جست‌وجوی استاد و پژوهشگر

• Control Theory
• Digital Signal Processing
• Adaptive Signal Processing and Control
• +۷ مورد دیگر

Dr. Allahyar Montazeri is a Senior Lecturer in Control and Electronics Engineering at Lancaster University's School of Engineering, specializing in advanced control systems and signal processing. His research focuses on adaptive signal processing, robust control, system identification, and applications in robotics, active noise/vibration control, and wave energy conversion. He has over 110 publications and serves on editorial boards such as Frontiers in Robotics and AI, and IFAC Technical Committees. Montazeri holds a Humboldt Research Fellowship (2011) and ERCIM Fellowship (2010). His industrial collaborations include Bosch for automotive noise control and Fraunhofer Institute. He has supervised PhD students in acoustic signal processing and leads projects on autonomous robotics and environmental monitoring. Notable awards include 'Outstanding Associate Editor' (2023) and 'Fellow of The Higher Education Academy.' He actively participates in conferences like IEEE CDC and chairs sessions on mechatronics systems. His work bridges theoretical control advancements with practical applications in extreme environments, including nuclear robotics and underwater systems.

Oscar Mendez Maldonadoمشاهده پروفایل

مدرس

• Robotics
• Artificial Intelligence
• Computer Vision
• +۳ مورد دیگر

Oscar Mendez Maldonado is a Lecturer in Robotics and Artificial Intelligence at the University of Surrey's School of Computer Science and Electronic Engineering, affiliated with the Robotics Department and CVSSP Centre. He holds a PhD (2018) and BEng (2013) from the University of Surrey. His research focuses on Machine Learning, Computer Vision, and Robotics, with emphasis on autonomous systems, localisation, and SLAM applications. Key projects include the Autonomous Valet Parking (AVP) system for indoor navigation and the SMILE project for sign language assessment using AI. He has supervised students like James Ross (Autonomous Vehicles), Xihan Bian (Reinforcement Learning), and Nimet Kaygusuz (Visual Odometry). Notable achievements include the Sullivan Thesis Prize (2018) and impactful publications in IEEE conferences (e.g., ICRA, CVPR, IROS). Research spans topics like 3D hand pose estimation via diffusion models, graph-based visual odometry fusion, and Raman spectroscopy for localisation. He contributes to open-source tools (e.g., RaSpectLoc GitHub) and collaborates with industry partners like Parkopedia. His work bridges theoretical advances with real-world applications in autonomous systems and healthcare.

Ehud Sharlinمشاهده پروفایل

استاد

• Human-robot interaction
• Tangible user interfaces
• Virtual reality
• +۴ مورد دیگر

Ehud Sharlin is a Professor in the Department of Computer Science at the University of Calgary, Faculty of Science. His research focuses on Human-Computer Interaction (HCI) with specializations in human-robot interaction, tangible interfaces, virtual/augmented reality, and autonomous vehicle interactions. He holds a Ph.D. in Computing Science from the University of Alberta (2003), and M.Sc. and B.Sc. degrees in Electrical and Computer Engineering from Ben-Gurion University of the Negev (1997 and 1990). Teaches CPSC 481: Human-Computer Interaction I Recipient of the NSERC Discovery Accelerator Award (2019), ACM Creativity & Cognition Honourable Mention (2018), and multiple academic excellence awards Active in industry collaborations, particularly in medical simulation (e.g., VRSpineSim) and geosciences (e.g., PLANWELL) Research explores: Embodied interaction through robotics and wearables Autonomous vehicle-pedestrian communication systems Immersive tools for creative and professional domains Accessibility in human-technology interfaces Publications span over 100 peer-reviewed works, emphasizing design methodologies, user experience in XR systems, and ethical considerations in sociotechnical systems. His work bridges technical innovation with human-centered design principles.

