جست‌وجوی استاد و پژوهشگر

Young-Jin Chaمشاهده پروفایل

استاد

• Deep Learning
• Structural Health Monitoring (SHM)
• Autonomous UAVs
• +۵ مورد دیگر

Dr. Young-Jin Cha is a tenured full Professor in the Department of Civil Engineering at the University of Manitoba, affiliated with the Price Faculty of Engineering. He holds a PhD from Texas A&M University and has postdoctoral experience at MIT. His research focuses on deep learning-based structural health monitoring (SHM), autonomous UAVs for infrastructure inspection, and smart transportation systems, with over 100 peer-reviewed publications and $1.2M in grants. He is a Fellow of ASCE and has received notable awards including the 2021 Merit Award and 2022 International Association of Advanced Materials Scientist Award. His work has been cited over 9,200 times globally. Research interests include automated SHM with UAVs, nonlinear system identification, unsupervised deep learning for damage detection, and sustainable infrastructure design. He serves as an editor for journals like Structural Control & Health Monitoring and Engineering Reports . His lab, the Laboratory for Infrastructure Science and Technology (LIST), develops advanced technologies for infrastructure resilience. Key achievements include pioneering deep learning-based SHM with UAVs, top-cited papers in civil engineering journals, and leadership in organizing international conferences. He actively seeks graduate students for research in AI-driven infrastructure solutions.

Fahim Khanمشاهده پروفایل

استادیار

• Computer Graphics
• Data Visualization
• Computer Vision
• +۵ مورد دیگر

Fahim Khan is an Assistant Professor in the Department of Computer Science and Software Engineering at California Polytechnic State University’s College of Engineering. He specializes in computer graphics, data visualization, computer vision, and machine learning, with a focus on applying these technologies to education, environmental monitoring, and public safety. His research emphasizes making complex data accessible through advanced tools, bridging the gap between raw data and actionable insights. He is deeply committed to inclusive education and fostering interdisciplinary collaboration. His work often integrates citizen science initiatives, empowering communities through mobile applications and machine learning. Notable projects include real-time rip current detection systems and platforms for high school students to engage in research. Khan advocates for equity in technology, designing inclusive learning environments and promoting diversity in STEM. He actively supports the university’s Learn by Doing philosophy, blending practical education with theoretical rigor. Professionally, he contributes to coastal observation networks and autonomous vehicle datasets while maintaining a balance through outdoor activities like exploring Pismo Beach. His research trends reflect a strong focus on mobile computing, environmental applications, and education technology, with recent efforts emphasizing citizen science and data-driven solutions. While no formal grants or advising records are detailed, his projects implicitly involve collaborative efforts. He is affiliated with labs focused on environmental monitoring and mobile technology development, though specific lab names are not mentioned.

Brian Surgenorمشاهده پروفایل

استاد

• Mechanical Engineering
• Machine Vision Systems
• Autonomous Vehicles
• +۳ مورد دیگر

Professor Brian Surgenor is a faculty member at Queen's University's Department of Mechanical and Materials Engineering, part of the Smith Engineering faculty. He holds a B.Sc. (1977), M.Eng. (AECL/Whiteshell), and Ph.D. (1983) in Mechanical Engineering from Queen's University. His research focuses on machine vision systems for automation, autonomous vehicle navigation, and mechatronic system design education. He has held key administrative roles including Department Head (1993-2002), Associate Dean (2008-2013), and Vice-Dean (2013-2016). His work emphasizes interdisciplinary innovation, such as the Mitchell Hall design project and contributions to Ingenuity Labs. Education: B.Sc. Mechanical Engineering, Queen's University (1977) M.Eng. Engineering Physics, McMaster University (AECL/Whiteshell) Ph.D. Mechanical Engineering, Queen's University (1983) Research interests include: - Pneumatic servosystems - Intelligent algorithms for machine vision - Off-road autonomous vehicle systems - Mechatronics education methodologies - Hybrid powertrain systems for vehicles His recent publications (2017–2024) explore autonomous systems, machine vision applications, and fuel cell hybrid technologies. Notable trends include advancements in UAV-based infrastructure inspection, terrain-adaptive autonomous driving, and low-cost machine vision solutions for small part sorting. His work bridges theoretical control systems with practical industrial automation challenges. He has contributed to laboratory design for CDIO curricula and pioneered mechatronics education through problem-based learning. His administrative leadership has shaped Queen's engineering graduate programs and research infrastructure. Currently involved in Ingenuity Labs, fostering cross-disciplinary innovation.

