جست‌وجوی استاد و پژوهشگر

• Fluid Mechanics
• Plasma Physics
• Turbulence
• +۳ مورد دیگر

Raffaele Marino is a Research Fellow at the CNRS affiliated with the Laboratory of Fluid Mechanics and Acoustics (LMFA) at École Centrale de Lyon. He specializes in studying the interaction between waves and turbulence in rotating stratified geophysical and astrophysical fluids, employing high-resolution numerical simulations and experimental observations. His research bridges fluid dynamics, plasma physics, and geophysics, with applications to solar wind, planetary atmospheres, and oceanic flows. Marino holds a Doctorate in Physics (2009) and has held postdoctoral roles at the National Center for Atmospheric Research (NCAR, USA) and the University of California Berkeley, leading projects like the TILDAE mission under NASA's GRIPS program. He later conducted Marie Curie research at École Normale Supérieure de Lyon before joining LMFA. His work focuses on turbulence intermittency, energy transfer mechanisms, and the role of rotation/stratification in driving large-scale structures. Key themes include solar wind turbulence decay, magnetic reconnection effects, and dual energy cascades in plasmas. He collaborates internationally with institutions like UC Berkeley, NASA, and the Solar Orbiter mission, contributing to both observational and computational advancements in fluid dynamics.

• Information Science
• Human-Computer Interaction
• Data Science
• +۱ مورد دیگر

Daniel Ouellette serves as an Intermittent Lecturer (adjunct) in the School of Information at the University of Michigan, based at 105 S. State St. in Ann Arbor. His role as part-time faculty supports the school's educational mission through specialized instruction. His academic focus centers on core Information Science disciplines, with specific expertise in: Human-Computer Interaction Data Science methodologies Information Systems design Information Retrieval systems Digital Library infrastructures Socio-technical aspects of information No scientific awards, research grants, or doctoral student mentorship activities were documented in the available materials. His contributions primarily involve teaching within the school's academic programs as an adjunct faculty member.

Stéphane Mallatمشاهده پروفایل

استاد

• Signal Processing
• Wavelet Theory
• Machine Learning
• +۴ مورد دیگر

Stéphane Mallat is a Professor at the Collège de France, holding the Chair of Data Sciences. He is also affiliated with the École normale supérieure in Paris, where his address is located. His research focuses on signal processing, wavelet theory, and their applications in machine learning and data sciences. Mallat pioneered wavelet transforms for signal decomposition and has contributed to scattering transforms for invariant feature extraction in deep learning. His work bridges applied mathematics, harmonic analysis, and computational methods, with impactful applications in image processing, audio analysis, and quantum chemistry. Publicly listed articles span from foundational wavelet theory (1989) to recent advances in scattering networks (2020). His research trends emphasize geometric signal representations, sparse approximations, and interdisciplinary applications across physics and engineering. His CV and publications are available through institutional links, though specific awards or grants are not explicitly detailed in the provided texts. He collaborates extensively with researchers in mathematics and computer science, advancing theoretical frameworks with practical implementations.

Marta Garaulet Azaمشاهده پروفایل

استاد

• Chronobiology
• Nutrition
• Obesity
• +۳ مورد دیگر

Marta Garaulet Aza is a Spanish Professor of Physiology at the University of Murcia and a leading Researcher at Brigham and Women's Hospital (Harvard University). She is also a Nutritionist , Chronobiology expert , and Businesswoman with a Master's in Public Health from Harvard University. Education : PhD in Pharmacy (University of Murcia, 1999), Master's in Public Health (Harvard University), Nutrition specialization (CEU San Pablo University, 2004-2008) Her research focuses on chronobiology and obesity , particularly how meal timing , circadian rhythms , and genetics influence metabolic health . The 15 most recent publications highlight trends in time-restricted eating , melatonin effects on metabolism , and gene-environment interactions related to circadian patterns. Notable scientific awards include: Roxbury Multiservice Center award (1990) Nutrition & Santé Career Award (2011) Dr. Gregorio Marañón Researcher Award (2012) SEEDO Best Obesity Research Award (2015) Grand Prix de la Science de l'Alimentation (2017) Cubi Healthy Gastronomy Award (2018) Vermeil Medal (2020) She serves on the steering committee of the Spanish Nutrition Foundation (FEN) and is a Full Academician of the National Academy of Nutrition , while directing the Garaulet Nutrition Centers . Her work has been featured in media outlets like Masterchef and Documentos TV .

