جست‌وجوی استاد و پژوهشگر

Iain Boydمشاهده پروفایل

استاد

• Hypersonic Aerothermodynamics
• Electric Propulsion
• Plasma Dynamics
• +۳ مورد دیگر

Iain Boyd is the H.T. Sears Memorial Professor of Aerospace Engineering Sciences at the University of Colorado Boulder and Director of the Center for National Security Initiatives. He holds a PhD in Aeronautics and Astronautics (University of Southampton, 1988) and a BSc in Mathematics (University of Southampton, 1985). His research focuses on hypersonic aerothermodynamics, electric propulsion, rocket plumes, and computational modeling of nonequilibrium gas and plasma dynamics. Boyd has held academic positions at the University of Michigan (2010–2019 as James E. Knott Professor), Cornell University (1993–2002), and NASA Ames Research Center (1989–1992). He leads the Nonequilibrium Gas and Plasma Dynamics Laboratory (NGPDL) and contributes to the Aerospace Mechanics Research Center (AMREC). His awards include the AIAA Thermophysics Award (2018), Fellowships from the Royal Aeronautical Society (2017) and American Physical Society (2014), and the Chief of Staff of the Air Force Award (2017). His research emphasizes advancing hypersonic vehicle technologies, plasma-based propulsion systems, and computational methodologies for extreme aerodynamic environments. Recent work addresses aerocapture trajectory optimization, plasma-driven cooling systems, and sensitivity analysis of hypersonic flow phenomena.

Nedim Hodzicمشاهده پروفایل

استاد

• Public Health
• Infectious Diseases
• Medical Research
• +۳ مورد دیگر

Nedim Hodžić is a Full Professor at the Department of Energy and Process Engineering, Faculty of Mechanical Engineering, University of Zenica. He has been employed at the institution since 1984. Born in 1960 in Zenica, he graduated from the Faculty of Mechanical Engineering in 1983. His research spans diverse medical and biomedical fields, including infectious diseases, surgical practices, and healthcare management. Notable contributions include studies on bacterial vaginosis prevalence, palliative care competencies, and mathematical modeling of pandemic spread. His work bridges engineering principles with clinical applications, such as in anesthesiology and diagnostic imaging. Education: Bachelor’s Degree in Mechanical Engineering (1983), Faculty of Mechanical Engineering, Zenica Research Interests: Public Health and Epidemiology Infectious Disease Management Biomedical Engineering Applications Surgical Techniques and Anatomy Evidence-Based Medicine Practices Recent Research Trends: Recent articles (2022–2025) focus on clinical diagnostics (e.g., prostate carcinoma imaging), surgical innovations (e.g., appendectomy anatomical variations), and public health challenges (e.g., hepatitis C in prisoners). His 2020 study on Bosnia’s COVID-19 modeling highlights his expertise in mathematical epidemiology. Lab/Teams: No specific laboratory or team affiliations mentioned in the provided text. Grants & Advising: No explicit mentions of grants or advisees in the text.

Qi Tangمشاهده پروفایل

پژوهشگر ارشد

• Hydrogeology
• Data Assimilation
• Earth System Modeling
• +۳ مورد دیگر

Qi Tang is a Research Fellow in the Department of Environmental Science at the University of Basel and concurrently serves as Coordinator of the Swiss Water Earth Systems PhD School at the University of Neuchâtel. His expertise spans hydrogeology, data assimilation, and Earth system modeling. He holds a PhD in Hydrogeology from RWTH Aachen University (2017) and has held postdoctoral positions at institutions including the Alfred Wegener Institute (Germany), the University of Basel, and the Chinese Academy of Sciences. Education: PhD in Hydrogeology, RWTH Aachen University, Germany (2012–2017) MSc in Hydrology and Water Resources, Beijing Normal University (2009–2012) BSc in Applied Mathematics, China Agriculture University (2005–2009) Research Interests: Qi Tang focuses on advancing coupled Earth system models through data assimilation techniques. His work integrates hydrological, oceanographic, and climatic processes to improve predictive accuracy. Key areas include river-aquifer interaction dynamics, satellite data integration in ocean-atmosphere models, and cloud computing for real-time water resource management. His research bridges theoretical modeling with practical applications in environmental monitoring and climate prediction. Publications: His articles emphasize data-driven approaches to environmental systems. Recent work highlights coupled model improvements using satellite data (e.g., ocean-atmosphere interactions), ensemble Kalman filtering for flood simulations, and Bayesian networks for precipitation modeling. These studies underscore his expertise in both computational methods and field applications. Advising & Grants: While no formal advisees are listed, his postdoctoral roles suggest involvement in mentoring junior researchers. No specific grants are mentioned in the provided texts. Labs/Teams: Affiliated with the Hydrogeological Processes group at the Center for Hydrogeology and Geothermal Energy (CHYN), University of Neuchâtel. This group specializes in geothermal energy, hydrochemistry, and stochastic hydrogeology.