Melih Kandemirمشاهده پروفایل

دانشیار

• Machine Learning
• Reinforcement Learning
• Bayesian Inference
• +۳ مورد دیگر

Melih Kandemir is an Associate Professor at the Department of Mathematics and Computer Science, Southern Denmark University. He also serves as Research Group Leader at the Bosch Center for Artificial Intelligence (2018–2021) and held a previous role as Assistant Professor at Ozyegin University (2017–2018). His research focuses on machine learning, Bayesian methods, reinforcement learning, and uncertainty quantification. **Education**: PhD in Computer Science from Aalto University (2013), specializing in 'Learning Mental States from Biosignals'. **Research Interests**: Machine Learning, Bayesian Inference, Reinforcement Learning, Deep Neural Networks, Stochastic Processes. His work emphasizes theoretical foundations and practical applications in domains like medical imaging, control systems, and robotics. **Awards**: Two Best Paper Awards (2017). **Grants & Projects**: Includes the Carlsberg Young Researcher Fellowship (2022–2026), Novo Nordisk Foundation grants (2021–2024), and DFF-funded research on PAC-Bayesian reinforcement learning (2025–2027). **Labs/Teams**: Leads research on Bayesian deep learning and reinforcement learning within the Bosch Center for AI and SDU's interdisciplinary groups.

Erisa Karafiliمشاهده پروفایل

دانشیار

• Cybersecurity
• Formal Methods in Security
• IoT Threat Models
• +۴ مورد دیگر

Erisa Karafili is an Associate Professor in Cybersecurity at the University of Southampton. She leads Teaching Methods Innovation at the GCHQ/EPSRC Academic Centre of Excellence for Cyber Security Education (ACE-CSE) and is a Champion in Security by Design at ACE-CSR. A Fellow of the Higher Education Academy, she joined the University in 2020 after roles including a Marie Curie Fellowship at Imperial College London, where she investigated cyber-attack attribution techniques. Her research focuses on formal methods applied to security, IoT threat models, and secure data sharing frameworks. Education: PhD in non-classical logics applied to multi-agent systems security from the University of Verona. Previous positions include PostDoc at Technical University of Denmark and Researcher at Imperial College London. Research Interests: Cyber-attack attribution, IoT security, formal methods in cybersecurity, data privacy, and argumentation-based reasoning for security. Awards: Higher Education Academy Fellowship. Current PhD Students: Betul Gokkaya, Mohammed Homaid Alquliti, Peter Geoffrey Williams, Steve Johnson. Active Projects: Heterogeneous Material Integrated MEMS/NEMS-Photonics Platform for Secure Communication (collaborative with Jize Yan and others).

Edward Johnsمشاهده پروفایل

دانشیار

• Robot Learning
• Robot Manipulation
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Edward Johns is an Associate Professor in the Department of Computing at Imperial College London and Director of the Robot Learning Lab. He specializes in robot learning, focusing on enabling robots to learn tasks through imitation and language-based reasoning. His expertise spans robotics, machine learning, and computer vision, with a particular emphasis on manipulation tasks requiring physical interaction with objects. He holds a BA and MEng from the University of Cambridge and a PhD from Imperial College London. Prior to his current role, he was a postdoc at UCL, a founding member of the Dyson Robotics Lab, and led the robot manipulation team there. He also served as Head of Robot Learning at Dyson (part-time, 2021–2022). His research has produced state-of-the-art capabilities such as one-shot imitation learning and language-driven task execution. Key areas of interest include sim-to-real transfer, self-supervised learning, and adaptive robotic systems. His work bridges foundational AI research with practical robotics applications, emphasizing real-world deployment and human-robot collaboration. Dr. Johns has published over 60 peer-reviewed papers, with over 4,000 citations, and has received prestigious awards including the UK-RAS Early Career Award (2023) and the Best Conference Paper Award at ICRA (2024). He is also actively involved in industry through advisory roles for robotics and AI startups. His teaching includes graduate courses on reinforcement learning and robot learning, and he collaborates extensively with labs such as the Robotics Forum and the Artificial Intelligence Network at Imperial College.