Orlin D. Velevمشاهده پروفایل

استاد

• Colloid Science
• Soft Materials Engineering
• Nanoscience
• +۷ مورد دیگر

Orlin D. Velev is the S. Frank and Doris Culberson Distinguished Professor of Chemical Engineering at North Carolina State University (NC State), part of the College of Engineering. His research focuses on colloid science, soft materials engineering, nanotechnology, and sustainable nanocomposites. He leads the Velev Lab, pioneering innovations in self-propelling microdevices, environmentally benign nanomaterials, and responsive materials for energy and biomedical applications. Velev's academic journey includes a PhD in Physical Chemistry from Sofia University (1999), followed by M.S. and B.Tech degrees in Chemical Engineering from NC State. His work bridges chemistry, physics, and biology, with notable contributions to microfluidics, colloidal assembly, and battery technologies. He has supervised numerous graduate and undergraduate students, fostering interdisciplinary research and innovation. Key research areas include: Directed assembly of colloids using external fields Self-propelling microbots and active particles Sustainable biopolymer composites (e.g., lignin-based nanoparticles) Soft robotic components and smart materials Biodegradable electronics and energy storage solutions Honors include the Braskem Award, AIChE’s Andreas Acrivos Award, and multiple fellowships. His lab’s recent advancements include osmotic-capillary wearable patches for sweat analysis and high-performance lithium-sulfur battery separators using soft dendritic colloids. Velev collaborates extensively, with projects funded by NSF, industry partnerships, and federal grants. His work emphasizes translating fundamental science into real-world applications, such as biodegradable packaging, microplastic remediation, and wearable health monitoring devices.

Arpan Gujaratiمشاهده پروفایل

عضو هیئت علمی

• Real-Time Systems
• Distributed Systems
• Cyber-Physical Systems
• +۷ مورد دیگر

Arpan Gujarati is a Sessional Lecturer in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Systopia Lab. He teaches graduate and undergraduate courses such as CPSC 538G (Distributed Systems), CPSC 416 (Operating Systems), and CPEN 432 (Real-Time System Design). He holds a PhD from the Max Planck Institute for Software Systems and TU Kaiserslautern, where he was supervised by Björn B. Brandenburg. PhD: Max Planck Institute for Software Systems & TU Kaiserslautern (2020) Undergraduate: Birla Institute of Technology and Science (BITS Pilani) Postdoctoral Researcher: MPI-SWS Research Associate: UBC Software Development Engineer: Citrix R&D, India His research focuses on real-time and distributed systems, with applications in cyber-physical systems, fault tolerance, and machine learning reliability. He investigates scheduling algorithms, reliability analysis, and the integration of learning-enabled components into safety-critical systems. His work combines theoretical analysis with practical system implementations, often involving real-world testbeds and open-source tools. His recent publications span top-tier venues including RTSS, OSDI, ECRTS, DSN, and Middleware, with a strong emphasis on performance predictability, resilience of ML systems, and real-time communication. His work frequently addresses challenges in timing guarantees, fault tolerance, and system reliability in both cloud and embedded environments. SIGBED Paul Caspi Memorial Dissertation Award Best Paper Award at RTSS 2022 Distinguished Artifact Award at OSDI 2020 Best Student Paper Award at Middleware 2017 Outstanding Paper Award at RTCSA 2025 He advises several PhD students and undergraduate researchers at UBC, including Heng Zhao, Aida Aminian, Zainab Saeed Wattoo, and Philip Schowitz. He has led multiple research projects involving robotic arms, NVIDIA Holoscan, FreeRTOS, and distributed key-value stores. His lab work emphasizes reproducibility, open datasets, and practical system building. He has served on program committees for RTSS, RTAS, ECRTS, and Middleware, and contributes to journals such as Real-Time Systems and JSys.

