جست‌وجوی استاد و پژوهشگر

• Geotechnical Engineering
• Seismic Analysis
• Soil Mechanics
• +۳ مورد دیگر

Youssef M A Hashash is the W. W. Grainger Chair and Professor in the Department of Civil and Environmental Engineering at the University of Illinois. His research focuses on geotechnical and earthquake engineering, with emphasis on seismic site response analysis, soil-structure interaction, and advanced computational methods like the Discrete Element Method (DEM). He has led projects on infrastructure resilience, including studies of buried water reservoirs, railway systems, and post-earthquake reconnaissance. Hashash has developed influential models for site amplification in Central and Eastern North America, contributing to seismic hazard assessments. His work integrates experimental centrifuge testing, numerical simulations, and field data. Notable contributions include guidelines for implementing NGA-East ground motion models and advancements in pore-water pressure generation models for liquefaction evaluation. Key Research Areas: Ground movement, seismic response, soil dynamics, and geotechnical data systems Major Projects: NGA-East Geotechnical Working Group, Beirut Explosion Analysis, and LA Metro Tunnel Projects Recipient of prestigious awards including the NAE Membership (2022), PECASE (2000), and Walter L. Huber Prize (2006), he collaborates internationally on earthquake engineering and geotechnical innovations. His lab develops tools like the DEEPSOIL software for nonlinear site response analysis and explores AI applications in geotechnical data interpretation.

Garg Vikasمشاهده پروفایل

استادیار

• Quantum Computing
• Artificial Intelligence
• Machine Learning
• +۸ مورد دیگر

Professor Garg Vikas holds the position of Assistant Professor in the Department of Computer Science at the School of Science. His research spans quantum computing, artificial intelligence, and machine learning with applications in computational biology, healthcare, and drug design. He leads the HEALED/Garg project focused on human-steered machine learning for drug discovery and collaborates with institutions like MIT and industry partners. He co-founded YaiYai Oy, providing AI/ML solutions to global sectors. Education: PhD from MIT CSAIL under Tommi Jaakkola, with postdoctoral and industry experience at Amazon, Microsoft, and IBM. His work aligns with UN SDGs, particularly in healthcare and sustainable energy. Research interests include graph neural networks, generative models, and quantum AI. Recent projects involve climate modeling via physics-informed neural ODEs and optimizing quantum circuits using graph autoencoders. Key collaborations include MIT’s MLPDS Consortium and the Finnish Center for Artificial Intelligence. He supervises doctoral researchers like Yogesh Verma and postdocs such as Kogkalidis.

Christoph Leitnerمشاهده پروفایل

پژوهشگر ارشد

• Convergent Technologies
• Ultrasonics
• Machine Learning
• +۳ مورد دیگر

Dr. Christoph Leitner is a Research Fellow at ETH Zurich's Integrated Systems Laboratory under Prof. Luca Benini, focusing on biomedical and IoT applications. His work integrates printed piezoelectric transducers and flexible electronics with energy-efficient systems. He holds a PhD in Biomedical Engineering from TU Graz (2022) and has collaborated with institutions like Sant'Anna School of Advanced Studies and KTH Stockholm. Notable achievements include the Josef Krainer Young Researcher Award and Motorik Scholarship. Leitner's research spans ultrasonics, machine learning, and wearable devices, with contributions to muscle-tendon dynamics and real-time biofeedback systems. Education: PhD in Biomedical Engineering, TU Graz (2022), Advisor: Prof. Christian Baumgartner Previous roles: University Assistant (2006–2011) and R&D Engineer at Virtual Vehicle GmbH Research Interests: Convergent technologies merging biomedical engineering and IoT Ultrasound-based monitoring for musculoskeletal systems Energy-efficient embedded systems for wearable applications Collaborations & Awards: Recipient of Josef Krainer Young Researcher Award (2023) and Motorik Scholarship (2018) Active collaborations with University of Zurich, Veterinary University of Vienna, and Queensland University of Technology Labs & Projects: Integrated Systems Laboratory at ETH Zurich Developed a patented ultrasound-transparent tattoo-based SEMG system with Prof. Francesco Greco

