She holds leadership roles, including Head of the Intelligent Robotics Laboratory and President of the Department's Research Standing Committee. Her academic journey includes a Laurea Degree (MSc equivalent) in Electronic Engineering from the University of Genova (1987) and a PhD in Computer Science and Electronics (1992). She transitioned from Assistant to Full Professor at the University of Pavia, contributing significantly to nonlinear control, automotive systems, robotics, and power systems. Her research focuses on sliding mode control, vehicular traffic modeling, and applications in autonomous systems. She has authored/co-authored over 450 publications, including 160 journal papers and monographs on topics like vehicle dynamics and freeway traffic control. Awards include IEEE Fellow (2020), IFAC Fellow (2021-2023), and AAIA Fellow (2024). She teaches courses such as Process Control, Robot Control, and Nonlinear Control in English, and contributes to international collaborations, including projects on sustainable mobility and medical robotics. Her institutional roles span research leadership, international mobility coordination, and editorial contributions to journals like Automatica and IEEE Transactions. Prof. Ferrara supervises numerous PhD, postdoc, and graduate students, leading over 200 MSc theses since 2020. She chairs major conferences, including the 24th IFAC World Congress (2029) and the 2024 IEEE Workshop on Variable Structure Systems. Her work bridges theoretical advancements with practical applications in industry, including collaborations with automotive companies like Ferrari F1 and FIAT.

Dmitri Kharzeevمشاهده پروفایل

عضو هیئت علمی

• Quantum Chromodynamics
• Chiral Magnetic Effect
• Topological Matter
• +۲ مورد دیگر

Dmitri Kharzeev is a Distinguished Professor in the Department of Physics and Astronomy at Stony Brook University. His research spans quantum chromodynamics, topological matter, chiral magnetic effects, and quantum computing applications in high-energy physics. The Kharzeev group investigates fundamental aspects of quantum field theory and their implications for nuclear and condensed matter physics. Current research focuses on chiral magnetic effects in heavy-ion collisions and topological materials, quantum entanglement in particle production, and quantum simulation of field theories. Recent publications demonstrate consistent themes in anomalous transport phenomena, quantum information approaches to particle physics, and applications of quantum computing to fundamental physics problems. Prof. Kharzeev leads research at the intersection of particle physics, condensed matter, and quantum information science, with significant contributions to understanding topological aspects of quantum field theories.

Dimitra Souliotiمشاهده پروفایل

مدرس ارشد

• Materials Engineering
• Composite Materials
• Additive Manufacturing
• +۱ مورد دیگر

Dimitra Soulioti is a Senior Lecturer in Materials Engineering at Sheffield Hallam University's Department of Engineering and Mathematics. She holds a PhD in Materials Engineering from the University of Ioannina and a Civil Engineering degree from Aristotle University of Thessaloniki. She joined SHU in 2014 as an Associate Lecturer and became Senior Lecturer in 2021. Her research focuses on mechanical behavior of structural and composite materials using destructive and non-destructive methodologies. Current projects include advanced lightweight composites for structural applications and non-destructive monitoring of advanced materials. Teaching areas: Aerospace Engineering Automotive Engineering Materials Engineering Sustainable Engineering Railway Engineering She has published 26 papers with over 1400 citations and is a Fellow of the Higher Education Academy since 2018.

Meaghan Charest-Finnمشاهده پروفایل

استادیار

• Advanced Automation
• Model Predictive Control
• Multi-Physics Process Automation
• +۳ مورد دیگر

Dr. Meaghan Charest-Finn is an Assistant Professor in the Department of Automotive and Mechatronics Engineering at Ontario Tech University. She holds a PhD in Mechanical Engineering from the University of New Brunswick (2020) and has extensive academic credentials including a Master's (2013), Bachelor's (2010), and a Diploma (2006) in mechanical engineering disciplines. Her research focuses on advanced automation, Model Predictive Control (MPC) algorithms, and integrating artificial intelligence into industrial processes. She teaches undergraduate courses in Artificial Intelligence and Machine Learning, Mechatronics Design, and Industrial Automation. Her professional contributions include patents on MPC systems and methods (e.g., US Patent 10386796) and active roles in initiatives like the Women in Research Council and Women in Engineering Mentorship. In 2023, she received the Ontario Tech TLC Teaching Award – Student Choice. Charest-Finn’s publications span topics like autonomous systems inspection, PID control optimization, and MPC applications in robotics and manufacturing. Her work bridges theoretical control systems with practical industrial challenges, emphasizing multi-physics automation and AI-driven process improvements.