Guanrui Liمشاهده پروفایل

استادیار

• Aerial Robotics
• Control Systems
• Robot Perception
• +۳ مورد دیگر

Guanrui Li is an Assistant Professor at Worcester Polytechnic Institute's Robotics Engineering Department and the director of the Aerial-robot Control and Perception Lab (ACP Lab). He holds a Ph.D. in Electrical and Computer Engineering from NYU (2024), an M.S. in Robotics from the University of Pennsylvania (2018), and a B.E. in Theoretical and Applied Mechanics from Sun Yat-sen University (2016). His research focuses on aerial robotics, including control methodologies for collaborative transportation, human-robot interaction, and perception-aware systems. Key contributions include Hybrid Perception-Aware MPC frameworks, cooperative manipulation algorithms, and simulation tools like RotorTM. Education: Ph.D., Electrical and Computer Engineering, NYU (2024) M.S., Robotics, University of Pennsylvania (2018) B.E., Theoretical and Applied Mechanics, Sun Yat-sen University (2016) Research Interests: Control and perception of aerial robots, human-robot collaboration, cooperative manipulation, and autonomous systems. Notable work addresses challenges in payload transportation, sensor fusion, and safety-critical navigation. Awards: NSF CPS Rising Stars (2023) Outstanding Deployed System Paper Finalist (IEEE ICRA 2022) NYU Dante Youla Award (2022) NYU Outstanding Dissertation Award (2024) Lab & Team: ACP Lab focuses on advancing aerial robotics through interdisciplinary research. Current projects include mixed reality interfaces for human-robot interaction and fault-tolerant control systems. Recent collaborations include workshops on Rust for Robotics (ICRA 2025) and embodied-AI for aerial systems (ICUAS 2025).

Lionel P. Robert Jr.مشاهده پروفایل

استاد

• Autonomous Vehicles
• Human-Robot Interaction
• Collaborative Robotics
• +۵ مورد دیگر

Affiliations & Roles Lionel P. Robert Jr. is a Professor of Information and Robotics at the University of Michigan, holding joint appointments in the School of Information and the College of Engineering's Robotics Department. He directs the Michigan Autonomous Vehicle Research Intergroup Collaboration (MAVRIC) and is an affiliate faculty member at the National Center for Institutional Diversity and Indiana University's Center for Computer-Mediated Communication. His roles include editorial board positions at journals like the Journal of Computer Information Systems and leadership in professional organizations such as ACM and IEEE. Education Ph.D. in Information Systems, Indiana University (BAT Fellow, KPMG Scholar) M.B. from Indiana University, Bloomington M.S. degrees from Clemson University and University of Louisiana, Lafayette B.S. from University of Louisiana, Lafayette Research Focus Robert's research bridges collaboration through technology, with a focus on human-robot interaction, autonomous vehicles, and virtual teams. His work addresses trust in automated systems, human-AV communication, and the sociotechnical implications of robotics in workplaces and public spaces. Recent projects explore explanations for automated vehicles, security robots' societal acceptance, and AI ethics in healthcare and labor. Key Contributions He has published over 100 peer-reviewed articles in journals like MIS Quarterly and conferences such as CHI and HRI. His research has been funded by NSF, Toyota Research Institute, and the Army Research Laboratory. Notable outcomes include frameworks for AV trust repair, models of human-robot team performance, and critiques of AI-driven labor practices. Awards & Recognition ACM Distinguished Member IEEE Senior Member Carnegie Junior Faculty Development Fellowship 3× Teaching Commendation (2006–2008) Grants & Labs Current grants include studies on explainable AI, human-AV trust dynamics, and security robot design. The MAVRIC lab focuses on AV-pedestrian interactions while the CCMC explores digital communication's societal impact.

Jens Altenburgمشاهده پروفایل

استاد

• Robotics
• Embedded Systems
• Microprocessor Technology
• +۳ مورد دیگر

Prof. Jens Altenburg holds the position of Professor of Microprocessor Technology and Embedded Systems at Bingen University of Applied Sciences. His work focuses on robotics, embedded systems, and control engineering. He is affiliated with Department 2, where he contributes to study programs in Computer Science, Electrical Engineering, and related fields. His research interests span robotics, UAVs, and microprocessor-driven automation. Notable publications include works on flight control systems (AONE test bench), image processing for robots, and solar-powered robotics (SOPHOCLES). He has authored technical books on microcontroller programming and mobile robotics, emphasizing practical experimentation and AI integration. While no specific awards are mentioned in the text, his contributions to educational materials and experimental systems highlight his impact in engineering education and applied research.