Constantin A. Rothkopfمشاهده پروفایل

استاد

• Perception and Action
• Computational Neuroscience
• Machine Learning
• +۳ مورد دیگر

Prof. Constantin A. Rothkopf is a W3 Professor at the Department of Psychology, Technische Universität Darmstadt, and a secondary member of the Department of Computer Science. He serves as Founding Director of the Centre for Cognitive Science and founding member of the Hessisches Zentrum für Künstliche Intelligenz (hessian.ai). He is also part of the European Laboratory for Learning and Intelligent Systems (ELLIS) and the DAAD Konrad Zuse Schools of Excellence in Artificial Intelligence (ELIZA). His research focuses on the interplay between perception and action, using computational models and experimental studies in humans. Current work includes eye-tracking studies in naturalistic environments, inverse optimal control models, and developing algorithms for virtual agents. Education: Ph.D. in Neuroscience and Informatics from the University of Rochester, followed by postdoctoral research at Frankfurt Institute for Advanced Studies (FIAS). He has held visiting professorships at Central European University (2017) and Columbia University (2023). Awards include an ERC Consolidator Grant (2022) and SCENE Project Funding (2025). Research Interests: Active vision, decision-making under uncertainty, sensorimotor control, and computational modeling. Key themes include how humans use sensory input to form beliefs, make decisions, and act in dynamic environments. Grants/Awards: ERC Consolidator Grant (2022), SCENE Funding (2025) Labs/Teams: Centre for Cognitive Science, hessian.ai, ELLIS Unit Darmstadt

Elliot Wright Hawkesمشاهده پروفایل

دانشیار

• Robotics
• Soft Robotics
• Mechanical Engineering
• +۳ مورد دیگر

Elliot Wright Hawkes is an Associate Professor at the Department of Mechanical Engineering , University of California, Santa Barbara . He leads the Hawkes Group, focusing on robotics innovation through design, mechanics, and non-traditional materials. His research enables robust, adaptable, human-safe robots for unstructured environments. Hawkes holds a PhD in Mechanical Engineering (2015) and MS in Mechanical Engineering (2014) from Stanford University, and a AB in Mechanical Engineering (2011) from Harvard. Research Areas : Solid Mechanics, Materials & Structures, Dynamic Systems and Control, Robotics, Biomechanics, Micro/Nanoscale Engineering Key Projects : Bio-inspired microstructured adhesives, Non-linear compliant mechanisms, High-power soft actuators, Soft exoskeletons, Growing robots His work has produced 20+ patents and 15+ recent publications spanning vine robots, soft actuators, rehabilitation devices, and extreme mobility systems. Notable awards include: Presidential Early Career Award for Scientists and Engineers (PECASE) National Science Foundation CAREER Award NASA Early Career Faculty Award 2020 Packard Fellow Northrop Grumman Excellence in Teaching Award Student Advisees (PhD/Master's): Matthew Devlin, William Heap, Sophia Paul, Nathan Usevitch, Charles Xiao, Nicholas Naclerio, David Haggerty, Lucia Gan, Patrick Slade, Cole Simpson, Mengjia Zhu, Anna Alvarez, Mijail Mendoza Flores, Laura Blumenschein, Tania Morimoto, Zachary Hammond, Muhammad Usman, Hao Jiang, Inrak Choi, and others. Laboratory Focus : The Hawkes Lab explores the intersection of design, mechanics, and materials to solve challenges in robotics, medicine, and biomechanics. Notable projects include: Material-like robotic collectives with spatiotemporal control Variable friction shoe for rehabilitation (US Patent 12,082,641) Soft robotic burrowing devices for NASA applications Light-controlled actuator arrays for extreme environments Plant root-inspired anchoring systems for granular media