Michael Thompsonمشاهده پروفایل

استاد

• Semiconductor Physics
• Materials Science
• Laser Processing
• +۷ مورد دیگر

Professor Michael Thompson is a tenured faculty member in the Department of Materials Science and Engineering at Cornell University's College of Engineering. He holds the Dwight C. Baum Professorship in Engineering and specializes in advanced materials processing, particularly semiconductor materials under pulsed laser exposure. His research focuses on transient thermal processing (nanosecond to sub-second timescales) for material property modification and characterization, with applications in semiconductors, EUV lithography, and photonic materials. Thompson has authored over 120 papers and 20 patents, emphasizing industrial challenges like front-end junction formation and flexible electronics. Education: B.S. in Physics (CalTech, 1979), M.S./Ph.D. in Physics (Cornell, 1982/1984). He has received prestigious awards including the North American Award for Technical Contribution to the Semiconductor Industry (2009), multiple Cornell Excellence in Teaching Awards, and the Stephen H. Weiss Presidential Fellow designation (2021). His teaching focuses on thermodynamics and electronic properties, with a commitment to making abstract concepts accessible through real-world examples. Service: Leads curriculum development, ABET accreditation, and industry outreach. His lab develops novel methods for autonomous materials discovery using AI-driven approaches. Current projects include laser spike annealing for semiconductor doping and high-throughput synthesis of metastable materials.

Angelo Cervoneمشاهده پروفایل

استاد

• Astrodynamics
• Space Propulsion Systems
• CubeSat Technology
• +۳ مورد دیگر

Angelo Cervone is a Professor at Delft University of Technology's Department of Astrodynamics & Space Missions within the Faculty of Aerospace Engineering. His research focuses on advanced propulsion systems, CubeSat technology, additive manufacturing for space applications, and space systems design. He leads projects like LUMIO, a CubeSat mission to monitor lunar meteoroid impacts, and has contributed to the development of green propellants and smart composite structures with embedded sensors. His work integrates cutting-edge manufacturing techniques like laser powder directed energy deposition with propulsion system optimization, emphasizing sustainable and robust space technologies. Cervone has authored over 130 publications and edited the book Adaptive On- and Off-Earth Environments , reflecting his expertise in off-world infrastructure and robotic production systems. He received the Rhizome Award (2021) for advancing autarkic systems in off-Earth habitat development. Key Projects: LUMIO CubeSat mission, Rhizome habitat system development, smart propellant tank design Research Themes: CubeSat propulsion, lunar exploration, additive manufacturing for space, in-situ resource utilization His articles highlight advancements in micro-thrusters, structural health monitoring via fiber optics, and autonomous navigation systems for deep-space CubeSats. Cervone collaborates globally on missions requiring innovative propulsion architectures and materials science breakthroughs.

Michael Scottمشاهده پروفایل

استاد

• Structural Engineering
• Nonlinear Structural Analysis
• Finite Element Analysis
• +۶ مورد دیگر

Michael Scott is a Professor in the Department of Civil and Construction Engineering at Oregon State University, part of the College of Engineering. He holds a Ph.D. in Structural Engineering from the University of California, Berkeley (2004), an M.S. from the same institution (1999), and a B.S. in Civil Engineering from North Carolina State University (1998). His research focuses on nonlinear structural analysis, dynamics, numerical methods, and software design, particularly in the context of bridges and fluid-structure interactions. He has developed widely used tools like OpenSees and contributed to multi-hazard resilience frameworks for infrastructure. Key research areas include tsunami impacts on coastal bridges, GPU-accelerated analysis, and machine learning applications for structural simulation. His work emphasizes sensitivity analysis and software reliability, with notable contributions to OpenSees and PFEM methodologies. He has been recognized with the 2019 Celebrate Excellence Awards for Online Teaching. His research also addresses bridge loading from truck platooning, seismic sensitivity, and ponding effects on structural steel roofs. Educations: Ph.D., Structural Engineering, UC Berkeley (2004) M.S., Structural Engineering, UC Berkeley (1999) B.S., Civil Engineering, NC State University (1998) Awards: 2019 Celebrate Excellence Awards, Online Teaching Award Key Contributions: Development of OpenSees software framework Pioneering work in PFEM for fluid-structure interaction Multi-hazard engineering for tsunami resilience

