جست‌وجوی استاد و پژوهشگر

William Oatesمشاهده پروفایل

استاد

• Solid mechanics of active materials
• Smart material device design
• Nonlinear control
• +۶ مورد دیگر

William S. Oates is the Cummins, Inc. Professor of Engineering in the Department of Mechanical Engineering at Florida A&M / Florida State University. He holds affiliations with the Mechatronics and Energy Center and the Florida Energy Systems Consortium (FESC). His research focuses on solid mechanics of multifunctional materials, quantum-informed continuum modeling, and applications in robotics, aerospace, and energy systems. He has advised over 20 graduate students and holds awards including ASME Fellow (2018) and NSF CAREER Award (2011). Education: Ph.D. from Georgia Institute of Technology. Research spans smart materials, fractal media mechanics, and quantum computing for material modeling. Key projects include high-temperature sapphire pressure sensors, photomechanical polymers, and Bayesian uncertainty quantification in materials science. Notable awards include DARPA Young Faculty Award (2009) and FSU Guardian of the Flame Teaching Award (2010). His lab collaborates with the National High Magnetic Field Lab and Challenger Learning Center for K-12 outreach. Current research includes quantum algorithm implementation for engineering applications and fractal-based viscoelastic models.

• Hardware Security
• Machine Learning
• 3D IC Design
• +۴ مورد دیگر

Wafi Danesh is an Assistant Professor in the Department of Engineering Programs at SUNY New Paltz, part of the School of Science & Engineering. He holds a PhD in Electrical and Computer Engineering from the University of Missouri Kansas City (2022). Prior to academia, he served as a Senior Engineer I - Design at Microchip Technology Inc. (2022-2023). His research focuses on hardware security, leveraging machine learning for FPGA Trojan detection and secure 3D IC design. Teaching interests include System-on-Chip Design, Digital Logic Fundamentals, and Computer Architecture. Education: PhD in Electrical and Computer Engineering, University of Missouri Kansas City, 2022 Research Interests: Dr. Danesh explores cutting-edge methods to enhance hardware security, including AI-driven approaches for IoT device protection and thermal management in 3D integrated circuits. His work bridges machine learning and physical hardware vulnerabilities, emphasizing FPGA security and PUF-based solutions for wireless systems. Publications Trends: His articles span FPGA Trojan detection via NLP and unsupervised learning, thermal challenges in 3D ICs, and neuromorphic computing innovations. Recent work highlights automated security tools and multi-valued computing for energy efficiency. Awards: None explicitly listed in the provided materials. Advising & Grants: No formal advisees or grants are mentioned. His professional activities center on research and teaching.

Roland N. Horneمشاهده پروفایل

استاد

• Geothermal reservoir engineering
• Energy production optimization
• Well test interpretation
• +۸ مورد دیگر

Roland N. Horne is the Thomas Davies Barrow Professor of Earth Sciences at Stanford University and Senior Fellow at the Precourt Institute for Energy. He holds positions in the Department of Energy Science & Engineering and is an Affiliate at the Stanford Woods Institute for the Environment. With degrees from the University of Auckland (BE, PhD, DSc), Horne has established himself as a leading expert in geothermal reservoir engineering and energy production optimization. His research focuses on inverse problems in reservoir modeling, including tracer analysis of fractures, computer-aided well test analysis, production schedule optimization, and automated history matching. Horne has made significant contributions to understanding geothermal reservoir engineering and multiphase flow of boiling fluids through porous materials and fractures. The analysis of his recent publications (2023-2025) reveals a strong emphasis on enhanced geothermal systems (EGS), with particular focus on flexible operations, economic modeling, and advanced characterization techniques. His work increasingly incorporates machine learning approaches for reservoir analysis and has expanded into microbial tracing methods for interwell connectivity assessment. There's also significant attention to US geothermal resource potential and integration into the broader energy transition. Honorary Member of the Society of Petroleum Engineers Member of the US National Academy of Engineering Multiple SPE Distinguished Lecturer appointments (1998, 2009, 2020) John Franklin Carl Award recipient Five Best Paper awards from Geothermal Resources Council Patricius Medal from German Geothermal Society Core Values Award from Women in Geothermal (2023) Horne has supervised 60 PhD and 135 MS students throughout his career. His current teaching includes undergraduate and graduate courses in Fundamentals of Energy Processes, Geothermal Reservoir Engineering, Mass and Energy Transport in Porous Media, and Well Test Analysis. He previously served as President of the International Geothermal Association (2010-2013) and Technical Program Chair for multiple World Geothermal Congress events. Horne maintains active research collaborations worldwide, including with the University of Tokyo (where he was a Fellow of the School of Engineering in 2016) and China University of Petroleum. His current research group focuses on advancing EGS technologies and developing more accurate reservoir characterization methods for geothermal applications.

