جستجوی استاد راهنمای دانشگاهی

Neville Hoganمشاهده پروفایل

استاد

• Rehabilitation Engineering
• Robotics
• Motor Neuroscience
• +۳ مورد دیگر

Neville Hogan is a Professor of Mechanical Engineering and Brain & Cognitive Sciences at MIT, and Director of the Newman Laboratory for Biomechanics and Human Rehabilitation. He holds a Ph.D. from MIT and has been a faculty member since 1979, leading roles in the Mechanical Engineering department's System Dynamics and Control division. His research bridges biology and engineering, focusing on motor neuroscience, rehabilitation robotics, and human-robot interaction. He co-founded Interactive Motion Technologies, Inc. and is a board member at Advanced Mechanical Technologies, Inc. Education: Dip. Eng. (Dublin College of Technology), M.S., M.E., and Ph.D. (MIT) Research interests include developing robots for neurological rehabilitation, such as gentle physiotherapy devices for stroke patients. His work emphasizes physically cooperative machines and human balance control analysis. Awards include Honorary Doctorates from Delft University and Dublin Institute of Technology, and the Silver Medal from Ireland’s Royal Academy of Medicine. Awards: Honorary Doctorates, Silver Medal, and other distinctions Led the Newman Lab, focusing on biomechanics and human rehabilitation. Advised numerous students (not listed here). His publications explore dynamic primitives, impedance control, and human-robot interaction, with applications in exoskeletons and rehabilitation therapies.

Philippe Dixonمشاهده پروفایل

استادیار

• Biomechanics
• Neuroscience
• Machine Learning
• +۳ مورد دیگر

Dr. Philippe Dixon is an Assistant Professor in the Department of Kinesiology & Physical Education at McGill University, with a division in Biomechanics and Neuroscience. He holds adjunct professor roles at the University of Montreal (School of Kinesiology and Physical Activity Sciences) and the University of Laval (Department of Kinesiology). His research focuses on human movement biomechanics using motion capture systems and wearable sensors, combined with machine learning for health and athletic performance optimization. He has expertise in gait analysis, muscle coactivation patterns in cerebral palsy, and predictive modeling of physiological states. Dr. Dixon earned a Post-doctoral fellowship in Public Health at Harvard University, a PhD in Engineering Science from the University of Oxford, and dual degrees in Biomechanics and Physics from McGill University. His education includes a Bachelor of Education in Mathematics and Physics (McGill), a Master of Science in Biomechanics (McGill), and a PhD in Engineering Science (Oxford). He has received grants such as the NSERC Discovery Grant (2022–2027) and the FRQSC AUDACE Grant (2022). His work emphasizes wearable sensor integration, with contributions to datasets like NACOB and tools like OpenOFM. He currently supervises Master’s and PhD students in biomechanics and machine learning applications. Key research themes include gait adaptations on uneven surfaces, machine learning for cough detection via smart garments, and musculoskeletal coordination in clinical populations. His articles span biomechanical modeling, wearable sensor validation, and neuro-musculoskeletal analysis, reflecting interdisciplinary innovation in human movement science.

Robert Xiaoمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۴ مورد دیگر

Robert Xiao is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Designing for People research cluster. He holds a Ph.D. from Carnegie Mellon University and a BMath from the University of Waterloo. His research focuses on interactive technologies, including VR/AR interfaces, sensing systems, and cybersecurity. Notable contributions include Lumitrack (tracking system), TouchTools (touch interaction), and CVE-2023-37271 (Python sandbox exploit). Education: Ph.D., Human-Computer Interaction Institute, Carnegie Mellon University; BMath, Computer Science & Combinatorics, University of Waterloo Affiliations: Core member of UBC's Designing for People cluster Research interests span novel input modalities, mixed-reality systems, and security challenges. He actively competes in DEF CON CTF (multiple 1st places) and publishes in top venues like CHI, UIST, and ISMAR. Recent work explores VR decision-making, low-latency tracking, and collaborative AR/VR environments. Awards: SIGCHI Outstanding Dissertation Award, CHI Honorable Mention, DIS Honourable Mention Teaching includes courses on computer systems (CPSC 213), human-computer interaction (CPSC 554X), and cybersecurity (CPSC 436S). His lab develops tools like SurfShare (surface sharing) and VirtualNexus (collaborative AR).

