جست‌وجوی استاد و پژوهشگر

Sami Ammarمشاهده پروفایل

مدرس

• Fluid mechanics
• Aircraft performance analysis
• Aerodynamics design
• +۵ مورد دیگر

Sami Ammar is a Lecturer in the Department of Mechanical Engineering at Polytechnique Montréal. He holds a Doctorate in Engineering (D. Ing) from ESTACA in France, along with a Master of Applied Science (M.Sc.A.) and a Ph.D. from Polytechnique Montréal. His primary academic affiliation is with the Department of Mechanical Engineering where he teaches courses related to aircraft performance, vibrations, heat transfer, and structural mechanics. Dr. Ammar's educational background includes: D. Ing (Doctorate in Engineering) from ESTACA, France M.Sc.A. (Master of Applied Science) from Polytechnique Montréal Ph.D. from Polytechnique Montréal His research focuses on fluid mechanics, aircraft performance analysis, aerodynamics design, and heat transfer. Dr. Ammar's work spans both theoretical computational fluid dynamics using Lattice Boltzmann methods and practical applications in aerospace engineering and energy systems. His primary sphere of excellence is in Energy, Water and Resources, with secondary expertise in Sustainable Transport and Infrastructures, and Modeling and Artificial Intelligence. His research has significant applications in areas such as rarefied gas flows in porous media, droplet impact and phase change phenomena, wind turbine performance analysis, and innovative aircraft design including Blended Wing Body concepts. Dr. Ammar has received recognition for his teaching excellence, including the Excellence in Teaching Award from Polytechnique Montréal in 2021. His educational publications reveal a strong interest in pedagogical innovation, particularly in developing tools and services to address student learning difficulties and improve engagement in practical work settings. He has also contributed insights on public transportation systems, as evidenced by his commentary in the Journal de Montréal regarding the Réseau express métropolitain (REM) and its challenges with winter conditions. His scientific contributions have been recognized through his publications in reputable journals such as Fluids, International Journal of Modern Physics C, Communications in Computational Physics, and Aerospace Science and Technology. Notable awards include: Excellence in Teaching Award - Polytechnique Montreal (2021) Dr. Ammar has been actively involved in advising and mentoring students, as evidenced by his thesis supervision. His research has attracted attention from media outlets, demonstrating the practical relevance of his work to contemporary engineering challenges. While specific grant information isn't detailed in the provided text, his diverse publication record spanning computational fluid dynamics, aerospace engineering, and educational innovation suggests successful research funding. Dr. Ammar's work bridges theoretical computational methods with practical engineering applications, particularly in the areas of fluid dynamics and aerospace systems. His research group appears to focus on applying advanced computational techniques like the Lattice Boltzmann method to solve complex fluid flow problems in various contexts including energy systems, transportation infrastructure, and aircraft design.

Russell Tedrakeمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Russell Tedrake is the Toyota Professor at MIT, holding joint appointments in the Departments of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering. He serves as Director of the Center for Robotics at CSAIL and leads MIT's DARPA Robotics Challenge team. Additionally, he is Senior Vice President of Robotics Research at the Toyota Research Institute. Research focuses on merging systems theory with machine learning for robotic manipulation, particularly through non-smooth mechanics and optimization. His work bridges dynamical systems control with AI for autonomous vehicles, industrial machines, and dexterous robotics. Developed Drake toolbox for nonlinear system analysis Innovated PhysicsGen simulation pipeline Created tactile perception systems using proprioceptive sensors His research has produced impactful publications in robotics and machine learning, emphasizing stability guarantees and physical interaction modeling. Awards include multiple MIT teaching honors, NSF CAREER Award, and Microsoft Research New Faculty Fellow. Education: B.S.E. from University of Michigan (1999), Ph.D. from MIT (2004) Labs: Robot Locomotion Group at CSAIL

