جست‌وجوی استاد و پژوهشگر

• High-Performance Integrated Circuit Design
• Artificial Intelligence Accelerators
• Digital Signal Processing Chips
• +۳ مورد دیگر

Dr. Fengwei An is an Associate Professor at the Shenzhen-Hong Kong Institute of Microelectronics , Southern University of Science and Technology (SUSTech). He earned his Ph.D. in Engineering from Hiroshima University (2013) , following a Master's (2010) and Bachelor's (2006) from Qingdao University of Science and Technology. Current Role : 2025-Present - Associate Dean and Associate Professor, SUSTech Shenzhen-Hong Kong Institute of Microelectronics Prior Academic Roles : 2017-2018 - Associate Professor, Hiroshima University; 2013-2017 - Assistant Professor, Hiroshima University Industry Experience : 2018-2019 - Chief Engineer, Panasonic Semiconductor Co., Ltd., Japan Research Interests focus on low-power edge artificial intelligence chip design for computer vision, including: Ultra-large-scale digital integrated circuit design System-on-Chip (SoC) integration Image processing and recognition Machine learning hardware Autonomous driving applications High-speed motion tracking systems Publications include over 80 top-tier journal/conference papers (e.g., TCAS-I/II, ESSCIRC, APCCAS) on AI accelerators, stereo vision processors, and sensor interfaces, with 15 recent articles highlighting advancements in stereo matching, video denoising, and reconfigurable coprocessors. Scientific Awards : 2023 - SUSTech Outstanding Teaching Award 2022 - APCCAS Best Paper Nomination 2022 - PrimeAsia Bronze Leaf Award 2020 - Wu Wenjun Artificial Intelligence Science and Technology Award (Second Prize) Patents : 9 Chinese and 3 Japanese inventions in AI chip design, stereo matching systems, and sensor interfaces.

Pedro Porto Buarque de Gusmãoمشاهده پروفایل

مدرس

• Computer Vision
• Navigation under adverse conditions
• Sensor Fusion
• +۴ مورد دیگر

Pedro Porto Buarque de Gusmão is a Lecturer in Computer Science at the University of Surrey, affiliated with the Computer Science Research Centre within the School of Computer Science and Electronic Engineering. His research focuses on Computer Vision, Navigation under adverse conditions, Sensor Fusion, and Distributed Machine Learning. He leads projects in federated learning, autonomous systems, and robotic navigation, contributing to frameworks like Flower, a widely used federated learning library. His work emphasizes advancing federated learning techniques for privacy-preserving distributed systems, with notable achievements including winning the First Prize in the NIST Privacy-Enhancing Technologies Prize Challenge (2023). His publications span conferences like ICCV, USENIX Security, and IEEE Transactions, addressing topics such as federated learning optimization, 3D lane detection, and thermal-inertial SLAM. Key contributions include developing methods like L-DAWA for federated visual learning and FedVal for federated model validation. His research also integrates multimodal sensor data for autonomous navigation systems, leveraging mmWave radar and thermal-inertial fusion. He actively contributes to open-source projects and collaborates with industry on privacy-aware machine learning solutions.

