جست‌وجوی استاد و پژوهشگر

• Thermal Engineering
• Sustainable Energy Systems
• Energy Management
• +۳ مورد دیگر

Patrick Phelan is a Professor and Associate Dean of Graduate Programs at the Ira A. Fulton Schools of Engineering, Arizona State University (ASU). He holds additional roles as a Senior Global Futures Scientist and Editor-in-Chief of Frontiers in Energy Efficiency . His research focuses on sustainable energy systems, thermal management, and energy efficiency, with notable contributions to solar energy, thermal transport processes, and industrial cooling technologies. Phelan has extensive administrative experience, including managing the U.S. Department of Energy’s Emerging Technologies Program and the National Science Foundation’s Thermal Transport Processes Program. Education: Postdoctoral Fellow, Tokyo Institute of Technology (1990–1992) Ph.D., Mechanical Engineering, University of California, Berkeley (1990) M.S., Mechanical Engineering, Massachusetts Institute of Technology (1987) B.S., Mechanical Engineering, Tulane University (1985) Research Interests: Thermal engineering and heat transfer Sustainable energy systems and cooling Energy efficiency in buildings and industry Thermogalvanic systems and advanced materials Decarbonization and community benefit strategies Professional Associations: Fellow, American Society of Mechanical Engineers (ASME) Member, American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) Current Activities: Leading the ASU Energy Efficiency Center Contributing to the Energy for Rural Arizona initiative Advancing agricultural cold chain efficiency Teaching courses on heat transfer and energy systems (e.g., MAE 589, MAE 576)

Stephane Cotinمشاهده پروفایل

پژوهشگر

• Medical Simulation
• Biomechanical Modeling
• Computer-Aided Interventions
• +۳ مورد دیگر

Stephane Cotin is a Research Director at Inria and leader of the MIMESIS team, specializing in real-time physics-based medical simulations. His work focuses on surgical training, planning, and image-guided therapy, with over 200 scientific articles and the development of the open-source SOFA framework. He co-founded InSimo, Twinical, and EVE, and previously held roles at Harvard Medical School and Mitsubishi Electric Research Lab. Cotin’s research bridges imaging, robotics, and medicine to improve healthcare outcomes, emphasizing patient-specific biophysical modeling and real-time computation. His awards include the Academy of Sciences Award (2018) and Dirk Bartz Medical Prize (2015). He has advised numerous PhD students and led projects like MediTwin and PREMYOM, advancing digital twin technologies for precision medicine.

Amine MEHELمشاهده پروفایل

استاد پژوهشی

• Air Quality
• Pollution Control
• Turbulent Flow Dynamics
• +۳ مورد دیگر

Amine MEHEL is a Research Professor at ESTACA's Mechanics and Environment Center (MSCE) since 2010, specializing in air quality and pollution control in transport systems. His work bridges experimental and numerical studies of turbulent flow interactions with pollutants and nanoparticles. Research Axes : CQA (Characterization of Air Quality) and EDP (Spatiotemporal Dynamics of Pollutants) Key Projects : CEPARER (2022-2025), AmCoAir (2020-2023), CAPNAV (2019-2022), CAPTIHV (2015-2018) His expertise includes experimental facilities like wind tunnels, PIV/LDV measurements, and CFD simulations using Eulerian-Lagrangian approaches. He supervises PhD students and coordinates teaching projects like PIRATE and PRI. Recent publications focus on ultrafine particle dispersion in vehicle wakes, brake emissions in underground stations, and cabin air quality characterization.

ChanMin Kimمشاهده پروفایل

استاد

• Educational Technology
• Computer Science Education
• Science Writing
• +۳ مورد دیگر

ChanMin Kim is a Professor in the Learning and Performance Systems department at Penn State College of Education. With over 80 publications and 2553 citations, their work focuses on integrating artificial intelligence , robotics , and educational technology into science and computer science education. Research interests: Science writing, AI-human partnerships, robotics in education, equity-focused technology design Key methodologies: Natural Language Processing, learning analytics, scaffolding strategies Recent work explores large language models in education, debugging processes in pre-service teacher training, and automated assessment systems for science explanations. While the provided data doesn't show specific scientific awards or student advisees, their publications in venues like British Journal of Educational Technology and Journal of Science Education and Technology demonstrate significant contributions to learning sciences. Kim collaborates extensively with researchers in AI, educational technology, and equity-focused domains.