Shideh Dashtiمشاهده پروفایل

استاد

• Geotechnical Engineering
• Geomechanics
• Seismic Soil-Structure Interaction
• +۷ مورد دیگر

Shideh Dashti is a Professor and Associate Chair for Administration in Geotechnical Engineering & Geomechanics at the University of Colorado Boulder's Department of Civil, Environmental, and Architectural Engineering within the College of Engineering and Applied Sciences. She holds a PhD (2009) and MS (2005) from UC Berkeley and a BS (2004) from Cornell University where she graduated Magna cum Laude. Dr. Dashti's research focuses on the intersection of geotechnical engineering, infrastructure resilience, and environmental sustainability. Her work spans physical modeling (particularly centrifuge testing), seismic soil-structure interaction, liquefaction mechanisms in urban environments, and the impact of compound hydrologic-seismic hazards on infrastructure. She has pioneered research on the seismic response of underground structures in dense urban settings and performance-based design of liquefaction remediation techniques. Analysis of her recent publications (2021-2025) reveals a strong emphasis on liquefaction mitigation techniques, particularly using dense granular columns and ground densification. Her work increasingly incorporates machine learning approaches and examines the intersection of infrastructure resilience with social equity, as evidenced by her research on environmental vulnerability in incarceration facilities. Her publications predominantly appear in top-tier journals like the ASCE Journal of Geotechnical and GeoEnvironmental Engineering. 2025 Earthquake Engineering Research Institute (EERI) Distinguished Lecture Award 2024 Campus Sustainability Award, CU Boulder 2021 Walter L. Huber Civil Engineering Research Price, ASCE 2015 National Science Foundation Early CAREER Award 2018 Arthur Casagrande Professional Development Award, ASCE Dr. Dashti has received significant research funding including the prestigious NSF CAREER award. She serves as Co-leader and Steering Committee member of GeoEngineering Extreme Event Reconnaissance (GEER), having participated in 8 reconnaissance efforts since 2011 (leading 3). She is also an ISSMGE TC104 committee member and one of two U.S. representatives. Her professional service includes editorial roles, notably as Associate Editor of the Year for the ASCE Journal of Geotechnical Engineering and Geomechanics (2020). As a leader in the field, Dr. Dashti directs research focused on resilient infrastructure with sustainability and equity. She leads the GAANN fellowships in Integrative Reengineering of Infrastructure and is affiliated with the Center for Infrastructure, Energy, and Space Testing. Her work bridges traditional geotechnical engineering with contemporary concerns about social justice and environmental sustainability in infrastructure systems.

Zachary E. Rossمشاهده پروفایل

استاد

• Seismology
• Geophysics
• Machine Learning
• +۷ مورد دیگر

Zachary E. Ross is a Professor of Geophysics at the California Institute of Technology (Caltech) and holds the William H. Hurt Scholar distinction since 2021. His research integrates machine learning, computational mathematics, and seismology to analyze earthquakes and fault zones using large seismic datasets. Education B.S., University of California, Davis (2009) M.S., California Polytechnic State University, San Luis Obispo (2011) Ph.D., University of Southern California (2016) His research focuses on high-resolution imaging of fault zones, understanding earthquake sequences in space and time, and applying artificial intelligence to seismic data analysis. He develops scalable algorithms for waveform inversion, ground-motion synthesis, and real-time seismic monitoring. Recent publications highlight his work on neural operators for wave propagation, AI-driven seismicity analysis, and induced earthquake dynamics. He teaches advanced courses including Ge 264 – Machine Learning in Geophysics and Ge 271 – Dynamics of Seismicity . Scientific Awards William H. Hurt Scholar (2021–present)

Mohamed Farhatمشاهده پروفایل

پژوهشگر

• Cavitation & Multiphase flows
• Flow Induced Noise & Vibration
• Fluid-Structure Interaction
• +۵ مورد دیگر