Sarah Perezمشاهده پروفایل

پژوهشگر

• Mathematical modelling
• Numerical simulation
• AI-driven approaches
• +۵ مورد دیگر

Sarah Perez is a Postdoctoral Research Associate in the GeoEnergy research group at the Lyell Centre, part of the School of Energy, Geoscience, Infrastructure and Society at Heriot-Watt University. Holding a PhD in Applied Mathematics from the University of Pau in France, she specializes in developing numerical and machine learning models for geological carbon storage applications. Her research sits at the intersection of mathematical modeling, numerical simulation, and AI-driven approaches for subsurface energy systems. She develops frameworks that integrate pore-scale imaging with AI-based uncertainty quantification to improve reliability of subsurface predictions, with particular focus on fractured and reactive media. Her work bridges multiple scales to address leakage risks and subsurface integrity in carbon storage systems. Analysis of her publications reveals consistent focus on computational methods for geological applications, with increasing integration of AI techniques across her work from 2022-2025. Her research shows strong interdisciplinary connections between computational physics, machine learning, and geoscience. Beyond research, Perez actively contributes to academic community through science communication and early-career initiatives. She co-chairs the InterPore Student Awards Sub-Committee and organizes YouTube webinars on Porous Media research and AI for Net Zero, demonstrating commitment to knowledge exchange and interdisciplinary collaboration. Her professional network shows significant international collaboration, with research activities spanning multiple countries and institutions. She maintains active engagement with the scientific community through conference presentations and peer-reviewed publications in high-impact journals.

• Offshore Renewable Energy
• Marine Technology
• Wind Power
• +۳ مورد دیگر

Erin Bachynski-Polić is a Professor in the Department of Marine Technology at the Norwegian University of Science and Technology (NTNU). Her research focuses on offshore renewable energy systems, particularly the design and analysis of fixed and floating support structures for wind turbines, hydroelasticity, and optimization of marine systems. She leads several major projects including WAS-XL, Green Energy at Sea, and WINDMOOR, addressing challenges in mooring systems, extreme loading, and floating wind farm layouts. Education includes a Ph.D. from NTNU (2014), an M.S. and B.S.E. from the University of Michigan (2010 and 2009), specializing in Naval Architecture and Marine Engineering with a mathematics minor. Her teaching spans marine dynamics, ocean structure design, and offshore wind courses. Research interests emphasize advancing hydrodynamic and structural models for floating turbines, wake steering techniques, and environmental load analysis. Notable contributions include validation of Morison force formulations, mooring optimization, and storm impact studies. Projects like SFI BLUES and FLOAWER aim to develop next-generation floating support structures for large-scale offshore wind energy.

• Control Systems
• Wind Energy
• Aerodynamics
• +۳ مورد دیگر

Finn Matras is affiliated with the Norwegian University of Science and Technology (NTNU). His research focuses on control systems, wind energy, and aerodynamic modeling, particularly for multirotor systems. He has contributed extensively to the understanding of inflow dynamics, airload parametrization, and energy optimization. His work includes modeling and simulation techniques for multirotor dynamics, with applications in wind turbines and aerospace engineering. Key themes from his publications include system dynamics, optimization algorithms, and computational fluid mechanics. His email contact is finn.matras@ntnu.no, and he is associated with the Department of Engineering Cybernetics at NTNU, although formal departmental details are not explicitly stated.

