جست‌وجوی استاد و پژوهشگر

Michael Barnesمشاهده پروفایل

استاد

• Plasma Physics
• Magnetic Confinement Fusion
• Astrophysical Accretion Disks
• +۳ مورد دیگر

Michael Barnes is a Tutorial Fellow in Physics and Professor of Physics at the University of Oxford. He contributes to the Department of Physics through teaching and research, with a focus on plasma behavior in magnetic fields. His work has critical applications in sustainable energy production via fusion and astrophysical systems. Professor Barnes teaches Mathematical Methods for Physicists to undergraduate students at University College and lectures on Complex Numbers and Ordinary Differential Equations . His pedagogical emphasis is on developing mathematical fluency for advanced physics topics. His research explores plasma turbulence suppression by sheared flows, particularly in magnetic confinement fusion. Key projects include the development of the TRINITY multiscale gyrokinetic transport code and studies on tokamak transport barriers. Recent publications highlight advancements in gyrokinetic simulations, collision operators, and beam diagnostics for fusion applications. Notable trends in his publications include multiscale modeling of plasma turbulence, zonal flow dynamics, and experimental comparisons for fusion devices like JET, MAST, and ITER. Subfields span from fundamental kinetic theory to applied fusion engineering.

Christopher Ferrieمشاهده پروفایل

دانشیار

• Quantum Estimation and Control
• Quantum Machine Learning
• Quantum Information Science
• +۵ مورد دیگر

Christopher Ferrie is an Associate Professor at the University of Technology Sydney (UTS), where he is affiliated with the Faculty of Engineering and Information Technology and the Centre for Quantum Software and Information (QSI). His academic career spans quantum information science, machine learning, and scientific education, with a strong emphasis on both theoretical research and public engagement through science communication. Full-time faculty member at UTS Active researcher in quantum information science Director of the Centre for Quantum Software and Information Author of numerous scientific publications and popular science books Dr. Ferrie earned his PhD in Applied Mathematics from the Institute for Quantum Computing and University of Waterloo in Canada in 2012. His doctoral work focused on quantum information and laid the foundation for his subsequent research career in quantum computing and related fields. Dr. Ferrie's research interests span several interconnected domains within quantum information science. His primary focus is on quantum estimation and control, with particular emphasis on applying machine learning techniques to solve statistical problems in quantum information science. He investigates how quantum systems can be characterized, controlled, and optimized for practical applications. His work bridges theoretical quantum physics with practical implementations, exploring how quantum phenomena can be harnessed for computational advantage. Recent research directions include quantum machine learning, quantum neural networks, and quantum optimization algorithms, with applications ranging from quantum state tomography to solving combinatorial optimization problems. Analysis of Dr. Ferrie's recent publications reveals a strong focus on practical quantum computing challenges. His work consistently addresses the intersection of quantum information theory and machine learning, with particular emphasis on making quantum algorithms more efficient, interpretable, and robust against noise. A significant portion of his recent research explores variational quantum algorithms and their optimization, reflecting the current priorities in near-term quantum computing. His publications also demonstrate growing interest in quantum machine learning applications and the development of techniques for quantum error mitigation and characterization. Dr. Ferrie has secured multiple research grants supporting his work in quantum computing and related fields. His funded projects span quantum control, quantum probability, quantum machine learning, and statistical decision theory, reflecting the breadth of his research program. While specific major awards aren't detailed in the available information, his sustained funding and publication record indicate significant recognition within the quantum information science community. Dr. Ferrie is actively involved in research supervision and teaching, with current funding supporting multiple PhD students and postdoctoral researchers. His teaching responsibilities include courses on quantum computing, where he introduces students to the fundamentals of quantum information processing. His research group at the Centre for Quantum Software and Information focuses on developing novel quantum algorithms and exploring the practical implementation challenges of quantum computing. The Centre for Quantum Software and Information at UTS serves as the primary research environment for Dr. Ferrie's work. This center brings together researchers working on various aspects of quantum computing, from hardware development to algorithm design and applications. Dr. Ferrie's team within the center focuses specifically on quantum software development, quantum algorithm design, and the application of machine learning techniques to quantum information problems. The collaborative environment enables interdisciplinary research that bridges theoretical quantum physics with practical computing applications.