• Process Metallurgy
• Advanced Materials Processing
• Steelmaking Technology
• +۷ مورد دیگر

Bryan Webler is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University (CMU) since 2013, with a courtesy appointment in the Department of Mechanical Engineering. He serves as Co-Director of the Center for Iron and Steelmaking Research (CISR), an industry-supported consortium, and is affiliated with the NextManufacturing Center and Mill 19 digital backbone initiative. His expertise spans process metallurgy, additive manufacturing, and steelmaking technologies. Education: B.S. in Engineering Physics (2005) from the University of Pittsburgh; M.S. (2007) and Ph.D. (2008) in Materials Science and Engineering from CMU. Prior to academia, he worked as a Senior Engineer at the Bettis Atomic Laboratory's Materials Technology department. Research focuses on four core areas: chemical reactions during liquid steel refining, non-metallic inclusion control, continuous casting of steel, and additive manufacturing (laser powder bed fusion, directed energy deposition). His group integrates high-temperature experiments, computational thermodynamics, and kinetic modeling. Notable contributions include developing oxide dispersion strengthening methods and advancing digital twin applications in manufacturing. Key awards include the Kent D. Peaslee Junior Faculty Award (AIST Foundation) and the AIST Foundation Steel Professor title. He serves on editorial boards for Metallurgical and Materials Transactions B and Metallurgical Research and Technology , and actively contributes to industry partnerships. Beyond technical work, Webler explores the history of metallurgy, particularly Pittsburgh's steel industry legacy. His lab's innovations address carbon management, energy production, and advanced materials processing for extreme environments.

• Machine Learning
• Data Mining
• GIS Modeling
• +۴ مورد دیگر

Usman Ali is an Assistant Professor and Adjunct Lecturer at the School of Mechanical and Materials Engineering, University College Dublin. He holds a Ph.D. in 'A data-driven GIS-based approach for multi-scale residential building energy modeling' (2020) from UCD and an M.Sc. in Computer Science from Lahore University of Management Science (2013). His research focuses on machine learning, GIS modeling, urban building energy systems, and energy performance certification. He has contributed to projects like the U.S.-Ireland R&D initiative on building stock classification and energy prediction, and collaborated with the Sustainable Energy Authority of Ireland (SEAI) on energy policy research. His work emphasizes data-driven solutions for energy efficiency, urban sustainability, and policy decision-making. Education: Ph.D., University College Dublin (2020) M.Sc., Lahore University of Management Science (2013) B.Sc., International Islamic University Islamabad (2008) Research emphasizes machine learning applications in energy modeling, GIS integration for urban planning, and energy policy frameworks. His recent work includes synthetic building datasets, occupancy-based energy analysis, and uncertainty quantification in energy systems.

Haifa AlSalmiمشاهده پروفایل

پژوهشگر ارشد

• AI for Sustainability
• Computational Geophysics
• Environmental Science
• +۶ مورد دیگر

Haifa AlSalmi is a Research Fellow at the Digital Environment Research Institute (DERI), Queen Mary University of London, specializing in AI-driven environmental and sustainability research. She holds a PhD in Geophysics from Imperial College London, where her thesis focused on computational methods for seismic data analysis and subsurface characterization. Her current role involves leveraging computer vision, deep learning, and computational geophysics to enhance subsurface seismic image processing, with applications in sustainable energy exploration (geothermal, hydrothermal, and hydrogen technologies) and climate change research. Her work addresses critical challenges in decarbonization and environmental sustainability, including improving resolution of subsurface data for energy resource exploration and deepening understanding of historical climate patterns and sea-level variations. She collaborates within Professor John’s research group at DERI, which integrates digital technologies to tackle environmental issues. No specific grants or advising roles are detailed in the provided materials, though her contributions emphasize interdisciplinary innovation in geophysics and AI applications. Labs/Teams: Part of the DERI and Professor John’s research group at Queen Mary University of London.