• Nonlinear Control
• Adaptive Control
• Cyber-Physical-Human Systems
• +۶ مورد دیگر

Kaiwen Chen is a Research Associate at the Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London. He holds a B.Sc. from the University of Illinois Urbana-Champaign and a B.Eng. from Harbin Institute of Technology, followed by M.Sc. and Ph.D. degrees from Imperial College London. His research focuses on nonlinear and adaptive control theory, particularly in time-varying systems, multi-agent systems, and applications in cyber-physical-human systems and soft robotics. He is affiliated with the Control and Power Research Group and the Hamlyn Centre for Robotic Surgery, contributing to advancements in medical robotics and resilient control systems. Dr. Chen’s work emphasizes adaptive control methodologies for uncertain systems, including robust designs for cyber-physical networks and surgical manipulators. He serves as an Associate Editor on the Conference Editorial Board of the European Control Association since 2022. His notable achievements include the 2023 IET Control and Automation Doctoral Dissertation Prize and the 2018 Hertha Ayrton Centenary Prize for academic excellence. His research portfolio spans theoretical control advancements and practical implementations, such as hybrid manipulators for gastrointestinal interventions and online data-driven adaptive control strategies. He actively explores interdisciplinary applications, integrating experimental robotics into remote teaching through platforms like quadrotor test-beds. Affiliations : Control and Power Research Group, Hamlyn Centre for Robotic Surgery, Mechatronics in Medicine Lab Editorial Role : Conference Editorial Board, European Control Association Key Contributions : Cyber-physical security, resilient control architectures, soft robotic systems

Sergio Pellegrinoمشاهده پروفایل

استاد

• Structural Mechanics
• Lightweight Structures
• Deployable Structures
• +۴ مورد دیگر

Sergio Pellegrino is the Joyce and Kent Kresa Professor of Aerospace and Civil Engineering at California Institute of Technology and a Jet Propulsion Laboratory Senior Research Scientist. He co-directs the Space-Based Solar Power Project and directs the Graduate Aerospace Laboratories. His research spans structural mechanics, deployable space structures, and composite materials. Aerospace & Civil Engineering Professor JPL Senior Research Scientist Co-Director, Space-Based Solar Power Project Director, Graduate Aerospace Laboratories His work focuses on lightweight deployable structures for space applications, including ultra-thin composites, deployment kinematics, and stability analysis. Key projects involve the Space Solar Power Demonstrator and modular telescope assembly. Publications emphasize dynamics, failure modeling, and novel packaging concepts. Recent research trends include multi-configuration rigidity theory, vibration damping in coiled structures, and scalable mesh reflector antennas. His Google Scholar articles (2022-2025) cover topics like bistable structures, thin-shell deployment, and fiber Bragg grating sensors, reflecting expertise in aerospace structural innovation. AIAA Best Paper Award Torroja Medal Co-Director of Caltech's Space-Based Solar Power Project Professor Pellegrino has advised numerous graduate students and leads a research group focused on in-space assembly technologies, constitutive modeling, and experimental validation. The Space Structures Lab under his direction supports projects like AAReST (Autonomous Assembly of a Reconfigurable Space Telescope) and DOLCE (Deployable On-Orbit Ultra-Light Composite Experiment).

Jianfeng Zhangمشاهده پروفایل

استاد

• Stochastic Analysis
• Backward Stochastic Differential Equations
• Stochastic Controls and Games
• +۲ مورد دیگر

Jianfeng Zhang is a Professor in the Department of Mathematics at the University of Southern California (USC). His research focuses on Stochastic Analysis, Backward Stochastic Differential Equations, Stochastic Controls and Games, Stochastic Numerics, and Mathematical Finance. He earned his Ph.D. in Mathematics from Purdue University in 2001, preceded by an M.S. in Computational Finance and a B.S. in Mathematics from Fudan University. Prof. Zhang has held faculty positions at USC since 2003, advancing from Assistant Professor (2003–2007) to Associate Professor (2007–2012) and his current rank (2012–present). His academic career also includes a Visiting Assistant Professorship at the University of Minnesota (2001–2003). His research interests emphasize theoretical advancements in stochastic processes and their applications to finance and control theory. Key contributions include works on Mean Field Games, Viscosity Solutions, and Optimal Stopping Problems. He co-authored Contract Theory in Continuous-Time Models (2012) and Backward Stochastic Differential Equations (2017). Recent publications explore topics such as stochastic volatility control, viscosity solutions for master equations, and dynamic programming in mean field settings. His work often bridges theoretical rigor with applications in finance and optimal control.

Alf Gerischمشاهده پروفایل

مدرس ارشد

• Mathematical Modeling
• Numerical Analysis
• Scientific Computing
• +۶ مورد دیگر

Dr. Alf Gerisch is a Senior Lecturer at the Department of Mathematics, Technical University of Darmstadt, where he leads the Numerical and Scientific Computing Group. His research focuses on mathematical modeling, numerical simulation, and analysis of biological, material, and natural science processes, particularly in tumor models, cell adhesion, bone fracture healing, and multiscale mechanical properties of tissues. He has organized and contributed to numerous international conferences, including ENUMATH2025 and ECMTB 2024. His work integrates advanced numerical methods like peer time integration schemes and uncertainty quantification, with applications in biomedical systems and soft matter. Education: Ph.D. in Numerical Analysis (2001, University of Halle-Wittenberg), M.Sc. in Applied Mathematics (1997, University of Dundee). Research Interests: Dr. Gerisch advances numerical methods for taxis-diffusion-reaction systems, develops computational frameworks for uncertainty quantification, and models biological processes such as tumor invasion and cell migration. His projects include leadership of the DFG-funded Multiscale structure-functional modeling of musculoskeletal mineralized tissues (2009–2016) and membership in SFB Transregio 154 and 146. Publications: Over 50 peer-reviewed articles, including contributions to journals like Journal of Computational Physics , Bulletin of Mathematical Biology , and Computer Methods in Biomechanics and Biomedical Engineering . Recent work explores nonlocal models of cell adhesion and data-driven approaches for gas networks. Teaching: Offers courses in numerical linear algebra, mathematical biology modeling, scientific programming, and finite element methods. Consultation hours via Zoom during lecture weeks. Grants & Projects: Co-led DAAD-funded research visits to India (2017), and collaborates internationally on biomechanical and computational biology initiatives. Labs/Teams: Active in the Numerical Analysis and Scientific Computing research group, contributing to the Kardos adaptive Finite Element software and the asymptotic homogenization framework for composite materials.