Jingxian Wangمشاهده پروفایل

استادیار

• Artificial Intelligence
• Wireless Systems
• Satellite Networks
• +۹ مورد دیگر

Jingxian Wang is an NUS Presidential Young Professor and Assistant Professor in the Department of Computer Science at the National University of Singapore's Faculty of Computing. His research builds next-generation wireless systems and satellite networks, with primary focus on integrating AI with wirelessly networked devices from WiFi to satellites. He earned his PhD from Carnegie Mellon University and previously served as a research scientist at Microsoft Research in Redmond, where he led the Smart Surface for 6G and Space initiative. His educational journey includes: PhD, Carnegie Mellon University Wang's research spans Wireless Systems , Satellite Networks , Artificial Intelligence , and Internet of Things , emphasizing AI-augmented wireless systems. His interdisciplinary work bridges robotics , materials science , and AI to develop sustainable sensing methods, robust communication networks, and multimodal AI techniques. Key projects include Multimodal AI for IoT (funded by Microsoft's Accelerate Foundation Models Program) and Satellite IoT Networks. His publication trends reveal accelerating integration of AI into wireless systems, with recent focus on satellite networking, soft robotics actuation, and generative models for IoT. The research consistently targets real-world deployment challenges in battery-free systems and space networks. His scientific contributions have earned prestigious recognition: ACM SIGMOBILE Doctoral Dissertation Award 2023 Communications of the ACM Research Highlights (2021, 2022) ACM SIGMOBILE Research Highlights 2021 Best Paper Awards at IPSN 2021 and UbiComp 2020 Microsoft Research Fellowship 2020 Emerging Rockstar in IEEE Pervasive Computing 2024 Wang actively mentors doctoral students and postdoctoral researchers through his AIoT Group. His grant portfolio includes Microsoft's Accelerate Foundation Models Research Program funding for multimodal AI projects, with ongoing work targeting satellite IoT infrastructure and wireless-powered soft robotics. Future directions emphasize foundation models for space networks and battery-free IoT systems. He leads the AIoT Group, fostering cross-disciplinary collaboration between computer scientists, roboticists, and materials engineers to pioneer wireless sensing and actuation technologies.

• Ports and Maritime Logistics
• Transport Network Modelling
• Intelligent Transport Systems
• +۶ مورد دیگر

Professor Michael Bell is the Foundation Professor of Ports and Maritime Logistics at the University of Sydney Business School's Institute of Transport and Logistics Studies. He holds a BA from Cambridge University, MSc and PhD from Leeds University, and has held roles including Director of Imperial College London's PORTeC and academic positions at Newcastle University and Karlsruhe Technical University. His research focuses on ports, transport networks, sustainability, and intelligent transport systems. He has authored over 150 publications, including seminal works like Transportation Network Analysis . Current projects include circular economy diversification for ports and autonomous delivery systems. Awards include fellowship in multiple transport societies. Education: BA (Economics) Cambridge (1975), MSc (Transportation) Leeds (1976), PhD (Freight Distribution) Leeds (1981). Postdoctoral research at Karlsruhe Technical University (1982–1984). Research Interests: Ports logistics, transport network resilience, urban logistics, cybersecurity in supply chains, and sustainable transport policy. Publications span 40+ years, emphasizing empirical and theoretical advancements in maritime systems, network modelling, and policy analysis. Recent work explores autonomous systems integration and port diversification strategies. Grants include a 2023 iMOVE CRC project on land use trip surveys and a 2022 ARC Discovery Project on automated transport decisions. Media appearances address global trade disruptions (e.g., Suez Canal blockage), autonomous vehicles, and port sustainability. Led PORTeC (Imperial College) and co-founded the Institute of Transport and Logistics Studies at Sydney. Active in policy advisory roles for government agencies and industry bodies.