• Harmonic Analysis
• Applied Mathematics
• Machine Learning
• +۴ مورد دیگر

Christina Frederick is an Associate Professor in the Department of Mathematical Sciences at New Jersey Institute of Technology. Her research spans computational mathematics, harmonic analysis, and machine learning applications in robotics and ocean acoustics. Active in time-frequency analysis and multiscale inverse problems Principal Investigator on NSF and Navy-funded projects Collaborates on seabed classification, intermittent diffusion algorithms, and sensor deployment Current work focuses on computational methods for autonomous systems and mathematical foundations of Riesz bases. She has contributed to robotics path planning and sonar imaging techniques. Her recent publications (2022-2024) demonstrate interdisciplinary integration of harmonic analysis with machine learning for applications in seabed classification, mobile sensor deployment, and robotics coordination. Key trends include time-frequency analysis, computational methods for autonomous systems, and Gaussian processes in acoustics. NSF Grant: Applied and computational time-frequency analysis (2023-2026) Navy Grant: Sensor deployment algorithms (2021-present) NSF Grant: Multiscale inverse problems in sonar imaging (2017-2020) Frederick's work bridges theoretical mathematics with practical engineering challenges, particularly in sensor network optimization and acoustic signal processing.

Abhijit Patwardhanمشاهده پروفایل

استاد

• Cardiovascular Control
• Signal Processing
• Neuroscience
• +۳ مورد دیگر

Abhijit Patwardhan, Ph.D., is a Professor and Department Chair in the F. Joseph Halcomb III, M.D. Department of Biomedical Engineering at the University of Kentucky. He holds a Ph.D. in Biomedical Engineering from the University of Kentucky (1992) and a B.E. in Mechanical Engineering from the College of Engineering, Pune, India (1984). His research focuses on cardiovascular control mechanisms, signal processing in medical diagnostics, and the physiological impacts of music and hypoxemia on neonatal and pediatric populations. He has held leadership roles, including Director of Graduate Studies (2004–2019) and Interim Chair (2015–2017), and has contributed to interdisciplinary projects in artificial gravity training and cardiovascular autonomic responses to particulate exposures. Dr. Patwardhan’s work spans clinical and computational domains, with notable contributions to understanding intermittent hypoxemia in preterm infants, neural-cardiovascular interactions during music listening, and the dynamics of Toxoplasma gondii infection. His Cardiac Rhythm Lab employs advanced signal processing techniques and machine learning for medical imaging analysis and disease modeling. He has collaborated on studies involving centrifuge training for orthostatic tolerance and the development of non-invasive monitoring systems using video-derived physiological signals. His professional activities include service to the Stanley and Karen Pigman College of Engineering and editorial roles in biomedical journals. Though no specific awards are listed, his extensive publication record reflects sustained excellence in cardiovascular and biomedical engineering research. Ongoing projects likely include translational studies on neonatal cardiorespiratory physiology and computational tools for pathogen lifecycle analysis.

Leonid Rubchinskyمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Mathematical Biology
• Mathematical & Computational Neuroscience
• +۳ مورد دیگر

Leonid Rubchinsky is an Associate Professor in the Department of Mathematical Sciences at Indiana University–Purdue University Indianapolis (IUPUI), affiliated with the Stark Neurosciences Research Institute, Indiana University School of Medicine. His research focuses on computational neuroscience, mathematical biology, and dynamical systems applied to understanding basal ganglia function in health and Parkinson's disease. He holds academic appointments since 2004, including postdoctoral research at UC Davis (2001–2004). Education: Ph.D. in Physics (2000, Russian Academy of Sciences), M.S. in Physics (1997, UC San Diego), B.S. in Physics (1995, University of Nizhny Novgorod). Research interests include neural oscillations, synchronization mechanisms, and pathophysiological dynamics in Parkinson's disease. His work bridges mathematical modeling and experimental neuroscience to elucidate basal ganglia operations and therapeutic strategies. Publications (2008–2013) emphasize beta-band synchronization, deep brain stimulation effects, and theoretical frameworks for tremor and neural network dysfunction. Awards include IUPUI Favorite Professor recognition (2006, 2010) and international grants. Professional roles include panelist for NSF/NIH computational neuroscience grants and membership in the Organization for Computational Neuroscience Program Committee. He has organized student competitions at annual neuroscience meetings.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Ning Zhang is a researcher affiliated with Tsinghua University , Department of Electronic Engineering, focusing on interdisciplinary applications of computer science and artificial intelligence in domains such as medical imaging, fault diagnosis, and multimodal systems. Their work bridges theoretical advancements with practical implementations in engineering, agriculture, and finance. Research Interests : Machine learning, signal processing, graph neural networks, and neuromorphic computing. Key Contributions : Recent publications highlight innovations in event-based tracking, digital twin systems, and reinforcement learning integration with vision-language models. Technological Focus : Applications include fault diagnosis in rotating machinery, medical image segmentation (CT-Net), and AI-driven urban risk assessment. The 2024-2025 publication trends reveal a strong emphasis on deep learning for remote sensing, reinforcement learning security, and stochastic control systems. Collaborations span institutions like the University of Manchester, Peking University, and Washington University in St. Louis.