• Software Engineering
• Industrial Automation
• Cloud Computing
• +۷ مورد دیگر

David Hästbacka is an Associate Professor (tenure track) at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences at Tampere University. His research focuses on software engineering, industrial automation, and energy systems, emphasizing system architecture, interoperability frameworks, and dependable IoT solutions. He leads a research group exploring edge and cloud computing, semantic integration, and smart energy systems. Education & Professional Background : While specific educational details are not provided, his academic career includes roles such as Postdoctoral Researcher in the SEMIS project (2017-2020) and extensive involvement in EU-funded initiatives like COCOP (EU H2020) and Horizon Europe projects. Research Projects : Active in high-impact projects like Hedge-IoT (Horizon Europe, 2024-2027), TwinfFlow (Business Finland), and TRINEFLEX (Horizon Europe), with a focus on industrial automation, distributed systems, and energy grids. Past projects include FEMMa (Business Finland), DisMa (Academy of Finland), and Arrowhead (ECSEL). Teaching & Supervision : Specializes in Web/Cloud architectures, IoT systems, and dependable automation technologies. Supervises students in topics like edge computing frameworks and MLOps pipelines. Technical Contributions : Develops frameworks for industrial interoperability (e.g., OPC UA PubSub integration), edge-cloud toolchains, and MLOps methodologies. His work addresses challenges in microservices, Kubernetes distributions, and semantic data integration. Labs & Teams : Leads a research group advancing automation technologies through interdisciplinary collaboration, with partnerships in industry and academia to bridge theory and practice in smart systems.

Roman Kucمشاهده پروفایل

استاد

• Robotics
• Biomimetic Sensors
• Digital Signal Processing
• +۴ مورد دیگر

Roman Kuc is a Professor of Electrical Engineering at Yale University, affiliated with the School of Engineering & Applied Science. He directs the Intelligent Sensors Laboratory, focusing on biomimetic sensors for robotics and bioengineering. His research explores brain-based devices (BBDs), sonar sensing, and neuromorphic processing inspired by biological systems. He holds a BSEE from Illinois Institute of Technology and a PhD from Columbia University. Dr. Kuc’s work bridges signal processing, robotics, and bioengineering, with applications in autonomous systems and clinical diagnostics. He has published over 200 papers and authored textbooks like Electrical Engineering in Context and The Digital Information Age . Notable honors include an honorary doctorate from the Glushkov Institute of Cybernetics and the Yale Sheffield Distinguished Teaching Award. His research themes include cognitive mapping via sonar echoes, neural network-based classification of environmental features, and biomimetic approaches to echolocation. Recent work emphasizes sensorimotor integration and robust performance in uncertain environments. Scientific awards highlight his contributions to robotics, signal processing, and education. His lab develops systems that emulate biological sensory mechanisms, aiming to advance robotics, medical applications, and assistive technologies.

Fu-Kuo Changمشاهده پروفایل

استاد

• Multi-functional materials
• Intelligent structures
• Structural health monitoring
• +۷ مورد دیگر

Fu-Kuo Chang is a Professor in the Department of Aeronautics and Astronautics at Stanford University, with a secondary affiliation in the Bio-X program. His research focuses on multifunctional materials, intelligent structures, and structural health monitoring (SHM), emphasizing applications in aerospace, robotics, and medical devices. He has pioneered work on embedded sensors, self-diagnostic systems, and energy storage composites. Academic Appointments: Professor (Stanford), Editor-in-Chief of International Journal of Structural Health Monitoring (since 2012), and Chair of the International Workshop on Structural Health Monitoring (since 1997). Honors: Multiple lifetime achievement awards in SHM, AIAA and ASME Fellowships, and the NSF Presidential Young Investigator Award (1988). Research interests include bio-inspired sensory materials, autonomous systems (e.g., 'fly-by-feel' vehicles), and multidisciplinary integration of structural mechanics, electrical engineering, and materials science. His recent work addresses challenges in smart skins for robotics, thermoplastic composites, and predictive modeling of material degradation. Publications span structural health monitoring, advanced composites, and robotics, reflecting expertise in both theoretical and applied domains. His lab, the Structures and Composites (SACL) laboratory, drives innovation in smart materials and system integration. Advising: Supervises doctoral and master’s students in aeronautics and materials science. Grants/Contributions: Active in industry and government collaborations, including roles on the US Army Research Laboratories Advisory Board and leadership in SHM industry initiatives.