Kate Fuمشاهده پروفایل

دانشیار

• Design Innovation
• Creativity
• Design Theory and Methodology
• +۹ مورد دیگر

Dr. Kate Fu is the Jay and Cynthia Ihlenfeld Associate Professor of Mechanical Engineering at the University of Wisconsin-Madison. She previously held academic positions at Georgia Institute of Technology (2014-2021) and completed postdoctoral fellowships at MIT and Singapore University of Technology and Design. Her education includes a Ph.D. (2012), M.S. (2009) from Carnegie Mellon University, and B.S. (2007) from Brown University. Her research focuses on engineering design cognition, computational design tools, and design innovation. Key areas include creativity enhancement, design-by-analogy methodologies, and integrating artificial intelligence into design processes. She has pioneered work on gender dynamics in engineering teams and equity in education. Notable awards include the NSF CAREER Award (2019), ASME Young Investigator Award (2020), and SREB Mentor of the Year (2022). She actively contributes to engineering education through courses like Geometric Modeling for Design, Experiential Design Projects, and graduate research supervision. Her work bridges disciplinary boundaries with projects on additive manufacturing, design justice frameworks, and social impacts of engineering solutions. Current research explores equity in makerspaces, energy justice metrics, and cognitive processes in design teams.

• Energy Harvesting
• Piezoelectric Materials
• Biomedical Engineering
• +۳ مورد دیگر

Lin Dong is an Assistant Professor in the Department of Mechanical and Industrial Engineering at New Jersey Institute of Technology (NJIT). His research focuses on advanced energy harvesting technologies, particularly in piezoelectric materials, flexible electronics, and their biomedical applications. He leads a federally funded project (NSF grant) titled Membranous Energy Harvester with Tuning Capability for Flexible Electronics , which explores energy harvesting systems for wearable and implantable devices. His research interests include the design of self-powered sensors, piezoelectric hydrogels, and nature-inspired nanofibers for health monitoring. Notable contributions include amphibious energy generators, helical piezoelectric hydrogels for human-machine interfaces, and flexible sensors for cardiac monitoring. His work bridges materials science, biomedical engineering, and mechanical systems, with applications in smart health and wearable technology. Dr. Dong’s publications (29+ articles) emphasize energy harvesting innovations, with 16+ citations. His articles highlight trends in flexible, bio-integrated energy systems and multimodal sensing. He collaborates on projects involving body sensor networks and tunable energy harvesters for flexible electronics. He has secured a 2021 NSF grant (PI) and generated media attention for advancements in flexible energy harvesting and nanofiber research. His lab develops cutting-edge materials and devices for sustainable energy solutions and healthcare applications.

Srinivas Sridharمشاهده پروفایل

عضو هیئت علمی

• Nanomedicine
• Neurotechnology
• Drug Delivery
• +۷ مورد دیگر

Srinivas Sridhar is a University Distinguished Professor of Physics, Biomedical Engineering, and Chemical Engineering at Northeastern University, with a secondary appointment as Lecturer on Radiation Oncology at Harvard Medical School. He previously served as Vice Provost for Research at Northeastern University (2004–2008), overseeing its research portfolio. As an elected Fellow of the American Physical Society and the American Institute of Medical and Biological Engineering, his research spans nanomedicine, neurotechnology, drug delivery, and quantitative MRI, with over 450 publications and patents. He founded the Nanomedicine Innovation Center and directs major NIH/NSF programs like CaNCURE and IGERT, focusing on undergraduate and graduate training in nanomedicine, particularly for underrepresented communities. His research interests include Nanomedicine Neurotechnology Quantitative MRI Drug Delivery Systems Metamaterials and Nanophotonics Quantum Chaos Superconductivity . Recent work involves machine learning-enhanced diagnostics for glaucoma, engineered nanoparticles for BRCA-deficient cancers, and portable neuro-ophthalmic devices. His publications from 2025–2017 reflect interdisciplinary applications in oncology, neurology, and materials science, with a focus on therapeutic and diagnostic innovation. Scientific accolades include the 2016 Biomedical Engineering Society Diversity Award University Distinguished Professorship . As an educator and entrepreneur, he has trained over 120 researchers, developed first-of-their-kind nanomedicine courses, and founded companies commercializing technologies like QUTE-CE MRI. His lab leads projects on cancer nanomedicine, quantitative imaging, and nanoscale magnetism, supported by grants from NIH, NSF, DoD, and private foundations.