Jeff Linderothمشاهده پروفایل

استاد

• Large-Scale Numerical Optimization
• Mixed-Integer Nonlinear Programming
• Operations Research
• +۵ مورد دیگر

Jeff Linderoth is the Harvey D. Spangler Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. His research focuses on large-scale numerical optimization, mixed-integer nonlinear programming, and stochastic programming, with applications in energy systems, global routing, and industrial processes. Education: BS in General Engineering (highest honors) from University of Illinois at Urbana-Champaign, MS in Operations Research from Georgia Institute of Technology, PhD in Industrial Engineering from Georgia Institute of Technology. Linderoth's work addresses theoretical and applied challenges in optimization, including developing algorithms for mixed-integer programming, analyzing knapsack polytopes, and creating tools like the Minotaur optimization toolkit. His recent publications explore integer programming techniques for subspace clustering, complementarity constraints, and customized coverage instrumentation. Selected trends in his research include advancements in stochastic programming, orbital branching for symmetric integer programs, and congestion analysis in power systems. His group contributes to optimization software and data-driven libraries like MIPLIB. Scientific Award: Harvey D. Spangler Professor.

Lifeng Zhouمشاهده پروفایل

استادیار

• Robotics
• Algorithms
• Combinatorial Optimization
• +۴ مورد دیگر

Lifeng Zhou is an Assistant Professor in the Department of Electrical and Computer Engineering at Drexel University, where he leads the Zhou Lab focused on advancing robustness and reliability in multi-robot systems through integration of foundation models. His research addresses real-world challenges in environmental monitoring, disaster response, and urban mobility. Education PhD, Electrical and Computer Engineering, Virginia Tech, 2020 MS, Control Science and Engineering, Shanghai Jiao Tong University, 2016 BS, Automation, Huazhong University of Science and Technology, 2013 Research Focus Dr. Zhou's work integrates robotics, algorithms, game theory and machine learning to develop secure and scalable autonomous systems. Primary research thrusts include: Resilient multi-robot coordination in adversarial environments Large language model integration for robotic decision-making Game-theoretic resource allocation strategies Risk-aware planning for autonomous vehicles Publication Trends Recent work (2024-2025) demonstrates strong focus on large language model applications in multi-robot systems, with 12/15 articles exploring LLM integration for flocking, scene segmentation, and decision-making. Additional emphasis includes adversarial robustness in target tracking (5 articles) and autonomous driving applications (4 articles). Awards and Recognition Best Paper Award, WACV 2025 LLVM-AD Workshop Professional Service Associate Editor, ICRA Conference Editorial Board Laboratory Focus The Zhou Lab develops foundational algorithms for secure and scalable multi-robot systems, with current projects spanning environmental monitoring drones, disaster response coordination, and autonomous vehicle perception systems.

• Smart Sustainable and Resilient Cities
• Energy Efficient Communities & Cities
• Crowdsensing-based Infrastructure Monitoring (CbIM)
• +۴ مورد دیگر

Mustafa Gül is a Professor in the Department of Civil and Environmental Engineering at the University of Alberta’s Faculty of Engineering. He also serves as Director of Internationalization at the Faculty of Engineering’s Deans Office. His research focuses on smart, sustainable, and resilient cities, with an emphasis on infrastructure monitoring and energy-efficient systems. Education: PhD in Civil Engineering (University of Central Florida, 2009), MSc in Electrical Engineering (University of Central Florida, 2011), MSc in Civil Engineering (Boğaziçi University, 2004), BSc in Civil Engineering (Boğaziçi University, 2002). Dr. Gül’s research spans two primary domains: Crowdsensing-based Monitoring of Built and Natural Environments (CoMBiNE) using AI, signal processing, and data analytics for infrastructure health; and Energy-Efficient Smart Cities through solar PV integration, IoT applications, and net-zero energy homes. His work bridges structural engineering, machine learning, and sustainable urban development. Recent publications highlight advancements in smartphone-based damage detection, UAV-assisted disaster assessment, and AI-driven energy systems. His team’s work on crowdsensing bridges, solar PV optimization, and smartphone analytics has been widely recognized in journals like Structural Control and Health Monitoring and Energy and AI . Notably, his 2017 paper earned the Best Paper Award at ISARC. Students supervised include Azim, R. , Keskin, M. , and Do, N. T. , among others. Scientific Awards: Best Paper Award, 34th International Symposium on Automation and Robotics in Construction (ISARC 2017) Dr. Gül’s projects often involve interdisciplinary collaboration, leveraging sensor networks, computer vision, and optimization algorithms to address urban resilience and energy sustainability. His leadership extends to course CIV E 779 and ongoing research initiatives in Alberta, Canada.