Ebenezer Fanijoمشاهده پروفایل

استادیار

• Sustainable Construction
• Civil Engineering
• Materials Science
• +۳ مورد دیگر

Ebenezer Fanijo is an Assistant Professor at the School of Building Construction, part of the College of Design at Georgia Institute of Technology. He joined in Spring 2023 and specializes in sustainable and smart-resilient infrastructure, focusing on low-carbon construction materials and alternative energy sources. His work addresses carbon emissions in building materials and processes through advanced research on cementitious composites, recycled materials, and green technologies. Dr. Fanijo holds a B.S. in Building Construction (Obafemi Awolowo University, Nigeria), M.S. in Civil Engineering (University of Idaho, 2019), and a Ph.D. in Civil Engineering with a concurrent MEng in Materials Science and Engineering from Virginia Tech (2022). He is also a Professional Engineer (P.E.) and LEED Green Associate with over five years of construction sector experience. Education: B.S. Building Construction, Obafemi Awolowo University, Nigeria (First Class Honours) M.S. Civil Engineering, University of Idaho (2019) Ph.D. Civil Engineering & MEng Materials Science, Virginia Tech (2022) Research Interests: His research spans sustainable construction materials, concrete durability, green technologies using recycled/by-product materials, 3D-printed cementitious materials, and advanced sensing for structural monitoring. He emphasizes decarbonizing infrastructure and developing innovative composites to reduce lifecycle emissions. Awards: NSBE Golden Torch Award (2022) – Recognized as Graduate Student of the Year National/international awards for research excellence Teaching & Advising: Dr. Fanijo teaches courses on construction materials, green technologies, and sustainable practices. He developed core curricula such as Construction Materials and Methods and Green Construction Technology . His advising focuses on student mastery of material properties and their integration into environmental performance frameworks. Professional Contributions: He has led funded research projects, published widely in peer-reviewed journals, and pioneered work on alkali-silica reactivity mitigation, asphalt mix design optimization, and corrosion monitoring. His lab integrates AI and nanoscale techniques for material analysis.

Florian Knollمشاهده پروفایل

استاد

• Medical Imaging
• Machine Learning
• Magnetic Resonance Imaging (MRI)
• +۳ مورد دیگر

Prof. Dr. Florian Knoll is a full professor in Computational Imaging at the Department of Artificial Intelligence in Biomedical Engineering (AIBE) at Friedrich-Alexander-Universität Erlangen-Nürnberg. He leads the Computational Imaging Lab, focusing on machine learning applications in medical imaging, particularly accelerating MRI through innovative reconstruction algorithms and translating them into clinical practice. His research emphasizes improving MRI speed, artifact robustness, and accessibility, alongside developing quantitative biomarkers for disease processes. Knoll's work is funded by NIH grants, including projects on machine learning for musculoskeletal imaging, MR fingerprinting, and deep learning frameworks for MRI reconstruction. He is a key figure in open science initiatives, co-creating the fastMRI dataset with Facebook AI, providing public access to over 1300 knee and 7000 brain MRI scans. He currently serves as deputy editor of Magnetic Resonance in Medicine and chairs the ISMRM Reproducible Research Study Group. His contributions extend to reproducible research, maintaining GitHub repositories with code for image reconstruction techniques (e.g., AGILE, gpuNUFFT) and educational materials. He teaches medical imaging fundamentals at FAU, integrating theoretical and practical insights for students and researchers. Grants: NIH R01EB024532, R21EB027241, P41EB017183, R01EB029957 Labs/Teams: Computational Imaging Lab, fastMRI initiative Software: GitHub repositories for MRI reconstruction (e.g., github.com/FlorianKnoll )