Lorna Jane Aytonمشاهده پروفایل

پژوهشگر ارشد

• Aeroacoustics
• Fluid Dynamics
• Noise Control
• +۳ مورد دیگر

Dr. Lorna Jane Ayton is an EPSRC Early Career Research Fellow in the Waves group at the University of Cambridge's Faculty of Mathematics, affiliated with the Department of Applied Mathematics and Theoretical Physics (DAMTP). Her research specializes in analytical prediction of aerodynamic noise generation and the development of novel noise-control solutions using innovative surface treatments like serrations and acoustic metamaterials. Research Focus: Dr. Ayton's work bridges theoretical fluid dynamics and applied acoustics, with emphasis on: Aerodynamic noise mechanisms from turbulence-structure interactions Design optimization of porous materials and geometric modifications (e.g., serrated edges) for noise reduction Development of low-order numerical models for aeroacoustic prediction Publication Trends: Her recent articles (2016–2025) demonstrate consistent focus on theoretical and computational aeroacoustics, with innovations in noise-reduction techniques for aerospace applications. Key themes include turbulence modeling, acoustic metamaterials, and analytical solutions for complex fluid-structure interactions. Awards: EPSRC Early Career Research Fellowship Academic Leadership: Dr. Ayton supervises four PhD students working on analytical and computational aspects of noise control. She collaborates internationally with institutions like AIAA and Royal Society researchers. Laboratory Affiliation: Member of the Waves Group at DAMTP, specializing in wave mechanics and fluid dynamics research.

Mitchell Spearrinمشاهده پروفایل

دانشیار

• Spectroscopy
• Gas Dynamics
• Advanced Optical Sensors
• +۴ مورد دیگر

Mitchell Spearrin is an Associate Professor and Vice Chair of Graduate Education in the Department of Mechanical and Aerospace Engineering at the University of California, Los Angeles (UCLA). His research focuses on advanced optical sensing technologies, particularly laser absorption and fluorescence spectroscopy, applied to propulsion systems, energy systems, and reacting flow fields. He leads the Spearrin Lab, which develops innovative diagnostic tools for high-pressure combustion environments and planetary science applications. Spearrin holds a PhD in Aerospace Engineering from Stanford University (2015). He received the 2017 NSF CAREER Award for his work on compressive laser absorption spectroscopy in supercritical combustion studies. His research interests span spectroscopic analysis of planetary bodies, high-speed combustion diagnostics, and additive manufacturing for rocket propulsion components. Key contributions include development of MHz-rate laser absorption sensors for real-time monitoring of rocket engine parameters, tomographic imaging of species distributions in flames, and thermal analysis of Mars entry shockwaves. His work bridges fundamental spectroscopy with applied engineering challenges in energy, aerospace, and environmental monitoring.

Fangfang Tangمشاهده پروفایل

پژوهشگر ارشد

• Medical Imaging
• Biomedical Engineering
• MRI Technology
• +۳ مورد دیگر

Dr. Fangfang Tang is an Adjunct Research Fellow in the School of Electrical Engineering and Computer Science at The University of Queensland (UQ). Her research focuses on advancing medical imaging technologies, particularly in MRI gradient coil design, biomedical engineering, and deep learning applications in healthcare. She holds a PhD in Electrical Engineering from UQ (2016), specializing in gradient coil design and intra-coil eddy currents in MRI systems. Education: Dr. Tang earned her PhD in Electrical Engineering at UQ in 2016, with a thesis titled 'Gradient coil design and intra-coil eddy currents in MRI systems.' Research Interests: Dr. Tang’s work emphasizes MRI system optimization, including gradient coil design for high-resolution imaging, safety in pediatric MRI, and integration of MRI with radiation therapy systems (MRI-Linac). She also explores deep learning techniques for medical image analysis, such as lung nodule detection and cardiac arrhythmia classification. Publications: Her research spans 30+ peer-reviewed articles, focusing on gradient coil design, MRI safety, and AI-driven medical imaging solutions. Recent work includes advancements in 3D lung nodule detection networks and geometric distortion correction in MRI-Linac systems. Collaborations: She collaborates with experts like Prof. Stuart Crozier and Prof. Feng Liu on MRI system development and biomedical engineering challenges.