• Plasmonics
• Photocatalysis
• Electrocatalysis
• +۳ مورد دیگر

Professor Emiliano Cortés is a faculty member at the Ludwig Maximilian University of Munich (LMU), where he leads research in Plasmonic and Photonic Chemistry at the Nano-Institute Munich. His work bridges the fields of nanotechnology, physical chemistry, and materials science, focusing on light-matter interactions for energy conversion applications. Dr. Cortés' research focuses on plasmonics , photocatalysis , and electrocatalysis at the nanoscale. His group investigates how the dynamics of photons, plasmon-polaritons, carriers, phonons, and molecular states influence chemical reactivity. A key aspect of his work involves developing techniques to study plasmonic systems at the single particle level and designing rational synthesis approaches for plasmonic colloidal photo and electrocatalysts. His research has significant implications for sustainable energy technologies, environmental remediation, and advanced sensing applications. Analysis of Professor Cortés' recent publications reveals a strong focus on energy conversion processes, with particular emphasis on CO2 reduction, ammonia synthesis, and hydrogen production. His work integrates plasmonic effects with catalytic processes to enhance reaction efficiencies, often through innovative interface engineering and nanostructure design. The research spans fundamental studies of charge carrier dynamics to practical applications in energy storage and environmental technologies. Professor Cortés actively mentors doctoral candidates and postdoctoral researchers, currently advertising open positions for projects on Single particle photo and electrocatalysis and Synthesis of hybrid colloids . His research group, the Hybrid Plasmonics Lab (www.hybridplasmonics.org), receives funding from various sources to support their work on plasmon-mediated chemistry for sustainable applications. The Cortés research group operates within the Nano-Institute Munich, utilizing state-of-the-art facilities for nanomaterial synthesis, characterization, and testing. Their work combines experimental approaches with theoretical modeling to understand and harness light-matter interactions at the nanoscale for practical applications in energy conversion and environmental technologies.

• Power Electronics
• Power Quality and Stability
• Solid-State Transformers
• +۴ مورد دیگر

Zian Qin serves as an Associate Professor in the Department of Electrical Sustainable Energy at Delft University of Technology, Netherlands. His academic journey includes a B.Sc. from Beihang University (2009), M.Sc. from Beijing Institute of Technology (2012), and Ph.D. from Aalborg University (2015), all in Electrical Engineering, with a Visiting Scientist stint at RWTH Aachen University (2014). B.Sc., Electrical Engineering, Beihang University (2009) M.Sc., Electrical Engineering, Beijing Institute of Technology (2012) Ph.D., Electrical Engineering, Aalborg University (2015) His research centers on power electronics-based grid stability, solid-state transformers, and battery energy storage systems. Key contributions span DC microgrid control, magnetic material optimization, and EV charging infrastructure, with fingerprints highlighting expertise in power quality ( 100% ), voltage stability ( 87% ), and grid-forming applications ( 79% ). Current projects like ECS4DRES and GROW focus on resilient renewable energy systems and African energy storage solutions. His 154+ publications reveal strong emphasis on power electronics control ( 83% ), grid integration ( 79% ), and EV technologies ( 42% ), with recent work targeting microgrid vulnerability reduction and data-driven magnetic loss modeling. Awards include IEEE Prize Paper Awards (2023), World Top 2% Scientist recognition, and IEEE Innovation Awards (2024). IEEE International Challenge Excellent Innovation Award (2024) IEEE Open Journal Prize Paper Award (2023) World's Top 2% Scientist (2022-2024) Featured IES Journal Articles (2023) IEEE TIE Distinguished Reviewer (2020) As Founding Chair of IEEE Transportation Electrification Council Benelux Chapter and Dutch National for Cigre WG B4.101, he leads critical industry collaborations. His editorial roles in IEEE TPEL/TIE/JESTPE and projects like PROGRESSUS demonstrate significant grant leadership in next-generation power infrastructure. Lab activities focus on DC systems, energy conversion, and storage validation through Delft's Electrical Sustainable Energy facilities.