Stavros Vougioukasمشاهده پروفایل

استاد

• Agricultural Robotics
• Mechanization of Specialty Crops
• Automation in Agriculture
• +۷ مورد دیگر

Stavros Vougioukas is a Professor and Vice Chair in the Department of Biological and Agricultural Engineering at the University of California, Davis, within the College of Engineering. He is actively involved in research and graduate mentorship, focusing on agricultural robotics and automation for specialty crops. His work integrates engineering solutions to improve efficiency and sustainability in farming systems. His research interests include agricultural robotics , automation of harvesting processes , sensors and control systems , precision agriculture , and wireless sensor networks for orchard environments . He develops technologies for robotic and robot-aided harvesting, particularly in strawberries and orchard crops, emphasizing optimal management of inputs and yield monitoring. The recent publications reflect a strong trend in robotics integration , real-time sensing , and data-driven decision-making in agriculture. His work spans mechanical design, signal processing, path planning, and structural durability, indicating a multidisciplinary approach to solving agricultural challenges through engineering innovation. Scientific Awards and Recognition: $1.6M grant (2021) to develop innovative fruit-picking machines CITRIS Seed Award (2023) for engineering solutions in agriculture Professor Vougioukas mentors graduate students and leads funded research projects focused on automation and robotics in agriculture. He has secured significant grants, including a $1.6M award for fruit-picking robotics, demonstrating strong research leadership. His collaborations span institutions and disciplines, particularly in agricultural machinery design and sensor network deployment. He leads research efforts in agricultural automation, particularly through projects involving robot-aided harvesting , orchard navigation systems , and wearable worker tracking devices . His lab contributes to the development of intelligent systems for sustainable farming, integrating mechanical, electronic, and computational components.

• Consumer Behavior
• Artificial Intelligence
• Decision Making
• +۴ مورد دیگر

Stefano Puntoni is a Professor of Marketing and a behavioral scientist at the Rotterdam School of Management, Erasmus University. He serves as Head of the Department of Marketing Management at RSM and as Director of the Psychology of AI Lab at the Erasmus Centre for Data Analytics. His academic journey began with a "Laurea" in Statistics and Economics from the University of Padova in 2000, followed by a Ph.D. in Marketing from London Business School in 2005. His primary research focuses on autonomous technology adoption in consumer markets and production, with particular emphasis on the value of human labor in the age of AI. Additional research areas include advertising language, consumer identity, and numerical cognition. Puntoni's work spans interdisciplinary boundaries, connecting marketing, psychology, and artificial intelligence. An analysis of his recent publications reveals a strong trend toward understanding human-AI interactions in consumer contexts. His research examines how consumers perceive decisions made by algorithms versus humans, preferences for material versus digital products in identity-based consumption, and psychological reactions to human versus robotic job replacement. These studies collectively explore the tension between technological advancement and human elements in decision-making processes. Scientist in Residence, Experiments in Arts and Economics, ZKM Centre for Art and Media (2021) Science Communication Grant, Royal Dutch Academy of Sciences (€10,000) (2021) Case Centre's Marketing Case Award (2021) EFMD Case Writing Award (2020) Case Centre's Outstanding Case Writer Award (2020) C.W. Park Award, Journal of Consumer Psychology (2019) Puntoni has mentored numerous doctoral students, including Phyllis (Jia) Gai, Eugina Leung, and Elisa Maira, many of whom have gone on to prestigious academic positions. He currently serves as Associate Editor for both the Journal of Consumer Research and the Journal of Marketing. His teaching spans marketing strategy, innovation and technology adoption, brand management, and decision making across multiple institutions including RSM, Lancaster University, London Business School, and Bocconi University. As Director of the Psychology of AI Lab at the Erasmus Centre for Data Analytics, Puntoni leads a research team exploring the intersection of human psychology and artificial intelligence in business contexts. His lab focuses on understanding consumer and worker reactions to AI implementation, with practical applications for businesses navigating the digital transformation.