Tobias Seidlمشاهده پروفایل

استاد

• Bionics
• Biomechanics
• Neuroethology
• +۳ مورد دیگر

Prof. Tobias Seidl serves as Vice Dean at the Westphalian Institute for Bionics within the Department of Mechanical Engineering at the Westphalian University of Applied Sciences in Bocholt, Germany. He has been with the university since January 2011, teaching bionics and sensor technology while leading research in biomimetic applications for robotics and engineering. Education: Bionics studies at Saarbrücken PhD on desert ant navigation systems under Rüdiger Wehner at the University of Zurich with fieldwork in Tunisia Professional experience at the European Space Agency (ESA) in Noordwijk, Netherlands Research Focus: Prof. Seidl's work centers on bionics , translating biological principles into engineering solutions. His expertise spans neuroethology (neural basis of natural behavior), functional morphology (structure-function relationships), and biomechanics . Key application areas include biomimetic robotics inspired by ants and spiders, sensor development, and bio-inspired materials. His research consistently bridges entomology with robotics, aerospace, and materials science to solve complex engineering challenges. Publication Trends: Recent publications (2025-2016) reveal a strong focus on biomimetic applications in robotics, 3D printing, and aerospace. Dominant themes include adaptive biomimetic valves for automotive cooling, force-based path integration in walking robots, hydrophobic surface replication, and satellite deployable structures inspired by insect wings. His work consistently leverages biological observations—particularly from desert ants and spiders—to advance robotic locomotion, adhesion mechanisms, and space technology. Research Infrastructure: As head of the Westphalian Institute for Bionics, Prof. Seidl leads R&D projects such as developing force sensors in ant legs for robotic applications. His institute serves as a hub for interdisciplinary collaboration between biologists and engineers, focusing on translating biological insights into technical innovations for automotive, aerospace, and medical applications.

Le Chenمشاهده پروفایل

پژوهشگر

• Robotics
• Machine Learning
• Reinforcement Learning
• +۵ مورد دیگر

Le Chen is a Doctoral Researcher at the Empirical Inference Department of the Max Planck Institute for Intelligent Systems and ETH Zurich , advised by Prof. Bernhard Schölkopf and Prof. Dieter Büchler. Previously, he obtained his M.S. in Electrical Engineering and Information Technology from ETH Zurich and gained research experience at Microsoft Mixed Reality & AI Lab, Tencent AI Lab, and Tencent Robotics X Lab. Research Interests: Le Chen focuses on the intersection of robotics and machine learning, with a specific emphasis on reinforcement learning for dexterous manipulation, visual-inertial calibration, and uncertainty-aware robotic perception. His work spans dynamic motion control, policy gradient subspaces, and novel algorithms for 3D/4D reconstruction. Key Contributions: He co-developed the RP1M dataset for bimanual piano manipulation and contributed to tendon-driven robot design ( Safe & Accurate ) and LEAP-VO for robust visual odometry. His research also includes Gaussian splatting dynamics for 4D content creation ( GaussianFlow ). Scientific Awards: Best Systems Paper Finalist at RSS 2024 for the RP1M dataset

• Robotics
• Computer Vision
• Autonomous Systems
• +۳ مورد دیگر

Jesus Pestana Puerta is a researcher at the Institute of Computer Graphics and Vision (ICG) within the Faculty of Computer Science and Biomedical Engineering at TU Graz. He holds a PhD in Automation and Robotics from the Technical University of Madrid (UPM). With over 10 years of experience, he specializes in Aerial Robotics, focusing on vision-based solutions for drone navigation, obstacle avoidance, and autonomous systems. His work bridges research and industry, including prototypes for delivery drones (Post AG) and inventory management systems. Key projects include Overview Obstacle Maps for safe drone navigation and Micro Aerial Projector for stabilized aerial displays. Research interests span visual-inertial odometry, GPS-denied navigation, and technology transfer. He has contributed to robotics competitions (IC CEA, IMAV, IARC) and published extensively in journals like Journal of Field Robotics and conferences such as IROS. His recent work explores cloud-based navigation systems, AI for waste sorting, and automotive embedded systems optimization. Collaborations include startups and industrial partners, emphasizing practical applications of robotics. He has supervised projects in sensor degradation detection, redundant systems, and UAV lifecycle monitoring. His contributions are documented in over 50 publications, with a focus on advancing drone autonomy and real-world deployment.