T. Alan Hattonمشاهده پروفایل

استاد

• Electrochemical Separation Processes
• Carbon Capture
• Water Purification
• +۴ مورد دیگر

T. Alan Hatton is a distinguished Professor in the Department of Chemical Engineering within the School of Engineering at the Massachusetts Institute of Technology (MIT). His career spans over four decades with significant contributions to electrochemical separation processes and sustainable engineering solutions. Current research focuses on developing next-generation electrochemical systems for critical environmental challenges. Education: Ph.D., University of Wisconsin, 1981 M.Sc. Eng, University of Natal, Durban, South Africa, 1976 B.Sc. Eng, University of Natal, Durban, South Africa, 1972 Professor Hatton's research centers on electrochemically-mediated separation processes , specifically targeting carbon capture from diverse sources (post-combustion flue gas, ambient air, and ocean water) and advanced water purification systems. His work integrates fundamental transport phenomena with innovative electrochemical engineering to create energy-efficient solutions. Key methodologies include redox-active materials, electro-swing adsorption, and molten salt electrochemistry, with strong emphasis on scalability and real-world implementation. Recent breakthroughs involve oxygen-stable quinone systems for direct air capture and marine carbon dioxide removal technologies. Analysis of his 15 most recent publications (2024-2025) reveals a concentrated focus on electrochemical CO 2 capture and conversion , with 87% of works directly addressing carbon management. Dominant themes include redox-active material design (particularly quinones and iron complexes), process thermodynamics optimization, and novel reactor architectures like fiber sorbents and photoelectrochemical systems. The research demonstrates consistent progression toward practical implementation, with increasing attention to marine carbon removal and integration with renewable energy sources. Scientific Awards: Founding Fellow, AIMBE, 1992 Merck Faculty Development Award, 1989 Class of '22 Career Development Chair, 1988 Presidential Young Investigator Award, NSF, 1985 Everett Moore Baker Award for Excellence in UG Teaching, MIT, 1983 Professor Hatton leads an active research group developing electrochemical separation technologies with significant industry and environmental impact. His laboratory operates at the intersection of fundamental electrochemistry and applied environmental engineering, securing sustained funding for projects targeting carbon capture scalability and water purification innovation. Current efforts focus on translating electro-swing adsorption technology to commercial applications through startup ventures, while maintaining strong educational contributions through MIT's chemical engineering curriculum. The research team maintains collaborations with national laboratories and industry partners to accelerate technology deployment.

Stuart James Khanمشاهده پروفایل

استاد مدعو

• Water Quality
• Water Recycling
• Chemical Contaminants in Water
• +۶ مورد دیگر

Professor Stuart James Khan is an Adjunct Professor in the School of Civil & Environmental Engineering at the University of New South Wales (UNSW). He previously served as Director of the Australian Graduate School of Engineering (AGSE). His research focuses on sustainable urban water management, water treatment processes, and chemical contaminant analysis. Khan holds a PhD in Environmental Engineering from UNSW (2003) and a BSc (Hons 1 in Organic Chemistry) from the University of Sydney (1995). His research interests include water recycling, desalination, disinfection byproduct formation, and the safe management of chemical contaminants. He has advised over 15 PhD students on topics ranging from advanced treatment technologies to risk assessment frameworks. Khan has published extensively, with over 200 journal articles and 18 book chapters, emphasizing interdisciplinary approaches to water quality challenges. Key contributions include advancing membrane bioreactor performance, optimizing water recycling systems, and assessing risks associated with emerging contaminants. His work bridges fundamental science and practical engineering solutions, addressing global water security challenges. Current projects explore wastewater-based epidemiology, PFAS remediation, and climate-resilient water infrastructure. Khan collaborates internationally on water reuse strategies and has contributed to policy frameworks for safe water management. His teaching spans courses like Water & Wastewater Treatment and Environmental Risk Analysis, reflecting his commitment to educating future engineers in sustainable practices.