• Computer Vision
• Machine Learning
• Signal Processing
• +۶ مورد دیگر

Qian Huang is a Professor in the Department of Computer Science at Sun Yat-sen University's School of Computer Science and Engineering. With over 350 publications spanning from 1992 to 2025, Dr. Huang has established themselves as a leading researcher in multiple interdisciplinary fields at the intersection of computer science, engineering, and applied mathematics. Dr. Huang's research spans several critical domains in modern computing. Their primary interests include computer vision with applications in medical image analysis, machine learning with emphasis on transformer architectures and federated learning, signal processing for video compression, and wireless communications for IoT applications. Recent work demonstrates significant contributions to nuclei segmentation in cervical cell images, advanced video compression techniques using spatiotemporal modeling, and predictive maintenance systems for industrial equipment that incorporate uncertainty quantification. An analysis of Dr. Huang's 15 most recent publications reveals a strong trend toward interdisciplinary research that bridges theoretical computer science with practical applications. Their work consistently addresses real-world challenges in healthcare diagnostics, industrial automation, and communication systems. The publications demonstrate expertise in developing novel deep learning architectures while maintaining theoretical rigor in mathematical foundations. Multiple publications in IEEE Transactions journals across various domains Regular contributions to top-tier conferences including ICASSP, ICIP, NeurIPS, and CVPR Collaborations with researchers from leading institutions globally Dr. Huang's research program appears well-funded through collaborations with industrial partners and Chinese national research grants, though specific grant information isn't detailed in the publication record. Their work on federated learning frameworks and medical image analysis suggests strong connections with healthcare technology companies and medical research institutions. The extensive publication record across multiple domains indicates leadership of a substantial research group with expertise spanning computer vision, machine learning, and signal processing.

• Complexity Science
• Non-Equilibrium Systems
• Theoretical Physics
• +۳ مورد دیگر

Professor Kim Christensen is a Professor of Theoretical Physics at the Department of Physics within the Faculty of Natural Sciences at Imperial College London. His research focuses on theoretical and numerical aspects of complex systems, particularly the spontaneous emergence of patterns and organization in non-equilibrium systems. He holds affiliations with the Centre for Cardiac Engineering, Centre for Complexity Science, Condensed Matter Theory Group, and other interdisciplinary initiatives. Christensen earned a Ph.D. in Science (1993) and a Master of Science (1990) from the University of Århus, Denmark. His work integrates theoretical, computational, and experimental studies across disciplines including geology, atmospheric physics, biology, sociology, medicine, and fire safety. A key contribution is the textbook Complexity and Criticality (2005), co-authored with Nicholas Moloney, which is widely used globally. His research interests emphasize interdisciplinary complexity science, with a focus on applying transferable tools to real-world systems. Recent work includes studies on atmospheric rivers, cardiac electrophysiology modeling, quantum networks, and venture capital network dynamics. He has over 8,150 citations (Google Scholar, June 2025), reflecting his impactful contributions to identifying universal research questions and knowledge transfer. Labs/Teams: Condensed Matter Theory Group, Physics of Life, ElectroCardioMaths Programme Grants/Awards: Not explicitly listed but implied by citation impact and textbook影响力

• Hardware Security
• Machine Learning Acceleration
• Hardware-Software Co-design
• +۳ مورد دیگر

Sai Manoj P D is Assistant Professor in the Electrical and Computer Engineering Department at George Mason University, where he leads the Hardware and AI Research Team (HArt Lab). His research focuses on hardware security, machine learning acceleration, and hardware-software co-design for emerging computing platforms. Current projects investigate federated learning approaches for malware detection on heterogeneous devices, energy-efficient computing architectures for intermittent power sources, and hardware acceleration of machine learning algorithms. The HArt Lab develops novel architectures for secure and efficient computing across edge devices, embedded systems, and data centers. Research Sponsors: National Science Foundation (NSF) Virginia Commonwealth Cyber Initiative (CCI) DARPA

Oliver Schneiderمشاهده پروفایل

دانشیار

• Haptic Technology
• User Experience (UX) Design
• Digital Fabrication
• +۵ مورد دیگر