Mohamed Farhat is a Senior Scientist at EPFL's School of Engineering, Department of Mechanical Engineering, where he leads the Research Group on Cavitation and Interface Phenomena. He serves as PhD Director, Lecturer, and Member of EPFL Doctoral Committee (Mechanics), while also representing EPFL at CLUSER association and coordinating activities at the Société Hydrotechnique de France (SHF). His research expertise spans Cavitation & Multiphase flows, Flow Induced Noise & Vibration, Fluid-Structure Interaction, Flow control, Flow instabilities in hydro turbines and pumps, Condition monitoring of Hydraulic Machines, Hemodynamics, and Advanced Instrumentation in Fluid Dynamics. Farhat's work uniquely bridges fundamental fluid mechanics with practical applications across hydropower, marine propulsion, healthcare, and water management sectors. Analysis of his recent publications reveals strong focus on cavitation bubble dynamics, with particular emphasis on measurement techniques for collapsing bubbles, vortex shedding control, hydrodynamic monitoring of hydraulic machinery, and biomedical applications of cavitation phenomena. His work increasingly integrates advanced imaging techniques with computational modeling to understand complex multiphase flow phenomena. 2021: Life Sciences Book Award of the International Academy of Astronautics 2019: 1st Prize Winner of Scientific Image Contest (Swiss National Science Foundation) 2020: EPFL-Rhyming Prize (Best PhD thesis in Fluid Mechanics) 2018: EPFL-EDME Prize (Best PhD thesis in Mechanics) 2015: Edmund Optics Educational Award 2014: APS-DFD Gallery of Fluid Motion Award Farhat has successfully supervised numerous PhD students including Ali Amini, Philippe Ausoni, and Outi Supponen, with research spanning from fundamental bubble dynamics to practical hydraulic machinery applications. His Cavitation Research Group maintains strong collaborations with industry partners in hydropower and medical device sectors. Current research directions include advanced instrumentation for cavitation monitoring, condition-based maintenance of hydraulic machinery, and biomedical applications of cavitation phenomena in therapeutic ultrasound and drug delivery.

Jordi McKenzieمشاهده پروفایل

دانشیار

• Industrial Organization
• Cultural Economics
• Economics of Digitisation
• +۵ مورد دیگر

Jordi McKenzie is an Associate Professor in the Department of Economics at Macquarie University. His research focuses on industrial organization, cultural economics, and digitization, with notable contributions to digital piracy, film industry economics, and generative AI in media. He holds degrees from the University of Sydney (PhD, MEc Hons) and the University of Tasmania (BEc Hons). Education: PhD in Economics, University of Sydney MEc (Hons) in Economics, University of Sydney BEc (Hons) in Economics, University of Tasmania Research interests include AI ethics in content creation, cultural trade patterns, and the economic impact of streaming services. His work has been published in journals like Poetics and Journal of Cultural Economics . He has contributed to policy discussions on digital piracy, music industry recovery post-pandemic, and author rights in AI-generated content. Recent projects include studying the transformation of data into trusted data products, digital piracy policy impacts, and subscription video on demand’s effect on legal/illegal consumption. He received the Mallen Lifetime Achievement Award in 2014 for contributions to film industry economics. McKenzie has engaged in media commentary on topics like Netflix’s viewing metrics, music collaboration impacts, and talent show biases. His research often bridges empirical evidence and policy implications, emphasizing the cultural and economic dimensions of digitization.

Glen Tianمشاهده پروفایل

استاد

• Big Data Computing
• Cloud Computing
• Computer Networks
• +۱۱ مورد دیگر

Professor Glen Tian is a Professor at the School of Computer Science , Queensland University of Technology . He holds two PhDs: one in computer and software engineering from the University of Sydney (2009) and another in industrial automation from Zhejiang University (1993) . His academic career spans institutions including Hong Kong University of Science and Technology, Curtin University, and the University of Maryland at College Park. Editor-in-Chief of the Handbook of Real-Time Computing (Springer) Associate Editor for Information Sciences (Elsevier) and Asia-Pacific Journal of Chemical Engineering (Wiley) His research focuses on big data computing , cloud computing , computer networks , smart grid communication and control , networked control systems , and cyber-physical system security . Applications include power systems , medical big data , vehicular networks , and transport systems . Recent publications highlight advancements in smart grid communications , distributed optimization , secure multi-agent systems , and medical imaging analysis . He has led QUT's Big Data Lab and served as Leader of QUT's Networks and Communications Discipline . Scientific achievements include Over 20 research grants totaling >$6M 6 Australian Research Council (ARC) grants 1 MRFF-TTRA grant ($745,623) 1 ATN-DAAD Australia-Germany Collaborative Grant 1 DEST International Science Linkage grant He supervises PhD students in big data bioinformatics , smart grid optimization , and cyber-physical security , while mentoring 30+ postdocs and research fellows. Current projects include mitigating cyberattacks on power systems and developing AI-based atheroma diagnostic tools .