• Control Systems
• Mechatronics Design
• Signal Processing
• +۴ مورد دیگر

Mohammad Narimani is a Senior Lecturer in the Department of Mechatronic Systems Engineering at Simon Fraser University’s Faculty of Applied Sciences. He holds a PhD in Mechatronics Engineering from King's College London (2011), a MASc in Electrical Engineering from Isfahan University of Technology (2001), and a B.Sc. in Electrical Engineering from Sharif & Isfahan University of Technology (1997). His teaching focuses on core mechatronic disciplines, including Control Theories, Mechatronic Design, Signal Processing, and Digital Logic Circuits. Dr. Narimani’s research spans multiple domains: Biomedical Engineering : Developing machine learning models for healthcare applications like blood pressure estimation and spinal injury detection. Control Systems : Stability analysis in fuzzy logic-based systems and nonlinear control theory. Renewable Energy : Investigating fuel cell dynamics during oxygen starvation to improve efficiency and safety. Machine Learning : Multimodal sensing for activity recognition and physical monitoring systems. Recent work emphasizes practical applications such as wearable sensor integration for health monitoring and smart home systems. His articles reflect a trend toward combining traditional engineering principles with modern AI-driven methodologies. Advising and grants: No formal advisees listed, but his courses (e.g., MSE 381 Feedback Control Systems, MSE 250 Electric Circuits) suggest involvement in student mentorship. No specific grants mentioned in available texts. Lab affiliations: Active within the Faculty of Applied Sciences’ research ecosystem, though specific lab names are not detailed in the provided materials.

Selin Ahipasaogluمشاهده پروفایل

استاد

• Operational Research
• Convex Optimization
• Robust Optimization
• +۵ مورد دیگر

Prof. Selin Damla Ahipasaoglu is a Professor in Operational Research at the University of Southampton's School of Mathematical Sciences . She serves on the management team of the UKRI CDT SustAI (Artificial Intelligence for Sustainability) as Senior Tutor and Co-Lead for the Transportation and Logistics Theme . Her work bridges mathematical optimization with practical applications in sustainability, finance, and transportation systems. Research Interests : Convex Optimization Robust Optimization Discrete Choice Theory Experimental Design Machine Learning Current Research : Focused on robust optimization and its applications in discrete choice modeling, portfolio optimization, and transportation systems. She explores theoretical frameworks alongside real-world implementations, particularly through interdisciplinary projects like the UKRI CDT SustAI. Teaching : In the 2025/2026 academic year, she teaches MATH3017: Mathematical Programming and MATH2013: Operational Research II . She supervises PhD students in Mathematical Sciences, including Kexin Lai, Samuel Jericho Ward, and others.

• Transportation Engineering
• Intelligent Transportation Systems
• Infrastructure Resilience
• +۷ مورد دیگر

Sean Qian is a Professor at Carnegie Mellon University (CMU), jointly appointed in the Department of Civil and Environmental Engineering, Heinz College of Information Systems and Public Policy, and the Department of Electrical and Computer Engineering. He directs the Mobility Data Analytics Center (MAC) and co-founded TraffiQure Technologies to commercialize AI-driven infrastructure solutions. His research focuses on dynamic network modeling, intelligent transportation systems, climate resilience, and infrastructure interdependency. Supported by NSF, U.S. DOT, and industry partners, his work integrates AI, big data, and policy analysis to address urban mobility challenges. Education: PhD in Civil Engineering (UC Davis, 2011), MS in Statistics (Stanford, 2012), and dual MS/BS in Civil Engineering (Tsinghua University, 2006/2004). Research emphasizes smart cities, EV integration, cybersecurity for infrastructure, and equity in mobility policies. He serves on editorial boards for Transportation Research journals and TRB committees. Awards include the NSF CAREER Award (2018) and Greenshields Prize (2017). Grants and collaborations include projects with Fujitsu, IBM, and state agencies, addressing curbside management, climate adaptation, and rural mobility. His lab develops tools like the Rural Access Mobility Platform and social digital twin technologies for infrastructure resilience.