• Composite Materials
• Structural Engineering
• Machine Learning Applications
• +۳ مورد دیگر

Dr. Thuc Vo is an Associate Professor in Civil Engineering at La Trobe University, Australia. His expertise lies in structural engineering, composite materials, and machine learning applications. He previously held roles at Northumbria University (UK) and Airbus’ Advanced Composite Training and Development Centre. His research focuses on shear deformation theories for composite structures and machine learning for structural engineering. He has authored over 120 publications in prestigious journals and conferences. Education & Experience: Associate Professor, La Trobe University (2019–present) Senior Lecturer & Program Leader in Civil Engineering, Northumbria University (2013–2019) Lecturer at Airbus’ Advanced Composite Training and Development Centre/Wrexham Glyndwr University (2011–2013) Research Associate, University of Liverpool (2010–2011) Research Interests: Composite material analysis (FGMs, nanoporous materials) Machine learning for structural prediction Vibration and buckling analysis Advanced beam and plate theories Collaboration & Supervision: Offers supervision for masters/PhD students and collaborates on industry projects. His work bridges theoretical mechanics with data-driven approaches, addressing challenges in smart materials and structural optimization.

Elliot Huiمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Microfluidics
• Spatial Cell Biology
• +۳ مورد دیگر

Elliot Hui, Ph.D., is an Associate Professor in the Department of Biomedical Engineering at the University of California, Irvine (UCI), within the Samueli School of Engineering. His research focuses on biological microtechnology, including spatial cell biology, microscale tissue engineering, global health diagnostics, and microfluidic computing. He leads the Hui Lab, which develops tools for automating biochemical reactions, controlling cellular organization, and understanding tissue development dynamics. Key achievements include pioneering microfluidic logic systems for autonomous laboratory automation and creating novel cell culture platforms to study intercellular communication in tissues. His work bridges engineering and biology, addressing challenges in diagnostics and regenerative medicine. Notable contributions include the development of a programmable finite state machine for microfluidic control and a SLAS Fellowship awarded to his student Erik. Research Interests: Microfluidic devices, cell-cell interaction modeling, tissue engineering, and lab-on-a-chip systems. Labs/Teams: Hui Lab at UCI, specializing in microscale biological systems and automation. Publications span topics such as microfluidic computing architectures, tissue dissociation devices, and Bayesian experimental design. His work emphasizes applications in global health diagnostics and mechanistic studies of cellular processes.

Emily Whitingمشاهده پروفایل

دانشیار

• Computer Graphics
• Computational Fabrication
• Architectural Geometry
• +۴ مورد دیگر

Emily Whiting is an Associate Professor of Computer Science at Boston University and Director of the Shape Design & Computation Lab. She also serves as Director of PhD Admissions and Co-Director of the BU Computer Graphics Lab. Her research focuses on computational fabrication, architectural geometry, and computer-aided design, bridging digital geometry processing, engineering mechanics, and rapid prototyping. She holds a PhD from MIT (2012), an SM in Design & Computation from MIT (2006), and a BASc in Engineering Science from the University of Toronto (2004). Previously, she was faculty at Dartmouth and a Marie Curie Postdoctoral Fellow at ETH Zurich. Her research interests include 3D printing optimization, structural design for fabrication, and tools for functionally-valid object creation. Notable projects include work on elastic garments, climbing experience replication, and print-wind instrument design. Her work has been featured on TEDx and PBS NOVA, and she has received awards such as the NSF CAREER Award and Sloan Research Fellowship. Education: PhD (MIT), SM (MIT), BASc (University of Toronto) Labs: Shape Design & Computation Lab, BU Computer Graphics Lab Key Projects: Knitting 4D garments, Environment-Scale Fabrication, Thermal-comfort casts Recent professional activities include program committee roles at SIGGRAPH 2025 and UIST 2024, and serving as Program Co-Chair for Pacific Graphics 2024. She advises a team of PhD and MS students, with alumni now in academia and tech industries.