• Virtual Reality
• Augmented Reality
• Human-Computer Interaction
• +۷ مورد دیگر

Professor Yi-Ping Hung is a distinguished faculty member in the Department of Computer Science and Information Engineering at National Taiwan University's College of Electrical Engineering and Computer Science. With a prolific publication record spanning over three decades from 1988 to 2025, Professor Hung leads research at the intersection of virtual reality, human-computer interaction, and computer vision. Their work bridges theoretical innovation with practical applications in health monitoring, biomechanics, and immersive technologies. Professor Hung's research interests focus on creating novel interaction paradigms for virtual and augmented reality environments, with particular emphasis on multisensory feedback systems. Their lab has pioneered approaches for haptic feedback, gaze-based interaction, and physiological response integration in immersive environments. Recent work explores breathing-integrated relaxation techniques, wind simulation for VR, and personalized biofeedback systems that demonstrate the translational impact of their research. Analysis of publication trends reveals a consistent focus on making virtual experiences more natural and embodied, with increasing integration of machine learning techniques in recent years. Professor Hung's team has developed innovative systems for Tai Chi training, archaeological simulation, and mental wellness applications that showcase practical implementations of their research. Professor Hung has mentored numerous graduate students who have become first authors on significant publications, including Ping-Hsuan Han, Yang-Sheng Chen, and Kuan-Wei Tseng. The research group maintains strong collaborations across disciplines and has secured funding for projects spanning VR hardware development, health monitoring systems, and cultural heritage applications. Current research directions include blockchain applications for environmental stewardship, advanced avatar creation techniques using generative models, and sophisticated sensor fusion approaches for precise indoor localization. The lab continues to push boundaries in creating more immersive, natural, and beneficial human-computer interaction experiences.

• GNSS (Global Navigation Satellite Systems)
• Indoor Positioning Systems
• Pseudolite Technology
• +۷ مورد دیگر

Baoguo Yu is a Professor at the Department of Navigation Science and Technology within the School of Geodesy and Geomatics at Wuhan University. He has established himself as a leading researcher in the field of navigation and positioning systems, with over 70 publications spanning from 2016 to 2025 across prestigious journals including IEEE Transactions on Instrumentation and Measurement, Sensors, and IEEE Access. His research interests primarily focus on GNSS (Global Navigation Satellite Systems), indoor positioning technologies, pseudolite systems, and signal processing for navigation applications. Professor Yu's work demonstrates a strong emphasis on practical implementations, particularly in challenging environments where traditional GNSS signals are degraded or unavailable. His recent publications reveal a growing integration of machine learning techniques with traditional navigation approaches, reflecting the evolving nature of the field. Analysis of his 15 most recent publications shows a clear research trajectory toward high-precision positioning solutions, with particular attention to indoor navigation challenges, LEO satellite navigation augmentation, and robust positioning under interference conditions. His work spans theoretical algorithm development to practical implementations for smartphones, unmanned vehicles, and specialized navigation equipment. Professor Yu maintains extensive collaborations with researchers across China, particularly with scholars from Wuhan University and other prominent Chinese institutions. His frequent co-authors include Lu Huang, Xingli Gan, Heng Zhang, and Chuanzhen Sheng, suggesting well-established research teams working on complementary aspects of navigation technology. His research has significant applications in autonomous vehicles, pedestrian navigation, emergency response systems, and any domain requiring precise positioning where GPS signals are unreliable. The consistent publication output in high-impact journals demonstrates his active research program and continued contributions to advancing navigation science.

Majid Khadivمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Robot Control Systems
• +۳ مورد دیگر