Nicholas Ouelletteمشاهده پروفایل

استاد

• Complex Systems
• Fluid Dynamics
• Environmental Engineering
• +۴ مورد دیگر

Nicholas Ouellette is a Professor of Civil and Environmental Engineering at Stanford University, specializing in complex systems far from equilibrium. His research emphasizes dynamical self-organization across disciplines like fluid dynamics, granular media, and collective animal behavior. He holds a Ph.D. in Physics from Cornell University (2006), an M.S. in Physics (2005), and a B.A. in Physics and Computer Science from Swarthmore College (2002). Prior to Stanford, he was on the faculty at Yale University’s Mechanical Engineering and Materials Science department from 2008-2015. He has received teaching awards at both institutions. His work spans experimental and theoretical studies of turbulence, granular erosion, insect swarms, and urban dynamics. Current research includes sediment transport in turbulent flows, collective behavior in bird flocks, and urban street network analysis. He leads the Environmental Complexity Lab and collaborates on projects involving ocean mixing instrumentation and computational modeling of complex systems. Research interests include turbulent flows in fluids, particle transport dynamics, granular bed erosion mechanics, and quantitative analysis of animal collective motion. Techniques employed range from particle tracking velocimetry to machine learning for free-surface reconstruction. Ouellette’s recent work explores interdisciplinary connections between physics and urban systems, such as pedestrian access optimization in suburban layouts and the interplay of multiple environmental stressors in policy modeling. Notable contributions include studies on midge swarm mechanics, jackdaw flock kinematics, and the application of spectral analysis to energy transfer in turbulence. His lab develops advanced measurement systems for oceanographic studies and applies network theory to environmental and urban systems analysis. Ouellette maintains active collaborations across engineering, biology, and policy domains.

• Mechanical Engineering
• Multibody Dynamics
• Nonlinear Mechanics
• +۷ مورد دیگر

Shabana Ahmed is the Richard and Loan Hill Professor of Engineering at the University of Illinois at Chicago (UIC), affiliated with the Urban Transportation Center. Her expertise spans mechanical engineering, multibody dynamics, nonlinear mechanics, and computational mechanics, with a focus on vehicle systems analysis, railroad engineering, and soft robotics. She holds a prominent role in advancing geometrically accurate finite element methods and ANCF approaches for analyzing complex mechanical systems. Her research integrates theoretical mechanics with practical applications in transportation, robotics, and material science. Her work includes studies on railroad vehicle dynamics, soft material behavior, and thermal-elastic coupling in articulated systems. Notable contributions include developing numerical methods for analyzing gear systems, beam elements, and liquid sloshing problems. She also explores the application of Lagrangian principles and Frenet force analysis in performance evaluation of mechanical systems. Shabana Ahmed has published extensively on topics such as constrained large-displacement thermal analysis, nonlinear strain measures, and the mechanics of flexible robots. Her research bridges computational methods with real-world engineering challenges, emphasizing accuracy and practical implementation.

Yuchao Liuمشاهده پروفایل

مدرس

• Power Converters
• Model Predictive Control
• Motor Drives
• +۵ مورد دیگر

Dr. Yuchao Liu is a Lecturer in the Department of Mathematics, Physics & Electrical Engineering at Northumbria University since January 2023. Previously, she held academic roles at Harbin Engineering University (2019–2021) and the University of Nottingham (2021–2022 as a Research Fellow in the PEMC Group). She earned her Ph.D. in Electrical Engineering from Harbin Institute of Technology (2019) and was a visiting scholar at Imperial College London (2017–2018). Her research focuses on power electronics, renewable energy integration, and control systems. Key areas include power converter design, model predictive control (MPC), multi-terminal DC transmission (MTDC), and motor drives. She has contributed to EU Horizon 2020 projects like the IMOTHEP initiative. Her publications span topics such as battery state-of-health estimation, DC-DC converter optimization, and grid stability analysis. She actively seeks PhD students and has collaborated internationally on projects addressing sustainable energy challenges. Her work aligns with UN Sustainable Development Goals, particularly in enabling clean energy transitions and advancing sustainable infrastructure.