John Whitneyمشاهده پروفایل

دانشیار

• Human-safe robotics
• Medical robotics
• Soft robotics
• +۵ مورد دیگر

John Whitney is an Associate Professor in the Department of Mechanical and Industrial Engineering at Northeastern University's College of Engineering. He joined the university in January 2016. His research focuses on human-safe robotics, medical robotics, soft robotics, MEMS, microrobotics, and bio-inspired design, with a particular emphasis on flapping aerodynamics and insect flight mechanisms. He has led major research initiatives including the National Science Foundation-funded 'Controllable Compliance' robotic arm project and Office of Naval Research projects on haptic manipulators for explosive ordnance disposal. Whitney holds a PhD in Engineering Sciences from Harvard University (2012) and an SM in Aeronautics and Astronautics from MIT (2006). He is affiliated with Northeastern's Institute for Experiential Robotics and has contributed to advanced systems like the ANA Avatar XPRIZE robotic avatar. His work integrates interdisciplinary approaches combining mechanical engineering, control systems, and biomedical applications. Education: PhD in Engineering Sciences, Harvard University, 2012 SM in Aeronautics and Astronautics, MIT, 2006 Awards: 2023 Impact Award Finalist, International Conference on Robotics and Automation 2022-2023 College of Engineering Faculty Award Recipient His research spans teleoperation systems, haptic feedback mechanisms, and soft material manufacturing. Notable projects include a MR-safe haptic system for prostate biopsies and a novel robotic arm for contact-rich environments. His lab's work on flapping-wing microrobots draws inspiration from insect flight dynamics to improve micro air vehicle (MAV) performance. Whitney advises teams like the Northeastern Mars Rover Team and ANA Avatar XPRIZE finalists, demonstrating his commitment to hands-on student engagement. His publications emphasize practical robotics solutions for medical, industrial, and exploratory applications.

Daniel Quinnمشاهده پروفایل

دانشیار

• Fluid-Structure Interactions
• Biomechanics
• Bio-Inspired Robotics
• +۲ مورد دیگر

Daniel Quinn is an Associate Professor at the University of Virginia, jointly affiliated with the Department of Mechanical and Aerospace Engineering and the Department of Electrical and Computer Engineering. He is a member of the Link Lab, focusing on Cyber-Physical Systems, particularly autonomous vehicles and bio-inspired robotics. His roles include teaching courses like Aerodynamics I and Fluid Mechanics. Education: BS in Aerospace Engineering (University of Virginia), PhD in Mechanical & Aerospace Engineering (Princeton University). Postdoctoral research at Stanford University and visiting fellowships at Harvard University's Museum of Comparative Zoology. Research focuses on Fluid-Structure Interactions, Biomechanics, Bio-Inspired Robotics, Energy-Harvesting, and Cyber-Physical Systems. Key projects include studying ground effects on propulsion, fish schooling dynamics, and self-powered breath sensors. Notable awards include the NSF Career Award (2020), Pi Tau Sigma Outstanding Faculty Award (2021–2023), and the Hartfield Excellence in Teaching Award (2024–2025). His work bridges experimental optimization, computational modeling, and interdisciplinary collaboration. Grants include DURIP support for advanced research facilities. Lab locations include Olsson Hall and 122 Engineer’s Way. Active in media, featured in articles on teaching excellence and UAV design innovations.

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.