• Computer Networking
• Network Performance Analysis
• Stochastic Network Calculus
• +۵ مورد دیگر

Yuming Jiang is a full Professor at NTNU's Department of Information Security and Communication Technology (Faculty of Information Technology and Electrical Engineering). He holds a BSc from Peking University, MEng from Beijing Institute of Technology, and PhD from National University of Singapore (NUS). His research focuses on network performance analysis, stochastic network calculus, and quality of service guarantees in communication networks. He authored the seminal book Stochastic Network Calculus (Springer, 2008). He has held roles including Study Programme Leader for NTNU's Master of Science in Digital Infrastructure and Cyber Security, and is a member of the Norwegian Academy of Technological Sciences (NTVA). Prof. Jiang has extensive experience in academic leadership, serving as conference chair (e.g., IFIP Networking 2014, IEEE Vehicular Technology Conference 2008) and committee roles in major networking communities. His work spans theoretical advancements (e.g., stochastic network calculus properties) and practical applications (e.g., UAV-assisted IoT security, NFV reliability). Key research contributions include modeling wireless channel capacity, analyzing time-sensitive networks (TSN/DetNet), and developing security frameworks for emerging communication systems. His publications (over 150 papers) bridge theoretical foundations and real-world network challenges in areas like energy-efficient communication, cyber-physical systems, and blockchain performance.

Guosheng Fuمشاهده پروفایل

استادیار

• Numerical Solution of Differential Equations
• Scientific Computing
• Finite Element Methods
• +۵ مورد دیگر

Guosheng Fu is the Robert and Sara Lumpkins Assistant Professor at the University of Notre Dame's Department of Applied and Computational Mathematics and Statistics (ACMS), part of the College of Science. His research focuses on numerical methods for partial differential equations, scientific computing, and high-order finite element techniques. He holds a Ph.D. from the University of Minnesota (2016), an M.S. from the same institution (2014), and a B.S. from Nankai University, China (2011). His education includes: Ph.D. in Applied Mathematics, University of Minnesota, 2016 M.S. in Applied Mathematics, University of Minnesota, 2014 B.S. in Mathematics, Nankai University, 2011 His research interests emphasize numerical solution strategies for complex systems, including fluid-structure interaction, optimal transport, and reaction-diffusion processes. Recent work highlights high-order discontinuous Galerkin (DG) methods, HDG schemes, and preconditioning techniques for incompressible flows and elasticity problems. His publications explore topics like divergence-free formulations, energy stability, and adaptive algorithms for nonlinear PDEs. Notable contributions include advancing hybridizable DG methods for fluid dynamics, developing robust numerical schemes for porous media flow, and creating efficient solvers for mean field control problems. His work bridges computational mathematics with applications in engineering and physical sciences. He currently holds no listed scientific awards but has an active research program supported by his academic position and collaborations. No advising or grant details are explicitly provided in the text.

Suman Chakravortyمشاهده پروفایل

استاد

• Estimation and Stochastic Controls
• Robotic Planning and Control
• Space Situational Awareness
• +۳ مورد دیگر

Suman Chakravorty is a Professor of Aerospace Engineering at Texas A&M University, part of the College of Engineering's Department of Aerospace Engineering. He leads the Estimation, Decision and Planning (EDP) Laboratory, focusing on nonlinear control, robotics, and space situational awareness. He holds a Ph.D. from the University of Michigan (2004) and a B.Tech from the Indian Institute of Technology Madras (1997). His research emphasizes stochastic controls, robotic planning, and data-driven modeling. Notable awards include the National Innovation Award (2017) and a Summer Faculty Fellowship from the Air Force (2010–2012). His work spans space object tracking, autonomous systems, and optimal control of complex systems like material microstructures. Key contributions include the SLAP framework for belief-space planning and advancements in particle Gaussian mixture filters. He advises students such as Utkarsh, Ran Wang, and Dilshad Raihan, and collaborates on projects like T-PFC control and randomized FISST techniques for multi-target tracking. His lab’s research integrates theory and practice, addressing challenges in non-Gaussian uncertainty, distributed estimation, and adaptive sampling. He promotes interdisciplinary approaches to robotics and aerospace systems, with applications in both academia and industry.