David Kwabiمشاهده پروفایل

دانشیار

• Electrochemical Energy Storage
• Carbon Capture
• Chemical Separations
• +۲ مورد دیگر

David Kwabi is an Associate Professor of Chemical & Environmental Engineering at Yale University, leading the Kwabi Lab. His research focuses on developing electrochemical systems for clean energy and environmental sustainability, including carbon capture and energy storage. He holds a BSE from Princeton University (2010) and a PhD from MIT (2016). Key research areas include electrochemical energy storage, carbon capture technologies, and chemical separations. His lab employs advanced analytical techniques and physics-based models to design durable, high-performance devices. Recent work addresses CO2 removal from seawater using photoacids and degradation mechanisms in organic redox-flow batteries. Awards: ASME Rising Star Award (2024) Scialog Negative Emissions Fellow (2022) NSF CAREER Award (2021) ASME Pi Tau Sigma Gold Medal (2020) His work is affiliated with the Yale Center for Natural Carbon Capture and the Yale School of Engineering. Research emphasizes clean energy transitions and sustainable environmental solutions.

Veronika Grimmمشاهده پروفایل

استاد

• Energy Economics
• Climate Policy
• Market Design
• +۳ مورد دیگر

Prof. Dr. Veronika Grimm is a leading economist at Friedrich-Alexander-Universität Erlangen-Nürnberg and serves as the spokeswoman for FAU Solar. She has been elected to the DFG review board and actively contributes to energy policy discourse through her research and public reports, including presentations on Germany's Annual Report by the Council of Economic Experts. School: School of Business and Economics Academic Rank: Professor Key Research Areas: Energy economics, climate policy, market design, and renewable energy systems Her work focuses on the economic implications of energy transitions, including hydrogen markets, coal phase-outs, and electricity market reforms. She employs advanced mathematical modeling to analyze multilevel market structures and policy interventions. Recent publications highlight her expertise in: European energy market dynamics Net-zero policy frameworks Hydrogen technology funding mechanisms Global green energy trade Behavioral economics in public policy contexts Scientific Contributions: DFG Review Board Election (2024) Key participant in EU energy policy evaluations Regular advisor on climate-economic synergies

Ashok Agrawalaمشاهده پروفایل

استاد

• Computer Systems
• Distributed Algorithms
• Real-Time Systems
• +۱۰ مورد دیگر

Ashok Agrawala is a Professor in the Department of Computer Science at the University of Maryland, with joint affiliations in the University of Maryland Institute for Advanced Computer Studies (UMIACS) and the Department of Electrical Engineering. He directs the Maryland Information and Network Dynamics (MIND) Lab, a leading research group focused on real-time systems, network performance, and wireless localization technologies. Education: B.E. and M.E. in Electrical Engineering, Indian Institute of Science, Bangalore M.A. and Ph.D. in Applied Mathematics, Harvard University His research interests span computer systems, distributed algorithms, real-time operating systems, network performance modeling, traffic shaping, and indoor localization . He is renowned for pioneering the Ricart-Agrawala distributed mutual exclusion algorithm, developing the Maruti real-time operating system, and creating the Horus and Locus indoor positioning systems. His work has led to significant advances in temporal guarantees, jitter-free data delivery, and calibration-free localization. His recent publications show sustained innovation in wireless localization, context-aware computing, breath analytics, and energy-efficient IoT systems , reflecting an evolving research trajectory toward smart health and urban computing. He has authored over 200 papers and seven books, with consistent publication activity into 2024. Scientific Recognition: Fellow, IEEE Member, ACM Member, AAAS Member, Sigma Xi Agrawala has advised over thirty Ph.D. students, many of whom now lead research in academia and industry. His research has been funded by DARPA, NSF, and AFOSR, with corporate partnerships from IBM, Novell, and AT&T. He previously worked at Honeywell Information Systems, where he designed an Optical Character Reader. He has also served as a consultant to the UNDP and the Government of India, and as a technical expert in legal cases. He leads the MIND Lab, which focuses on mobile computing, wireless networks, and context-aware systems , continuing to innovate in real-time and networked systems.