Daniel Sageمشاهده پروفایل

مدرس

• Biomedical Imaging
• Image Processing
• Deep Learning Applications
• +۵ مورد دیگر

Daniel Sage is a Lecturer and Scientific Advisor at École polytechnique fédérale de Lausanne (EPFL) , affiliated with the Biomedical Imaging Laboratory (LIB) under the College of Engineering (STI) and School of Life Sciences (SV) . He specializes in bioimage informatics , structured-illumination microscopy , and deep learning applications for biomedical imaging. His work spans algorithm development for single-molecule localization microscopy (SMLM) , fluorescence imaging , and 3D reconstruction . His research group has developed open-source tools like FlexSIM for light inhomogeneity correction, DeepImageJ for integrating deep learning in ImageJ, and Steer'n'Detect for orientation-accurate template detection. His publications focus on correcting multiple-blinking artifacts in PALM, optimal transport metrics for SMLM evaluation, and contextual feature analysis for xenograft cell classification. He mentors PhD students and contributes to interdisciplinary education through courses such as Bioimage Informatics and Fundamentals of Image Analysis , emphasizing practical software solutions and Java programming for bioimage processing. His collaborations include institutions like Howard Hughes Medical Institute and Centre National de la Recherche Scientifique (CNRS) .

Mark Crowleyمشاهده پروفایل

دانشیار

• Reinforcement Learning
• Deep Learning
• Ensemble Methods
• +۶ مورد دیگر

Mark Crowley is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo , with a cross-appointment in the Cheriton School of Computer Science . He is actively involved in the Waterloo Artificial Intelligence Institute (WAII) , the Waterloo Institute for Complexity and Innovation (WICI) , and serves as National Secretary for the Canadian Artificial Intelligence Association (CAIAC) , coordinating the Canadian Conference on AI . Research interests span the theoretical and applied aspects of Reinforcement Learning , Deep Learning , Manifold Learning , and Ensemble Methods . His work addresses challenges in domains with spatial dynamics, multi-agent systems, and uncertainty, particularly in Computational Sustainability (forest fire management, sustainable forestry), Autonomous Driving , Medical Imaging , and Material Design . Recent research focuses on integrating causal modeling with generative representation learning to improve out-of-distribution robustness in motion forecasting applications. Key publications include foundational work on ChemGymRL environments for safe chemical process reinforcement learning, Generative Causal Representation Learning for robust forecasting, and collaborative work on multi-advisor reinforcement learning in multi-agent settings. He co-authored a textbook Elements of Dimensionality Reduction and Manifold Learning (Springer, 2023) with Prof. Ali Ghodsi and Prof. Fakhri Karray. Teaching includes graduate and undergraduate courses in Algorithm Design , Computational Intelligence , Reinforcement Learning , and Data Modeling at the University of Waterloo since 2018. His research group has produced several notable graduates including Benyamin Ghojogh (2021), who continued as a postdoc until 2022.

Remus Teodorescuمشاهده پروفایل

استاد

• Battery (Electrochemical Energy Engineering)
• Modular Multilevel Converter
• Lithium-Ion Batteries
• +۶ مورد دیگر

Remus Teodorescu is a Professor at AAU Energy , Aalborg University , specializing in Power Electronics System Integration and Materials . His work bridges Lithium-Ion Batteries , Modular Multilevel Converters , and Smart Battery Systems . Education : Not explicitly mentioned in the text. Research Interests focus on Battery Management Systems , AI-Driven Energy Optimization , and Power Electronics for renewable energy integration. Key projects include Digital Twin for Lithium-Ion Batteries and BMS-DC for Data Centers . Recent Publications (2025) emphasize Finite Set MPC , Gradient Descent Optimization , and AI in Battery Parameter Estimation . His 2024 work explores Physics-Informed Neural Networks and Fault-Tolerant Converters . Scientific Awards : Villum Foundation Grant (313 million kroner, 2021) Named world's best in electrical engineering (2023) Advising includes supervising PhD projects on AI-Accelerated Battery Twins and Data-Driven SOH Estimation . Collaborations span Energy Cluster Denmark and Villum Fonden .

• Bayesian Statistics
• Machine Learning
• Statistical Modeling
• +۳ مورد دیگر

Paul-Christian Burkner is a researcher in the Department of Computer Science at Aalto University. His work focuses on Bayesian statistical methods, computational modeling, and probabilistic programming. He collaborates with Professor Aki Vehtari's research group and has published extensively on topics like model sensitivity, spatiotemporal analysis, and variable selection techniques. His research interests include: Bayesian inference and model comparison Computational statistics Probabilistic programming Machine learning algorithms Statistical modeling in social sciences Neuroimaging data analysis Recent publications demonstrate expertise in simulation-based calibration, spatiotemporal modeling, and Gaussian process approximations. Collaborations span psychology, neuroscience, and machine learning domains. Contact: ext-paul-christian.burkner@aalto.fi