Caroline Roneyمشاهده پروفایل

مدرس

• Computational Medicine
• Cardiac Arrhythmia
• Biomedical Engineering
• +۴ مورد دیگر

Dr Caroline Roney is a UKRI Future Leaders Fellow and Lecturer in Computational Medicine at Queen Mary University of London's School of Engineering and Materials Science. Her research focuses on developing engineering methodologies to personalize treatment for cardiac arrhythmias, combining signal processing, machine learning, and computational modeling to predict optimal patient-specific therapies. She holds a MMath from the University of Oxford, MRes and PhD from Imperial College London, and has held fellowships at Liryc Institute and King's College London. Her work integrates clinical imaging and electrophysiological data to advance atrial fibrillation treatment strategies. Education: MMath in Mathematics, University of Oxford MRes in Biomedical Research, Imperial College London PhD in Cardiac Signal Processing, Imperial College London Research Interests: Development of patient-specific digital twins for atrial fibrillation, computational modeling of fibrosis, and integration of machine learning with clinical data. Awards: UKRI Future Leaders Fellowship, Fondation Lefoulon Delalande Fellowship (2015–2017), MRC Research Fellowship (2017–2021). Affiliations: Digital Environment Research Institute (DERI), Visiting Lecturer at King's College London. Her research group has secured £9.3M in grants, including EPSRC and MRC funding, to advance virtual atrial modeling and AI-driven healthcare tools. Key collaborations include industry partners like Acutus Medical and RHYTHM AI, focusing on clinical translation of computational models.

Surl-Hee Ahnمشاهده پروفایل

استادیار

• Molecular Dynamics Simulations
• Enhanced Sampling Methods
• Drug Discovery
• +۷ مورد دیگر

Surl-Hee Ahn is an Assistant Professor in the Department of Chemical Engineering at the University of California, Davis. Her research focuses on using molecular dynamics (MD) simulations and enhanced sampling methods like the weighted ensemble (WE) to study biological systems, including proteins, nanocrystals, and drug discovery for tuberculosis and other diseases. She leads the Ahn Lab, which develops cutting-edge computational tools, such as ParGaMD and DeepWEST, to advance kinetic and thermodynamic sampling in simulations. Education: Ph.D. in Chemistry (Chemical Physics), Stanford University M.S. in Chemistry, University of Pennsylvania M.A. in Mathematics, University of Pennsylvania B.A. in Biochemistry and Mathematics, University of Pennsylvania (Magna Cum Laude, Vagelos Scholar) Research Interests: Molecular dynamics simulations, enhanced sampling methods, computational drug discovery, vaccine design, protein interactions, and nanomaterial dynamics. Her work bridges computational biology, materials science, and pharmacology, with applications to infectious diseases and neurodegenerative disorders. Awards and Recognition: 2020 ACM Gordon Bell Prize Winner (SC20) for SARS-CoV-2 spike dynamics simulations 2021 Chancellor’s Outstanding Postdoctoral Scholar Award Finalist MIT Rising Stars in Mechanical Engineering (2018) ACS PHYS Division Young Investigator Award (2021) Grants & Collaborations: Her research is supported by grants from SC20/SC21 and leverages high-performance computing for multiscale modeling. She collaborates on projects like #COVIDisAirborne, combining AI with computational microscopy. Labs & Teams: The Ahn Lab at UC Davis emphasizes interdisciplinary training in computational methods and their application to real-world biomedical challenges.