• Biogeochemistry
• Microbiology
• Soil Science
• +۳ مورد دیگر

Ferran Garcia-Pichel is a Regents Professor and Center Director at Arizona State University’s School of Life Sciences, affiliated with the Biodesign Center for Fundamental & Applied Microbiomics, Center for Biodiversity Outcomes, Water Institute, and Global Drylands Center. He holds a PhD in Microbiology from the University of Oregon (1999) and has been a faculty member at ASU since 1999. His research focuses on microbial adaptations in arid environments, including biogeochemical cycling, soil crust formation, and sustainable land restoration. Key interests include cyanobacterial sunscreen compounds (scytonemin), carbonate dissolution mechanisms, and hydrogen production. Teaching responsibilities include advanced microbiology, microbial ecology, and geomicrobiology courses such as MBB 495 Undergraduate Research and BIO 493 Honors Thesis. Awards span from the 2021 Regents Professor distinction to the 2023 Sperry Award for restoration science. His lab explores interdisciplinary approaches to study microbial communities in desert soils, marine intertidals, and atmospheric dust, with applications in climate resilience and biomedicine. Research highlights include biocrust restoration strategies, microbial nitrogen fixation networks, and the role of GABA/Glu signaling in spatial organization. Collaborations address global challenges like fugitive dust mitigation and carbon sequestration. The lab is based at the Biodesign Building B on ASU’s Tempe campus.

David Wettergreenمشاهده پروفایل

استاد پژوهشی

• Space Robotics
• Robotic Exploration
• Autonomous Navigation
• +۷ مورد دیگر

David Wettergreen is a Research Professor at the Robotics Institute within Carnegie Mellon University's School of Computer Science , where he has been a faculty member since 2000. He directs the PhD Program in Robotics and holds a courtesy appointment in Mechanical Engineering. His research focuses on robotic exploration systems for extreme environments, spanning planetary surfaces, underwater caves, and terrestrial deserts. Key areas include autonomous navigation , science autonomy , multi-modal perception , and resource-cognizant planning . Field validation drives his work, with deployments in the Atacama Desert, Antarctic volcanoes, and lunar analog sites. Co-founder of Mesh Robotics LLC for off-road autonomy Former Research Fellow at Australian National University Former National Research Council Research Associate at NASA Ames Research Center His 15 most recent publications (2023-2025) demonstrate expertise in autonomous path planning , machine learning applications , terrain modeling , and science-driven exploration . Collaborations span planetary science, environmental monitoring, and space systems engineering. He has advised 17 PhD and 33 MS students , many of whom now work in space exploration or field robotics, and teaches courses in Robotics Systems Engineering . Current projects include the MoonRanger lunar micro-rover and technologies for autonomous resource mapping .

John Nassourمشاهده پروفایل

پژوهشگر

• Computational Cognitive Systems
• Robotics
• Wearable Robotics
• +۵ مورد دیگر

John Nassour is a Researcher at the Technical University of Munich's School of Computation, Information and Technology, affiliated with the Chair of Cognitive Systems. He holds engineering degrees from Tishreen University (electronics), a Master's in intelligent systems from University of Cergy-Pontoise/École Nationale Supérieure de l'Électronique, and a joint PhD from University of Versailles/TUM. His interdisciplinary research focuses on computational cognitive systems applied to robotics, including wearable devices, humanoid robots, soft robotics, and robot learning for locomotion/manipulation. Before joining TUM in 2020, he was a lecturer/researcher at Chemnitz University of Technology. He teaches courses in cognitive systems, neuro-inspired engineering, and soft robotics.