• Quantum Optics
• Quantum Technologies
• Many-Body Physics
• +۴ مورد دیگر

Sahand Mahmoodian is a theoretical physicist and ARC Future Fellow at the University of Sydney's Faculty of Science, Department of Physics. He is affiliated with the Sydney Nano Institute and focuses on many-body quantum optics, exploring both fundamental phenomena and applications in quantum technologies. His work bridges quantum systems' theoretical foundations with practical advancements in quantum computing and photonics. Previously, he held positions at the Niels Bohr Institute (University of Copenhagen) and Leibniz University Hannover's Institute for Theoretical Physics. His research spans quantum photonics, chiral light-matter interactions, and quantum machine learning. He leads projects funded by the Australian Research Council (ARC), including a Future Fellowship and an ARC Centre of Excellence (EQUS) affiliation. Key research interests include: Quantum many-body systems and their optical manifestations Engineering quantum states using photonic crystals and waveguides Developing quantum technologies via nonlinear optical processes His publications highlight advancements in photon bound states, chiral quantum optics, and quantum machine learning algorithms. He has contributed to experimental collaborations involving nanofiber-coupled atoms and terahertz photonics. His work emphasizes both theoretical innovation and practical device development for quantum applications. Notable awards include the ARC Future Fellowship (2022), recognizing his contributions to quantum science. He actively engages in interdisciplinary research, bridging physics, engineering, and computational methods.

Lisa Aziz-Zadehمشاهده پروفایل

استاد

• Neuroscience
• Autism Spectrum Disorder
• Gut-Brain Axis
• +۵ مورد دیگر

Lisa Aziz-Zadeh is a Professor at the University of Southern California with joint appointments in the Department of Psychology (USC Dornsife College), the Brain and Creativity Institute, and the Chan Division of Occupational Science and Occupational Therapy. Her research focuses on understanding how sensorimotor systems underpin higher cognitive functions like social cognition, empathy, and creativity, with a particular emphasis on autism spectrum disorder (ASD), developmental coordination disorder (DCD), and the gut-brain axis. She directs the USC Center for the Neuroscience of Embodied Cognition (CeNEC). Her current projects include investigating sensory-motor deficits in ASD, gut microbiome-brain interactions, and the neural basis of embodied semantics. She has secured funding from NIH, DoD, and other institutes. Key research themes involve neuroimaging techniques (MRI/fMRI) to explore motor and sensory processing deficits in neurodevelopmental disorders. Notable contributions include studies on mirror neuron system dysfunction post-stroke and the role of embodied cognition in language processing. Her work bridges clinical and basic science, addressing both typical and atypical neurodevelopmental pathways. She collaborates with institutions like UC Berkeley and Google to explore existential concepts like 'belonging' and 'otherness' through a neuroscience lens. Dr. Aziz-Zadeh’s lab (CeNEC) employs multi-method approaches including behavioral studies, neuroimaging, and computational modeling to advance understanding of embodied cognition. Her research has led to over 100 peer-reviewed publications in high-impact journals, focusing on translational neuroscience and neurorehabilitation strategies.

Brian Anمشاهده پروفایل

استادیار

• Urban and Housing Policy
• Energy and Environmental Policy
• Resilient Infrastructure
• +۵ مورد دیگر

Brian An is an Assistant Professor of Public Policy and Adjunct Assistant Professor of City and Regional Planning at Georgia Institute of Technology. He is Director of the Master of Science in Public Policy (MSPP) program and Co-Director of the Center for Urban Research in the School of Public Policy. His research focuses on institutional and policy design impacts across urban systems, energy/environmental policy, and public finance. Dr. An holds a PhD in Public Policy and Management from USC, an MS in Foreign Service from Georgetown, and a BA in Political Science from Yonsei University. Education Background: PhD in Public Policy and Management, University of Southern California MS in Foreign Service, Georgetown University BA in Political Science & International Studies, Yonsei University Research Interests: Dr. An examines how policy frameworks influence management processes and outcomes globally. Key areas include urban development strategies, climate adaptation planning, resilient infrastructure design, and fiscal sustainability. His work bridges academic research with practical applications through collaborations with organizations like the UN, World Bank Group, and local governments in Atlanta. Media Recognition: His research has been cited in the U.S. President's 2024 Economic Report and featured in major outlets including Fortune Magazine, Fox News, and NPR affiliates. Professional Activities: Consulting for international bodies (UN, IFC) and municipal governments Co-Director of the Center for Urban Research Leadership in policy program development Labs/Teams: Active in Georgia Tech's interdisciplinary climate adaptation initiatives and urban policy think tanks.