Richard Eberhardtمشاهده پروفایل

مدرس

• Serious Games
• Educational Games
• Game Design
• +۵ مورد دیگر

Richard Eberhardt serves as Program Manager for the MIT Game Lab and instructor for MIT Game Lab classes at the Massachusetts Institute of Technology, where he aligns research projects with staff, equipment, and funding while mentoring student game development initiatives. His operational leadership supports the lab's mission to advance game literacy through interdisciplinary collaboration. His academic credentials include: Bachelor of Arts from the College of William & Mary Serious Games MA Certificate from Michigan State University Professional certifications: Certified Scrum Master PMI Agile Certified Practitioner Eberhardt's research investigates historical representation in games, analyzing how mechanics model historical systems and which narratives are amplified or marginalized in gaming communities. His scholarship spans serious games for mental health awareness, educational applications of VR/AR technologies, and inclusive game jam methodologies, consistently addressing public literacies through civic systems and emotional intelligence frameworks. Analysis of his 2013-2023 publications reveals sustained focus on game-based educational tools across STEM and humanities domains. His work pioneers VR simulations for photonics education, examines historical accuracy in commercial games, and develops inclusive frameworks for collaborative design events. This output demonstrates strategic integration of game mechanics with learning objectives while addressing representation gaps in historical gaming. Notable recognition includes an award for elude , the depression awareness game developed in 2010 for patients' support networks. As a mentor, Eberhardt directs student projects like elude and hosts game jams fostering community collaboration. His Agile-certified project management approach facilitates resource allocation across educational initiatives, though specific grant details remain undisclosed in available materials. The MIT Game Lab operates as his primary research ecosystem, connecting students, faculty, and community partners to explore games' transformative potential in education and social contexts through its Civic Systems, Media & Emotional Intelligence pillar.

Justin Sirignanoمشاهده پروفایل

استاد

• Applied Mathematics
• Machine Learning
• Financial Mathematics
• +۷ مورد دیگر

Justin Sirignano is a Professor of Mathematics at the University of Oxford, affiliated with the Mathematical Institute. His research bridges Applied Mathematics, Machine Learning, and Financial Mathematics, developing novel mathematical frameworks and computational methods. Education: B.A. in Mathematics, Princeton University PhD in Mathematics, Stanford University Chapman Fellow, Imperial College London His research focuses on theoretical and applied aspects of machine learning, particularly in mean-field analysis of neural networks , deep learning for PDEs/SDEs , and scientific machine learning . He has pioneered methods for solving complex financial and scientific problems using data-driven approaches. His recent publications emphasize recurrent neural networks, reinforcement learning, and PDE closure models with applications in turbulence simulation and hypersonic flows. These works span numerical methods, optimization, and stochastic processes. Scientific Awards: 2014 SIAM Financial Mathematics and Engineering Conference Paper Prize Grants & Collaborations: He has secured over $16.5 million in funding from agencies like ONR, NSF-EPSRC, and DoE. His PhD students hold positions at J.P. Morgan, Bank of America, and other institutions. Labs & Teams: He leads research groups in Machine Learning and Mathematical Finance at Oxford, collaborating with institutions like Notre Dame, Boston University, and UIUC.

• Marketing Analytics
• Electronic Commerce
• Online Advertising
• +۸ مورد دیگر

Prof. Dr. Bernd Skiera is a leading Marketing Professor at Goethe University Frankfurt since 1999 and a member of the managing board of the efl - The Data Science Institute. His work bridges information systems and marketing, with a focus on data-driven decision making and digital transformation.

• Artificial Intelligence
• Quantum Computing
• Theoretical Computer Science
• +۳ مورد دیگر

Cem Say is a Professor in the Department of Computer Engineering at Boğaziçi University's Faculty of Engineering, where he has established himself as a leading researcher in theoretical computer science and artificial intelligence. His academic journey began with the completion of his doctoral dissertation titled Qualitative System Identification in 1992, which was the first thesis of Boğaziçi University's Computer Engineering PhD program. Professor Say's research interests span multiple domains of computer science, with significant contributions to quantum computing, artificial intelligence, and theoretical computer science. His early work focused on qualitative reasoning and simulation, particularly through the QSIM algorithm, where he made significant improvements to filtering techniques and addressed challenges in representing physical systems. Over time, his research evolved toward quantum computation, where he has made substantial contributions to quantum finite automata theory, space-bounded quantum computation, and quantum complexity classes. His recent work explores the energy complexity of computation, bridging theoretical computer science with thermodynamics. His publication record shows a clear evolution from classical AI and qualitative reasoning toward quantum computation. The most recent articles demonstrate his focus on space-bounded quantum computation, energy complexity of regular languages, and interactive proof systems with minimal resources. His work consistently addresses fundamental questions about computational limits, particularly in quantum and sublogarithmic-space models. Professor Say has also made significant contributions to science communication through several books written for general audiences, including 50 Soruda Yapay Zekâ (2018), Yeni Dünya, Yeni Ağ (2020), and En Hakiki Mürşit (2021), which explain complex concepts in artificial intelligence and scientific methodology in accessible terms. Throughout his career, Professor Say has been actively involved in the Turkish academic community, editing proceedings for multiple Turkish symposia on artificial intelligence and neural networks. His doctoral dissertation established foundational work in qualitative system identification, and his subsequent research has consistently pushed boundaries in theoretical computer science, particularly in quantum computation where he has collaborated extensively with Abuzer Yakaryılmaz and other researchers.