Karthik Dantuمشاهده پروفایل

دانشیار

• Mobile Sensor Networks
• Robot Networks
• Networked Embedded Systems
• +۸ مورد دیگر

Karthik Dantu is an Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York, within the School of Engineering and Applied Sciences. His research focuses on mobile sensor networks, robot networks, networked embedded systems, mobile computing, wireless networks, and embedded operating systems. He leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab and has received significant funding including an NSF CAREER Award. Dr. Dantu's educational background includes: PhD in Computer Science from University of Southern California (2009) BE in Computer Science from Sri Jayachamarajendra College of Engineering (1999) His research interests center on algorithmic and systems challenges in Edge Computing Systems, with particular focus on enabling seamless vision sensing in cloud-edge environments. Dantu's work bridges mobile systems and robotics, developing novel approaches for UAV software, visual SLAM, and distributed sensing. His research addresses critical challenges in resource-constrained environments, security, and real-time performance for mobile and robotic systems, with emphasis on practical implementations that solve real-world problems in autonomous systems. Dr. Dantu's publication record shows a strong trajectory in mobile systems and robotics research, with increasing focus on edge computing applications for visual sensing. His recent work demonstrates expertise in adapting visual SLAM to edge environments, securing mobile systems through technologies like Rushmore, and developing novel approaches for UAV software reliability and depth sensing. The research spans theoretical algorithms and practical system implementations, with particular strength in bringing academic research to practical applications in robotics and mobile computing. Dr. Dantu has received several scientific honors: NSF CAREER Award on Enabling Seamless Vision Sensing in Cloud-Edge Systems Outstanding service award from the Office of International Services NSF Travel Grant for SenSys 2005 Conference Travel Grant for SIGCOMM 2002 As an advisor, Dr. Dantu has mentored numerous PhD students to completion, with graduates now working at companies like Samsung Research and Zoox Inc., or continuing academic careers as Assistant Professors. His research is supported by substantial grants including a DARPA OFFSET Sprint 4 award ($470k), an NSF CAREER award ($550k), and multiple NSF collaborative grants totaling over $1.5 million. He serves on numerous conference committees including Mobicom, MobiSys, and ICRA, demonstrating leadership in the mobile systems and robotics research communities. Dr. Dantu leads the Distributed Robotics and Networked Embedded Sensing (DRONES) Lab at UB, which focuses on developing algorithms and systems for mobile sensor networks, robot networks, and embedded sensing applications. The lab's work spans theoretical foundations to practical implementations, with particular expertise in UAV systems, visual SLAM, and edge computing for robotics, maintaining strong collaborations with industry partners and other academic institutions to advance the state of the art in mobile and robotic systems.

Elisabeth Hoffberger-Pippanمشاهده پروفایل

عضو هیئت علمی

• International Security
• Arms Control
• Non-Proliferation
• +۳ مورد دیگر

Dr. Elisabeth Hoffberger-Pippan is a Senior Researcher at the Peace Research Institute Frankfurt (PRIF), specializing in international security with a focus on verification mechanisms for biological/chemical weapons norms and the ethical implications of AI in military contexts. She holds affiliations with CBWNet and iPRAW initiatives, addressing arms control and autonomous weapons regulation. Her academic background includes postdoctoral research and lecturing at Johannes Kepler University Linz (2015–2022). She has contributed to policy dialogues, including a keynote speech in the Austrian Parliament, and serves on editorial boards for journals like Jahrbuch Digitalisierung und Recht . Key awards include the Ernst-Otto Czempiel Award and Hessian Peace Prize. Her work spans publications on UN compliance procedures, AI ethics, and legal frameworks for emerging technologies. Recent policy engagement includes analyses of Gaza conflict arms exports and Dutch court rulings on Israel’s military actions. Education: PhD in International Law (university details implicit in professional trajectory). Key Projects: Lead roles in iPRAW (autonomous weapons regulation) and CBWNet (biological/chemical weapons compliance). Publications emphasize interdisciplinary approaches to arms control, human rights in technology, and legal responses to modern warfare. She actively contributes to policy blogs (e.g., PRIF Blog) and edited volumes on digitalization and international law.