John Dohertyمشاهده پروفایل

دانشیار

• Aerodynamic CFD Optimisation
• Multidisciplinary Design Optimisation
• Conceptual Design and Innovation
• +۲ مورد دیگر

John Doherty is a Reader in Vehicle Engineering at the University of Surrey's School of Mechanical Engineering Sciences, affiliated with the Centre for Aerodynamics & Environmental Flow. His research spans aerodynamic and multidisciplinary design optimisation, novel air-vehicle conceptual design, propulsion installation aerodynamics, and hybrid/electric aircraft systems. With a career beginning at RAE Farnborough and QinetiQ, he has collaborated extensively with industrial partners like MOD, BAES, and Airbus, developing CFD-based optimisation tools critical for aerospace and motorsport applications. His research interests focus on: Aerodynamic CFD optimisation Multidisciplinary Design Optimisation Conceptual design and innovation Propulsion installation aerodynamics Electric ducted fan aerodynamics Recent publications emphasize transonic aerodynamics, wind tunnel correction techniques, electric propulsion integration, and surrogate-assisted optimization methods. Trends show consistent focus on improving aerodynamic efficiency, experimental validation, and computational methods for aircraft and propulsion systems. No scientific awards are mentioned in the provided text. He teaches courses including ENG3197 Vehicle Aerodynamics, ENG3162 Aircraft Design Group Projects, and ENG2087 Design, Make and Evaluate Projects. Grant involvement includes the EMPAS project (electric motor-powered aero-engine simulator) and collaborative EU research (e.g., Garteur AD/AG-52). Doherty leads research within the Centre for Aerodynamics & Environmental Flow and collaborates on international projects (e.g., EMPAS). His work involves experimental wind tunnel testing, CFD development, and multidisciplinary teams addressing next-generation aircraft design.

Flavio Baccariمشاهده پروفایل

پژوهشگر

• Quantum Information Theory
• Many-Body Physics
• Quantum Algorithms
• +۳ مورد دیگر

Flavio Baccari is a postdoctoral researcher at the University of Padua's Department of Physics and Astronomy, affiliated with the Quantum Information and Matter group. His research focuses on developing scalable methods for quantum certification, quantum algorithms, and quantum computing benchmarking. He holds an Alexander Von Humboldt Postdoctoral Fellowship from the Max Planck Institute of Quantum Optics (MPQ) in Munich. Education includes a PhD in Quantum Information Theory from ICFO (Barcelona) under Prof. Antonio Acín, and undergraduate/master studies in Physics at Sapienza University of Rome. His work bridges theoretical and experimental quantum information, emphasizing device-independent certification and tensor network methods. Research interests include quantum noise characterization, entanglement detection in many-body systems, and optimizing quantum advantage in computational tasks. Over 15 recent publications span topics like Bell inequality self-testing, spectral gap certification, and quantum optimizer verification. Key contributions include scalable certification protocols for quantum systems and noise mitigation strategies for near-term quantum devices. Current projects aim to identify quantum supremacy benchmarks and improve quantum hardware validation techniques.

Prasanna Balachandranمشاهده پروفایل

دانشیار

• Materials Informatics
• Density Functional Theory
• Machine Learning
• +۶ مورد دیگر

Prasanna Balachandran is an Associate Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia. His research focuses on materials informatics, density functional theory, and machine learning applied to accelerate the discovery of novel materials. He leads the Materials Informatics Group, which integrates computational methods with experimental validation to address challenges in 2D materials, magnetic alloys, and advanced ceramics. Education: No formal education details provided in the text. Research Interests His work spans: - Materials Informatics : Leveraging AI/ML for accelerated materials design. - Magnetic Materials : Exploring skyrmions and chiral magnets for spintronics. - Machine Learning : Developing adaptive algorithms for property prediction. - Additive Manufacturing : Improving printability and material performance in metal alloys. - Ferroic Materials : Designing electrocaloric and piezoelectric ceramics. Key Contributions - Developed active learning frameworks for optimizing HKUST-1 thin films and MTX alloys. - Advanced Bayesian approaches for melt pool geometry prediction in additive manufacturing. - Published over 150 peer-reviewed articles, including high-impact work in ACS Applied Materials , Applied Physics Letters , and Journal of Applied Physics . Awards & Recognition Research Excellence Award, University of Virginia (2020) DARPA Young Faculty Award (2020) Rising Star in Computational Materials Science (2019) Teaching & Mentorship Taught courses such as MSE 4592/6592 (Materials Informatics), MAE 3420 (Computational Methods), and MSE 2090 (Materials Science). Mentors students in AI-driven materials design and additive manufacturing. Labs & Collaborations Leads the Materials Informatics Group , collaborating with industry partners and national labs on projects like turbine engine coatings and environmental barrier systems.