Oliver Schneider is an Associate Professor at the University of Waterloo's Department of Information Systems, specializing in haptic technology, human-computer interaction, and sustainable digital fabrication. His research focuses on advancing haptic experience design, accessibility in technology, and innovative approaches to 3D printing sustainability. Key contributions include the Haptic Experience Inventory (HXI), the Proteus Card Deck for remote play, and the Substiports system for sustainable 3D printing. His work bridges engineering and psychology, addressing challenges in user perception, inclusive design, and multimodal interaction. Notable projects include the Haptic Playground (empowering accessible haptic prototyping) and TactJam (collaborative vibrotactile design). He explores intersections between haptics and robotics, such as multi-robot supervision systems and blind-user virtual world interfaces. Research interests span Human perception in haptic systems Design methodologies for tangible interfaces Sustainable manufacturing techniques Accessibility in virtual and augmented reality Recent publications analyze intermittent interaction in fabrication workflows, unified haptic experience models, and user-defined gestures in virtual environments. Articles emphasize practical applications like assistive devices and eco-friendly fabrication.

Theodosis Dimitrakosمشاهده پروفایل

دانشیار

• Applied Probability
• Stochastic Operations Research
• Optimal Control
• +۵ مورد دیگر

Theodosis Dimitrakos is an Associate Professor at the Department of Mathematics, University of the Aegean, specializing in Applied Probability and Stochastic Operations Research . His work focuses on optimal control of stochastic systems across diverse domains. University of the Aegean School of Sciences Department of Mathematics His research spans epidemic processes , biological populations , preventive maintenance , vehicle routing , and medical emergency systems . Publications emphasize semi-Markov decision processes and dynamic programming . Recent articles analyze stochastic vehicle routing, maintenance optimization, and predator-prey dynamics. Key trends include stochastic demand modeling , penalty systems , and multi-compartment logistics . Teaching courses: Undergraduate and Postgraduate Statistics , Probability I , and Stochastic Modeling . Author of the textbook Probability, Statistics and Stochastic Models (Eudoxos code: 143557808).

Maria Kennedyمشاهده پروفایل

استاد

• Membrane Technology
• Water Treatment
• Desalination
• +۵ مورد دیگر

Professor Maria Kennedy is an academic specializing in membrane technology and water treatment with 11 years of research experience. Her work focuses on membrane fouling, scaling, and cleaning, particularly in desalination applications. She leads international projects in Israel (West Bank) and Jordan regarding brackish/sea water desalination. Her research innovates in hydrothermal carbonization of biomass and optimization of reverse osmosis systems. Key research areas include: Membrane-based water treatment technologies Desalination plant optimization Water-Energy Nexus solutions Environmental sustainability of water infrastructure Recent work emphasizes techno-economic analysis of PV-integrated desalination systems for low-income regions, and development of advanced pretreatment methods using hydrothermal carbonization. Her studies on hydraulic systems and water distribution equity address global water scarcity challenges through both technical and social equity lenses. Publications highlight contributions to: Algal bloom mitigation in SWRO systems Bacterial growth potential measurement Smart dosing algorithms for antiscalants Nonrevenue water assessment methodologies No academic awards are explicitly listed in the provided texts. She collaborates on international projects but no specific grants/teams are detailed.

Metin Hünerمشاهده پروفایل

استادیار

• Neuroscience
• High Power Ultrasonic Applications
• Electromagnetic Compatibility
• +۳ مورد دیگر

Metin Hüner is an Assistant Professor at the Department of Electronics and Communication Engineering, Istanbul Technical University (ITU). He holds a PhD in Physical Engineering from ITU (1998), MSc in Physics Engineering (1993), and BSc in Electronics and Communications Engineering (1991). His research focuses on Neuroscience (neuronal dynamics, ion channel conductivity) and High Power Ultrasonic Applications (ultrasonic cleaning systems, emulsion systems design). He has authored/co-authored over 10 publications and supervised 5 theses. Teaching includes graduate courses like Mathematical Methods in Electrical Engineering (ELE 519) and undergraduate courses like Basics of Electrical Circuits (EHB 211E). Professional experience includes roles as Quality Manager at 2M Cable (2003-2006) and Quality/Test Engineer at Teleco Cable (2000-2003). Research highlights include investigations into ultrasonic pressure distribution, automotive EMC simulation, and neuronal bifurcation analysis. Lab involvement includes projects on ultrasonic emulsion systems design and acceleration logger development. His work bridges theoretical physics (superconductivity, nonlinear dynamics) with applied engineering (acoustic systems, biomedical instrumentation).