Samuel Lederمشاهده پروفایل

پژوهشگر

• Robotics
• Architectural Design
• Computational Design
• +۵ مورد دیگر

Samuel Leder is a doctoral researcher at the Institute of Computational Design and Construction (ICD) under the Cluster of Excellence IntCDC at the University of Stuttgart. His work focuses on the integration of robotics and architectural design, particularly in developing distributed robotic systems for timber construction. He has been actively involved in research projects such as RP 19-1 – Robotic Kinematic System for Parallel Construction and RP 19-2 – Co-Design for Distributed Cooperative Multi-Robot Systems . Additionally, he serves on the Equal Opportunity Commission at ICD. Bachelor of Design in Architecture (summa cum laude), Washington University in St. Louis Bachelor of Applied Science in Systems Science and Engineering (magna cum laude), Washington University in St. Louis MSc in Architecture via the Integrative Technologies and Architectural Design Research (ITECH) program, University of Stuttgart Samuel’s research explores the synergies between agent-based modeling , robotic systems , and architectural design . His work aims to create minimal robotic machines capable of constructing complex spatial assemblies, particularly with timber structures . He investigates the co-design of robots and the structures they build, emphasizing modular systems and kinematic behaviors . Recent publications highlight advancements in digital twins , adaptive assembly , and human-robot collaboration for timber construction. The 15 most recent articles reveal trends in collective robotic construction , agent-based modeling , and material-robot interaction . These works emphasize timber fabrication , modular systems , and interactive simulation for large-scale construction tasks. Key sub-fields include adaptive assembly , cyber-physical systems , kinematic control , and human-guided robotics . Scientific Awards: German Academic Exchange Service (DAAD) Award for Outstanding Achievement Deutschlandstipendium Samuel’s research is conducted within the ICD at University of Stuttgart , where he collaborates on the Wood Building Systems for Distributed Robotics associated project. His work bridges architecture , robotics , and computational design , aiming to redefine on-site construction methodologies through innovative robotic systems.

Thomas K. Uchidaمشاهده پروفایل

دانشیار

• Biomechanics
• Dynamical Systems
• Musculoskeletal Modeling
• +۷ مورد دیگر

Thomas K. Uchida is an Associate Professor in the Department of Mechanical Engineering at the University of Ottawa, a position he has held since May 2024. Prior to this promotion, he served as an Assistant Professor at the same institution from October 2018 to May 2024. Before joining the University of Ottawa, Dr. Uchida was an Engineering Research Associate (April 2015-August 2018) and Simbios Distinguished Postdoctoral Fellow (July 2012-April 2015) in the Department of Bioengineering at Stanford University. Dr. Uchida's research focuses on the modeling and simulation of dynamic systems, with particular emphasis on human movement biomechanics. His work spans multiple areas including: Simulation-guided design of assistive devices for improving mobility Modelling musculotendon dynamics and energy expenditure Parameter identification and model reduction methods Impact and contact dynamics Development of computational tools for biomechanical analysis He is a co-author of the book "Biomechanics of Movement: The Science of Sports, Robotics, and Rehabilitation" published by MIT Press, and actively contributes to the development of OpenSim, an open-source software platform for modeling musculoskeletal systems and generating simulations of human and animal movement. His work on OpenSim was featured on the cover of PLoS Computational Biology. Dr. Uchida's recent publications demonstrate strong activity in biomechanics, robotics, and computational modeling. His work bridges engineering principles with biological applications, particularly in understanding human movement mechanics. Key trends include applying machine learning to gait analysis, developing enhanced spine models, analyzing human balance stability with time delays, and advancing musculoskeletal simulation techniques. As an academic advisor, Dr. Uchida currently supervises seven graduate students: Firas Baklouti (expected completion August 2025) Shahin Sharafi Kazem Alambeigi Jiawei Gao Yuzhen Yan Manuel Lucas De Oliveira Blake Scott Miller Dr. Uchida collaborates with research teams focused on biomechanics and movement science. His work with OpenSim places him within an international community of researchers developing computational tools for biomechanical analysis, connecting mechanical engineering with biomedical applications in sports, robotics, and rehabilitation.