Arrasy Rahmanمشاهده پروفایل

پژوهشگر ارشد

• Game Theory
• Reinforcement Learning
• Transfer Learning
• +۵ مورد دیگر

Arrasy Rahman is a Postdoctoral Research Fellow at Professor Peter Stone’s Learning Agents Research Group (LARG) in the College of Natural Sciences at The University of Texas at Austin. His research focuses on creating adaptive autonomous agents for collaborative tasks, with expertise in game theory, reinforcement learning, and graph neural networks, particularly applied to the ad hoc teamwork (AHT) problem. Education: PhD and MSc from the University of Edinburgh, BSc from Universitas Indonesia His work explores methods to generate diverse teammate policies for training robust agents capable of collaborating with unseen teammates. Recent projects include partnerships with Lockheed Martin Corporation and organizing a workshop at AAAI-24. Arrasy’s research aims to build intelligent agents that assist humans in real-world collaborative decision-making challenges. Research trends in his publications include ad hoc teamwork, reinforcement learning, graph-based policy learning, and multi-agent systems. He has contributed to advancing techniques for best-response diversity and sub-task curriculum frameworks in autonomous agent collaboration. Labs and teams: Arrasy collaborates with the Autonomous Agents Research Group at the University of Edinburgh and the Learning Agents Research Group (LARG) at UT Austin. He is also involved in organizing the Ad-Hoc Teamwork Seminar Series and a AAAI-24 workshop.

Meyer Nahonمشاهده پروفایل

استاد

• Dynamics and Control
• Aerospace Engineering
• Unmanned Aerial Vehicles (UAVs)
• +۴ مورد دیگر

Meyer Nahon is a Professor at McGill University specializing in dynamics and control systems with cross-domain applications in aerospace, underwater vehicles, and robotics. He maintains active affiliations with the Aerospace Mechatronics Lab, Centre for Intelligent Machines (CIM), and McGill Institute for Aerospace Engineering (MIAE). His academic credentials include: Ph.D. from McGill University M.ASc. from University of Toronto B.ASc. from Queen's University Research spans fundamental mechanical systems (cable dynamics, vehicle dynamics), aeronautical systems (tethered aerostats, autonomous vehicles), underwater systems (ROVs/AUVs), and robotics (parallel mechanisms, flight simulators). His work integrates sensor-based motion measurement using accelerometers, rate gyros, and GPS for comprehensive dynamic analysis across platforms. Recent publications (2015-2019) reveal concentrated UAV research including aerobatic maneuvering, slipstream dynamics, and propeller modeling, while extending to marine structures through mooring system analysis. This demonstrates consistent application of control theory across aerial, marine, and mechanical domains with emphasis on extreme maneuvering and system validation. As leader of the Aerospace Mechatronics Lab, he directs research in cable-actuated systems (cranes, elevators), UAV motion planning, and underwater vehicle dynamics within McGill's collaborative research ecosystem.