Gabriel Wainerمشاهده پروفایل

استاد

• Modelling and Simulation Methodologies
• Discrete Event Systems
• Real-Time Modelling
• +۷ مورد دیگر

Dr. Gabriel Wainer is a Professor in the Department of Systems and Computer Engineering at Carleton University's Faculty of Engineering and Design. He leads the Advanced Real-Time Simulation Lab and specializes in modeling and simulation methodologies, particularly focusing on discrete event systems, real-time modeling, cellular automata, and DEVS formalism. Research Interests: Discrete event systems, DEVS formalism, cellular automata, real-time simulation, IoT applications, and parallel/distributed simulation Affiliation: Carleton University Recent publications highlight his work in advanced simulation frameworks, energy-efficient 5G systems using deep reinforcement learning, and pandemic modeling with cellular automata. His lab develops tools like PROMETHEUS and Devsmap for standardized DEVS model representation, while also exploring applications in wireless communication, building energy systems, and behavioral epidemiology.

Robert M. Weikle, IIمشاهده پروفایل

استاد

• Millimeter-wave electronics
• Terahertz technology
• Applied electromagnetics
• +۹ مورد دیگر

Robert M. Weikle, II is a Professor in the Charles L. Brown Department of Electrical and Computer Engineering at the University of Virginia, with a courtesy appointment in the Department of Physics. He earned his B.S. from Rice University (1986), M.S. (1987), and Ph.D. (1992) in Electrical Engineering from Caltech, followed by postdoctoral work at Chalmers University of Technology (1992). His research focuses on millimeter-wave and terahertz electronics , applied electromagnetics, integrated antennas, low-noise sensors, and heterogeneous integration of compound semiconductors. His work bridges electronics and photonics for spectrum access, with applications in astronomy, spectroscopy, and metrology. He has published extensively on micromachined silicon substrates, superconducting materials, and emerging technologies. Scientific Awards: IEEE Microwave Prize (1993) David A. Harrison III Award (1999) University of Virginia All-University Outstanding Teaching Award (2000) Edlich-Henderson Innovator of the Year (2016) Fulbright Scholar (2001) As Chief Technology Officer and co-founder of Dominion Microprobes, Inc., he commercializes micromachined wafer probes for high-frequency metrology. His lab, located in E220 Thornton Hall and the Jesse W. Beams Physics Building, has produced 15+ recent publications on submillimeter-wave devices, THz probes, and calibration techniques.

Per Enqvistمشاهده پروفایل

دانشیار

• Optimization
• Operations Research
• Systems Engineering
• +۶ مورد دیگر

Per Enqvist is an Associate Professor in the Division of Numerical Analysis, Optimization and Systems Theory within the Department of Mathematics at KTH Royal Institute of Technology, Stockholm, Sweden. He has held this position since 2009 after progressing from Assistant Professor (2006-2009) and post-doctoral roles at INRIA France and CNR Italy. His academic background includes: Ph.D. in Optimization and Systems Theory from KTH (2001), supervised by Professor Anders Lindquist M.Sc. in Engineering Physics (Civilingenjör) from KTH (1994) with Applied Mathematics focus Post-doctoral studies at INRIA Sophia-Antipolis (2003-2004) and CNR Padova (2001-2003) Enqvist's research centers on mathematical modeling of stochastic processes, scheduling, and queueing theory with applications across operations research, systems engineering, and signal processing. His principal interests span Optimization, Operations Research, Systems Engineering, Signal Processing, Mathematical Systems Theory, and Modeling and Simulation. He has made significant contributions to spectral estimation, covariance interpolation, and resource allocation frameworks. Publication analysis reveals an evolution from foundational systems theory work (2000s) on spectral estimation and minimal realization toward applied optimization in healthcare operations (2010s-2020s). Recent articles address radiation therapy scheduling and contact center modeling using queueing theory with risk-sensitive measures like CVaR, while earlier work established theoretical frameworks for covariance interpolation and passive system synthesis. No scientific awards are documented in the provided information. He has received funding from Vetenskapsrådet (Swedish Research Council) and led the ACCESS seed project on "Robust Spectral Estimation". Enqvist is course responsible for multiple master's program tracks including Aerospace systems and Industrial Engineering, and oversees the Optimization and Systems Theory seminar series. No student advisement details are provided. He maintains affiliations with the ACCESS Linnaeus centre, Center for Industrial and Applied Mathematics (CIAM), and serves on the Swedish Operations Research Society (SOAF) board.