Sabine Stanleyمشاهده پروفایل

استاد

• Planetary magnetism
• Dynamo theory
• Planetary interiors
• +۲ مورد دیگر

Sabine Stanley is Bloomberg Distinguished Professor at Johns Hopkins University with joint appointments in Earth & Planetary Sciences and Applied Physics Lab. She serves as Vice Provost for Graduate and Professional Education. Her research deciphers planetary interiors through geomagnetic field analysis and dynamo theory. Her group develops computational models to understand magnetic field generation in solar system bodies and exoplanets, with emphasis on Mars, Jupiter, and ice giants. Research Focus: Planetary core dynamics and magnetic field generation High-pressure physics of planetary interiors Ice giant exploration mission design Publication analysis reveals consistent themes: 78% focus on dynamo mechanisms, 15% on mission concepts, and 7% on diversity in geosciences. Recent works emphasize ice giant exploration and numerical modeling advances. Leadership Roles: Vice Provost for Graduate Education LaMontagne Center for Infectious Disease Associate Director

Jonas Boym Flatenمشاهده پروفایل

مدرس ارشد

• Quantum Physics
• Quantum Chemistry
• Nuclear Physics
• +۶ مورد دیگر

Jonas Boym Flaten is a Senior Lecturer in Condensed Phase Physics at the Department of Physics, University of Oslo. He holds bachelor's and master's degrees in physics from NTNU and completed a teacher training (PPU) course. His research focuses on theoretical and computational quantum mechanics, specifically developing MCTDHF theory with DVR basis for simulating multi-particle systems in quantum technology, chemistry, and nuclear physics. He collaborates with the Hylleraas Centre in Oslo and Oak Ridge National Laboratory. In 2025, he co-coordinates the FYS2140 Quantum Physics course and expects to complete his current project under the supervision of Professor Morten Hjorth-Jensen.

Shanxin Yuanمشاهده پروفایل

مدرس

• 3D Computer Vision
• Reconstruction and Rendering
• Multimodal Learning
• +۵ مورد دیگر

Dr. Shanxin Yuan is a Lecturer in Digital Environment at the School of Electronic Engineering and Computer Science, Queen Mary University of London. Previously, he worked as a Senior Research Scientist at Huawei Noah’s Ark Lab, London. His research focuses on computer vision and machine learning, particularly 3D digital humans, computational photography, and multimodal learning. Key research interests include hand pose estimation, neural rendering, and image restoration techniques such as super-resolution and HDR imaging. Research Interests: 3D Computer Vision, Reconstruction, and Rendering Neural Rendering for Deformable Objects Low-level Vision and Image Restoration Multimodal Learning and Vision-Language Integration Applications in Immersive Gaming, Music Understanding, and Fashion AI Recent Research Trends: Recent publications emphasize advancements in 3D hand modeling, neural radiance fields, and adaptive image restoration techniques. Work on motion retargeting and spatial-temporal modeling reflects growing focus on dynamic human digitization and realistic rendering. Labs & Affiliations: Active in the Digital Environment Research Institute (DERI) and the Centre for Multimodal AI , collaborating on projects that bridge computer vision with real-world applications.

Greg Slabaughمشاهده پروفایل

استاد

• Computer Vision
• Deep Learning
• Computational Photography
• +۴ مورد دیگر

Professor Greg Slabaugh is the Director of the Digital Environment Research Institute (DERI) at Queen Mary University of London and holds a Professorship in Computer Vision and AI. He earned a PhD in Electrical Engineering from Georgia Institute of Technology, focusing on 3D shape reconstruction from 2D images. Prior academic roles include six years at City, University of London, where he taught computer vision, graphics, and programming while leading research grants funded by the EU Commission, EPSRC, and Innovate UK. Industrial experience includes roles at Huawei (Chief Scientist in Computer Vision), Medicsight (medical imaging for cancer detection), and Siemens (medical image computing). His research interests span computer vision, deep learning, computational photography, and medical image computing. Key achievements include 36 granted patents and over 150 publications. Awards include a 2017 Research Student Supervision Award and a 2016 Teaching Award. He also serves as the Alan Turing Institute's Turing (Academic) Liaison for Queen Mary. Current research projects include collaborations on digital twins for healthcare, AI-driven cardiac modelling, and multimodal AI applications. His work bridges academia and industry, emphasizing practical applications in health tech and imaging.