Tyson Govan Phillipsمشاهده پروفایل

مدرس ارشد

• Autonomous Systems
• Robotics
• Mining Automation
• +۴ مورد دیگر

Dr. Tyson Phillips serves as Senior Lecturer and Director of Teaching and Learning at The University of Queensland's School of Mechanical and Mining Engineering within the Faculty of Engineering, Architecture and Information Technology. He is an active Affiliate of the Future Autonomous Systems and Technologies research group, focusing on translating robotics innovations into practical mining applications. His academic leadership includes curriculum development for engineering programs and direct industry engagement with major mining equipment manufacturers. He earned his Doctor of Philosophy (PhD) from The University of Queensland in 2016, with thesis research centered on LiDAR-based perception systems for autonomous excavators. His doctoral work established foundational methods for object pose verification in mining contexts. Phillips' research specializes in robotics perception for extreme mining environments, developing LiDAR-centric solutions for autonomous equipment operation amid dust, fog, and unstructured terrain. Key contributions include evidential reasoning frameworks for uncertainty management, real-time pose estimation algorithms, and sensor fusion techniques for excavators and bulldozers. His work bridges theoretical computer vision with industrial deployment, targeting operational safety and efficiency in mineral extraction. Publication analysis reveals consistent focus on mining robotics since 2012, with recent works (2021-2024) emphasizing minimal-sensor configurations, probabilistic terrain mapping, and vibration-assisted gripper technology. His 14 scholarly outputs demonstrate evolution from sensor evaluation (2012-2015) toward integrated autonomy systems (2018-2024), predominantly in Journal of Field Robotics and Sensors . He actively supervises graduate researchers as Principal Advisor for a PhD on multimodal perception mapping and Associate Advisor for two PhD projects involving spreader systems and physics-informed neural networks. Completed supervision includes a 2024 PhD on bulldozer terrain mapping and a 2021 Master's on shovel/hopper interaction strategies. Research funding spans 14 projects from 2012-2026, including current Australian Coal Association Research Program support (2025-2026) and major Caterpillar Inc. collaborations for ERS self-protection and articulated truck automation. Phillips operates within The University of Queensland's Future Autonomous Systems and Technologies group, which develops field-deployable autonomy solutions for mining partners. This team conducts real-world testing of perception systems using Caterpillar and FMG operational sites as validation environments.

Almut Sophia Koepkeمشاهده پروفایل

پژوهشگر

• Multi-Modal Learning
• Computer Vision
• Audio-Visual Processing
• +۳ مورد دیگر

Dr. Almut Sophia Koepke is a junior research group leader and TUM Junior Fellow at the Technical University of Munich (TUM) and University of Tübingen. She leads the multi-modal learning research group focusing on video understanding through sound, vision, and text integration. University: Technical University of Munich School: TUM School of Computation, Information and Technology Department: Informatics 9 Academic Rank: Researcher Her research spans multi-modal learning, audio-visual foundation models, and cross-modal attention mechanisms. Key themes include: Advancing zero-shot learning through language-guided audio-visual models Developing explainable AI systems via attention pattern translation in VQA Exploring temporal understanding in video-adverb retrieval Building robust multi-modal representations for self-driving applications Recent publications analyze foundation model capabilities in audio-visual tasks (ICCV 2025), temporal reasoning (ACMMM 2024), and cross-modal attention frameworks (ECCV 2022). She co-organizes CVPR workshops on foundation model evaluations and serves as area chair/reviewer for major conferences.

François Gouletteمشاهده پروفایل

استاد

• 3D Point Cloud Processing
• LiDAR Perception
• Autonomous Systems
• +۷ مورد دیگر

François Goulette is a Professor and Deputy Director of the Computer Science and Systems Engineering Unit (U2IS) at ENSTA Paris, part of Institut Polytechnique de Paris. His research focuses on 3D point cloud processing, LiDAR perception, and autonomous systems within the Robotics Center (CAOR). His primary research interests lie in 3D point cloud processing , LiDAR perception , and autonomous systems . His work spans fundamental algorithm development to practical applications in autonomous driving, cultural heritage digitization, and robotics. He has made significant contributions to domain generalization of LiDAR perception, semantic segmentation of 3D point clouds, and point cloud registration techniques. The analysis of his recent publications reveals a strong focus on domain generalization for LiDAR perception systems, with multiple papers addressing challenges in 3D semantic segmentation across different environments. His work combines multi-scale architectures , unsupervised learning , and dataset creation to advance the state-of-the-art in autonomous systems perception. The research spans both theoretical algorithm development and practical applications in urban environments. François Goulette leads research activities within the Robotics Center (CAOR) at ENSTA Paris. His team develops advanced techniques for 3D environment understanding, with applications in autonomous vehicles, cultural heritage preservation, and industrial robotics. The research combines computer vision, machine learning, and robotics to solve challenging problems in 3D perception and scene understanding.