Zhu-Tian Chenمشاهده پروفایل

استادیار

• Data Visualization
• Human-Computer Interaction
• Augmented Reality
• +۷ مورد دیگر

Zhu-Tian Chen is an Assistant Professor in the Department of Computer Science and Engineering at the University of Minnesota, Twin Cities, where he leads research in data visualization, human-computer interaction, and augmented reality. Prior to this, he held postdoctoral positions at Harvard University and UC San Diego, working with leading researchers in visual computing and interactive design. Ph.D. in Computer Science, Hong Kong University of Science and Technology B.Eng. in Software Engineering, South China University of Technology His research focuses on augmenting human intelligence through hybrid human-AI systems, particularly in everyday and outdoor environments. He specializes in designing intelligent AR interfaces, embedded visualizations, and language-oriented interactions for applications in sports analytics, education, and data analysis. His work integrates human-centered design with applied machine learning to create intuitive and effective visualization tools. The recent trend in his publications shows a strong emphasis on intelligent AR systems for dynamic scenes, LLM-based code generation interfaces, and real-time augmentation of sports videos using natural language and gaze-based interactions. His work frequently appears in top-tier venues such as IEEE VIS, ACM CHI, and UIST. Best Paper Award, ACM CHI'23 Best Short Paper Honorable Mention, EuroVis'23 Best Paper Honorable Mention, IEEE VIS'22 (twice) Certificate of Distinction and Excellence in Teaching, Harvard University Hong Kong Ph.D. Fellowship Dr. Chen actively mentors undergraduate, master’s, and PhD students, as well as visiting scholars and interns, and is building a new research lab focused on visualization for intelligent AR systems. He has served on program committees for major conferences including ACM CHI, IEEE VIS, and EuroVis, and has been invited to speak at institutions such as Apple, JP Morgan, and multiple universities worldwide. He also contributes to the academic community through grant reviewing for NSF and the Department of Energy. He leads research projects in intelligent AR systems for sports, language-oriented interactions with LLMs, and immersive data visualization, often in collaboration with institutions like Harvard, UC San Diego, and HKUST. His lab welcomes students and collaborators interested in visualization, HCI, and applied AI.

Maneesh Agrawalaمشاهده پروفایل

استاد

• Computer Graphics
• Human-Computer Interaction
• Visualization
• +۷ مورد دیگر

Maneesh Agrawala is the Forest Baskett Professor of Computer Science and Director of the Brown Institute for Media Innovation at Stanford University. He is also a consulting AI Scientist at Roblox. His research lies at the intersection of computer graphics, human-computer interaction (HCI), and visualization, with a focus on cognitive design principles for improving audio/visual media. He leads a vibrant research group and has advised numerous PhD students and postdocs. His research interests include: Computer Graphics Human-Computer Interaction Visualization and Visual Communication Cognitive Design Principles Generative AI and Diffusion Models Interactive Video and Sketch-based Interfaces Data and Information Visualization His recent publications (2023–2025) reflect a strong trend toward leveraging generative models—particularly diffusion models—for video and image synthesis, editing, and personalization. Key themes include controllable generation (e.g., SparseCtrl, ControlNet), sketch-to-image translation, relightable texturing, and tools that enhance visual storytelling and data communication. His work integrates cognitive science with computational tools to build systems that support human creativity and understanding. His scientific honors include: MacArthur Foundation Fellowship (2009) Alfred P. Sloan Foundation Fellowship (2007) NSF CAREER Award (2007) SIGGRAPH Significant New Researcher Award (2008) Allen Distinguished Investigator Award (2014) Induction into the SIGCHI Academy (2021) ACM Fellow (2022) Okawa Foundation Research Grant (2006) A dedicated mentor, Agrawala has advised a large cohort of students and postdocs, many of whom have gone on to influential positions in academia and industry. His lab develops tools for video editing (e.g., AnimateDiff, ControlNet), sketch-based design, and visualization (e.g., EmphasisChecker), often bridging theory with practical applications in media and education. He continues to be a leading figure in visual computing and interactive systems.

Martin Nordal Petersenمشاهده پروفایل

دانشیار

• Internet of Things
• Optical Networking
• Wireless Communication
• +۳ مورد دیگر

Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .

Arno Onkenمشاهده پروفایل

استادیار

• Data Science
• Machine Learning
• Computational Neuroscience
• +۷ مورد دیگر

Dr. Arno Onken is a Lecturer (Assistant Professor) in Data Science for Life Sciences at the School of Informatics, University of Edinburgh, where he is also affiliated with the Institute for Adaptive and Neural Computation. He leads a research group focused on developing machine learning and statistical methods for modeling neural activity and analyzing large-scale neuroscience data. His work bridges artificial intelligence and computational neuroscience. His research interests lie at the intersection of machine learning, statistics, and neuroscience. He develops flexible probabilistic models such as copulas and Gaussian processes, deep learning architectures like Vision Transformers for brain activity prediction, and matrix/tensor factorization techniques for dimensionality reduction in neural datasets. His group aims to uncover interpretable structure in complex neural recordings and understand how behavior and cognition are encoded in population activity. The recent publications reflect a strong trend in combining modern deep learning with classical statistical modeling to analyze large-scale neural recordings. His work spans from foundational methods in copula modeling and information theory to applications in predicting visual cortex responses and modeling brainstem-hippocampus interactions across sleep states. The research has been published in top venues including NeurIPS, CVPR, eLife, and PLoS Computational Biology. Dr. Onken actively supervises PhD students and has developed several open-source scientific software packages, including the Mixed Vine Toolbox and Population Spike Train Factorization Toolbox. He teaches core courses in Machine Learning and Pattern Recognition and Data Mining and Exploration at the University of Edinburgh.

André B.J. Kokkelerمشاهده پروفایل

استاد

• Cognitive Radio
• Beamforming
• MIMO Systems
• +۵ مورد دیگر

André B.J. Kokkeler is a Full Professor at the Digital Society Institute and affiliated with the Radio Systems department at the University of Twente. His research focuses on wireless communication systems, signal processing, and mmWave technology, particularly in applications like beamforming, cognitive radio, and error-resilient algorithms. Recent research outputs highlight his work on: Hybrid beamforming techniques for full-duplex integrated sensing and communication (ISAC) systems Energy-efficient iterative algorithm implementations Single-bit angle-of-arrival (AoA) localization methods mmWave channel characterization in reverberation chambers Radar-driven human gait modeling His work contributes to advancements in wireless systems for IoT, automotive radar, and energy-constrained environments. Collaborations span multiple institutions and focus on propagation modeling, antenna characterization, and sensing applications.

• Plasma Physics
• Fluid Dynamics
• Turbulence
• +۴ مورد دیگر

Dr Mahdi Davoodianidalik is a researcher in the Department of Nuclear Physics & Accelerator Applications at the Australian National University (ANU). He is affiliated with the Space plasma power and propulsion group and the Physics of fluids group, focusing on interdisciplinary research at the intersection of plasma physics, fluid dynamics, and space propulsion technologies. His research interests include Turbulence and wave-driven flows Plasma thrusters and electrothermal propulsion Fluctuation-induced forces and interactions Fluid-structure dynamics Thermal engineering of micro-thrusters Nonlinear phenomena in fluids Recent publications highlight his work on analogs of the Casimir effect in turbulent flows, passive propulsion mechanisms, and advanced propulsion systems using solid hydrocarbon propellants. He has contributed to understanding turbulence in both fundamental and applied contexts, with a focus on energy transfer and chaotic flow phenomena. His collaborations span ANU colleagues including Nicolas Francois and Michael Shats, with a strong emphasis on experimental and computational fluid dynamics.

Christine Tardifمشاهده پروفایل

استادیار

• MRI-based Neuroimaging
• Quantitative MRI (qMRI)
• Biophysical Modeling
• +۸ مورد دیگر

Christine Tardif is an Assistant Professor in the Department of Biomedical Engineering and the Department of Neurology and Neurosurgery at McGill University. As head of the McConnell Brain Imaging Centre lab at the Montreal Neurological Institute, she develops advanced MRI techniques for in-vivo brain imaging, focusing on quantitative mapping of myelin and cortical microstructure. Her work spans methodological innovation (e.g., multi-modal biophysical modeling) and translational applications across preclinical (7 Tesla) and clinical (3 and 7 Tesla) systems. Undergraduate: B.Eng. in Computer Engineering, McGill University (2004) Master's: M.Sc. in Bioengineering, Imperial College London (2006) PhD: Biomedical Engineering, McGill University (2011) Her research explores myelin dynamics in health and disease, emphasizing its role in neural conduction, brain plasticity, and cognitive functions. The lab investigates dysmyelination in psychiatric disorders (e.g., bipolar disorder) and neurodegenerative conditions (e.g., multiple sclerosis) using relaxometry , magnetization transfer , and diffusion-weighted imaging . Recent methodological work includes 3D MERMAID sequences for motion-insensitive diffusion imaging and optimization of magnetization transfer saturation maps. Current projects integrate ultra-high field MRI with histological validation in preclinical models (e.g., marmoset brain sections), aiming to bridge microstructural metrics with macro-scale brain function. Applications span Alzheimer's disease risk assessment via white matter alterations, synaptic density mapping in psychosis, and cortical laminar differentiation studies.