Michael Danieleمشاهده پروفایل

دانشیار

• Bioelectronics Engineering
• Wearable Biosensors
• Microphysiological Systems
• +۳ مورد دیگر

Michael Daniele is an Associate Professor at North Carolina State University, jointly appointed in the Department of Electrical & Computer Engineering and the Joint Department of Biomedical Engineering . His research focuses on bioelectronics engineering, particularly in developing microsystems for monitoring, mimicking, and augmenting biological functions. He leads the @BiointerfaceLab , exploring wearable/implantable biosensors, microphysiological systems, and process analytical technologies for biomanufacturing. Education : Ph.D. in Materials Science & Engineering (Clemson University, 2012) Bachelor's in Materials Science & Engineering (Rutgers University, 2009) Research Highlights : Developing "injury-on-a-chip" models for coagulation studies Pioneering hydrogel microneedles for diagnostic devices Advancing light-controlled peptide ligands for protein purification Collaborating with Novartis on viral vector manufacturing Award Recognition : 2024 William F. Lane Outstanding Teaching Award 2019 NSF CAREER Award 2022 University Faculty Scholar Grants & Initiatives : Co-leader of the NC-Viral Vector Initiative (2023–present) NSF-funded projects in biosensor integration and biomanufacturing His work bridges engineering and medicine, with applications in gene therapy, wearable diagnostics, and precision agriculture.

Mohammad Naraghiمشاهده پروفایل

استاد

• Nanomaterials Engineering
• Materials Science
• Polymer Engineering
• +۶ مورد دیگر

Dr. Mohammad Naraghi is a Professor and Associate Department Head for Academics in the Department of Aerospace Engineering at Texas A&M University. He leads the Nanostuctured Materials Lab , focusing on advanced nanomaterials for aerospace applications. His work integrates material science principles to develop lightweight, high-performance materials for structural, energy storage, and smart textile systems. Education: Ph.D., Aerospace Engineering (2009), University of Illinois at Urbana-Champaign M.S., Civil Engineering (2004), Sharif University of Technology B.S., Civil Engineering (2004), Sharif University of Technology Research Interests: Graphitic carbon nanomaterials, bio-inspired composites, experimental nanomechanics, and polymer nanofiber processing. His lab explores multifunctional materials for aerospace applications, including self-healing polymers, structural batteries, and sustainable carbon fiber recycling. Publications: Dr. Naraghi has authored over 150 peer-reviewed articles, with recent work focusing on carbon nanomaterial synthesis, self-healing vitrimers, and all-electric aircraft sustainability . His studies bridge nanoscale mechanics and macroscale applications, emphasizing scalability and industrial relevance. Awards: Best Paper Award (2009) for nano viscoelastic composites research Roger A. Strehlow Memorial Award (2009) for outstanding research First Place in Sandia MEMS Design Competition (2007) Advising & Grants: Leads NSF-funded projects on sustainable materials and structural energy storage. Advises graduate students in aerospace and materials engineering. Collaborates with Sandia National Labs and industry partners on advanced composite development. Labs & Facilities: Directs the Nanostuctured Materials Lab, equipped with advanced nanomechanical testing systems, electrospinning setups, and characterization tools for nanoscale materials analysis.

Chen Wei Wayneمشاهده پروفایل

استادیار

• Generative Design AI
• Machine Learning
• Uncertainty Quantification
• +۳ مورد دیگر

Chen Wei Wayne is an Assistant Professor in the Department of Mechanical Engineering at Texas A&M University. His research focuses on generative design AI, machine learning, uncertainty quantification, and advanced manufacturing. He leads the DIGIT Lab, which develops AI methods for design innovation, automation, and manufacturing integration. Education: Ph.D., Mechanical Engineering, University of Maryland, College Park (2019) M.S., Mechanical Engineering, Chongqing University, China (2015) B.S., Mechanical Engineering, Chongqing University, China (2012) Research Interests: Generative adversarial networks (GANs) for design synthesis Data-driven metamaterials and multiscale systems Uncertainty quantification in engineering design AI-driven design automation Awards & Honors: ASME Journal of Mechanical Design Reviewer of the Year Award (2023) ASME DAC Best Paper Award (2022) Journal of Mechanical Design Editors’ Choice Honorable Mention (2021) Lab Activities: Recent lab milestones include successful completion of TAMUQ Summer Research Programs (2024) Hosts undergraduate researchers like Wisam Gadam and Eddie Guerrero