• RF IC Design
• Mixed-Signal IC Design
• Wireless Communication Systems
• +۴ مورد دیگر

Bertan Bakkaloglu is the On Semiconductor Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), where he has been since 2004. Prior to ASU, he worked at Texas Instruments focusing on analog, mixed-signal, and RF SoC development for communication transceivers. His research expertise spans RF and mixed-signal IC design, wireless/wireline communication systems, and broadband communication systems. Education: Ph.D. in Electrical Engineering, Oregon State University (1995) M.S.C. in Electrical Engineering, University of Houston (1992) Research Interests: RF and mixed-signal integrated circuits Power management ICs (including LDO regulators and DC-DC converters) High-efficiency power delivery systems Radiation-hardened electronics for space applications MEMS-based sensor systems Biomedical circuits for implantable devices Grants & Collaborations: Over 40+ funded research projects with institutions like NASA/JPL, BAE Systems, and NSF, focusing on power electronics, space systems, and biomedical applications Key projects include radiation-hardened converters, self-calibrating DACs, and implantable medical device circuits Industry partnerships with Texas Instruments, Space Micro, and FLIR Professional Activities: Technical committee member for IEEE Radio Frequency Integrated Circuits Conference Founding chair of IEEE Solid-State Circuits Society Phoenix Chapter

• Radiation Detectors
• Materials Physics
• Perovskite Materials
• +۳ مورد دیگر

Professor Paul Sellin is a Professor of Physics at the University of Surrey's School of Mathematics and Physics, with visiting roles at UCL and the University of Wollongong. He holds a PhD in Nuclear Physics from the University of Edinburgh (1992) and a BSc (Hons) in Physics from the University of Birmingham (1988). His research focuses on radiation detector materials, including perovskites, semiconductors, and scintillators, with applications in medical imaging, nuclear security, and high-energy physics. Key interests include perovskite semiconductor development, neutron/gamma detection, and radiation-hard materials. His group collaborates internationally on projects like the DTRA Interaction of Ionizing Radiation with Matter (IIRM) University Research Alliance. Publications highlight advancements in X-ray detection using perovskite nanocomposites, Cu-doped crystals, and organic semiconductors. His work emphasizes material synthesis, charge transport optimization, and device fabrication for low-dose imaging and high-sensitivity detection. Professor Sellin has supervised over 30 postgraduate students, many contributing to seminal studies on perovskite detectors, plastic scintillators, and semiconductor characterization. His contributions span academic networks like the Nuclear Threat Reduction Network (NTR-net) and the STFC NuSec program.

• Networked Control Systems
• Cyber-Physical Systems
• Cybersecurity
• +۴ مورد دیگر

Professor Daniel Quevedo is a leading academic in Electrical and Computer Engineering at The University of Sydney. Previously, he held positions at Queensland University of Technology and Paderborn University, Germany, where he founded the Chair in Automatic Control. He earned his PhD from the University of Newcastle (Australia) and MSc/Ing. degrees from Universidad Técnica Federico Santa María (Chile). His research focuses on networked control systems, cyber-physical systems, and cybersecurity, with contributions to state estimation, control of power converters, and human-in-the-loop systems. He has pioneered work integrating machine learning, behavioral economics, and advanced mathematics to address challenges in interconnected digital-physical environments. Quevedo serves as Associate Editor for IEEE Transactions on Control of Networked Systems and IEEE Control Systems. He chairs the Committee of Experts for Germany’s Excellence Strategy on Digital Methods and has held leadership roles in IEEE technical committees. Notable awards include the IEEE Axelby Outstanding Paper Award (2018) and multiple fellowships. Teaching includes advanced control systems courses like Reinforcement Learning and Optimal Control. He is a Fellow of the IEEE and has published over 200 peer-reviewed articles, with recent work emphasizing privacy-preserving state estimation, resilient control systems, and energy-efficient wireless control. His research labs explore topics such as human-machine collaboration, cybersecurity in Industry 5.0, and data-driven control strategies. Current projects include secure remote state estimation frameworks and adaptive control under adversarial conditions.