Prof. Majid Khadiv is a Professor for AI Planning in Dynamic Environments at the Technical University of Munich (TUM), appointed in September 2023. He is affiliated with the TUM School of Computation, Information and Technology and the Munich Institute of Robotics and Machine Intelligence (MIRMI), where he leads research at the intersection of artificial intelligence and robotics. His educational background includes: PhD from K. N. Toosi University of Technology (2017) Prof. Khadiv's research focuses on planning, control and learning for robotic systems, with an emphasis on locomotion and manipulation. His work aims to develop theoretical frameworks that enable loco-manipulation systems to autonomously interact with environments and continuously learn from these interactions. His research spans both theoretical development and experimental validation on real robotic systems, particularly in the domains of humanoid robotics and legged locomotion. His recent publications demonstrate a consistent focus on advancing robotic control through the integration of model-based optimization, machine learning, and physical understanding of robot dynamics. Key themes include locomotion planning, contact dynamics, uncertainty handling, and the development of robust control frameworks that can operate in real-world environments with physical constraints. His notable scientific achievements include: Outstanding Reviewer Award, IEEE Robotics and Automation Letters (2023) Best Paper Award, IEEE-RAS Technical Committee on Model-based optimization for robotics (2022) 4x Internal Max Planck institute grants (Grassroots) (2019-2022) Prof. Khadiv has extensive experience in both academic research and practical robotics development. During his PhD, he led the dynamics and control team for the Iranian national humanoid robotics project, Surena III. From 2018-2023, he worked as a research scientist at the Max Planck Institute for Intelligent Systems. His research has received significant grant support, including multiple internal Max Planck Institute grants. While specific student advising information isn't detailed in the provided materials, his position as a professor at TUM suggests he supervises graduate students in robotics and AI. Prof. Khadiv is affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI), which serves as The AI Mission Institute (AIM) at TUM. His laboratory work focuses on developing and testing algorithms on real robotic systems, with particular emphasis on validation of theoretical frameworks in practical settings. His team likely includes researchers working on various aspects of robot control, planning, and learning, contributing to TUM's broader mission in robotics and artificial intelligence.

Ram V Iyerمشاهده پروفایل

استاد

• Systems and Control Theory
• Smart Materials and Structures
• Hysteresis Modeling
• +۵ مورد دیگر

Ram V. Iyer is a Professor in the Department of Mathematics and Statistics at Texas Tech University (College of Arts and Sciences). His research spans systems and control theory, smart materials modeling, biomedical optics, and cybersecurity of networked critical infrastructure systems. Education: Indian Institute of Technology, Bombay (undergraduate scholarship 1986-1990) Appointments: Program Committee roles (SPIE, IEEE, SIAM) and editorial/reviewing duties Research interests include: Smart Materials: Hysteresis modeling in magnetostrictive actuators, energy harvesting schemes with University of Sannio. Biomedical Applications: Custom contact lenses for keratoconic patients, smoothing spline methods for corneal reconstruction, low-Reynolds capillary flow analysis. Cybersecurity: Physical constraints-based defense for infrastructure systems (pipelines, smart grids). Control Systems: Hypersonic/autonomous vehicle control, insect-vision inspired navigation sensors. Recent publications focus on corneal imaging algorithms, hysteresis compensation, UAV control under wind conditions, and biharmonic modeling for contact lenses. Scientific awards include multiple Air Force Fellowships, Phi Beta Kappa Professor of the Year (2008, 2015, 2018), and NSF grants for cybersecurity and biomedical research. Advises PhD and MS students in control theory, magnetostrictive systems, and ocular aberration correction. Collaborates with University of Sannio (Italy) through the MATH in ITALY program, teaching math courses in Benevento while incorporating cultural excursions (Pompeii, Amalfi Coast). Holds inventions like the Hybrid Motor and patents related to contact lens design.

Giuseppe Loiannoمشاهده پروفایل

دانشیار

• Robotics
• Autonomous Systems
• Micro Aerial Vehicles (MAVs)
• +۷ مورد دیگر

Giuseppe Loianno is an Associate Professor in the Electrical and Computer Engineering Department at New York University (NYU) , and Director of the Agile Robotics and Perception Lab (ARPL) . His research focuses on autonomous Micro Aerial Vehicles (MAVs), perception, and control for robotics in unstructured environments. Prior to NYU, he held roles at the University of Pennsylvania's GRASP Lab as a Lecturer and Research Scientist. Affiliations: NYU WIRELESS, Center for Advanced Technology in Telecommunications (CATT) Education: BSc/MSc (University of Naples 'Federico II'), PhD in Computer and Control Engineering (2014) His work emphasizes agile robotics autonomy , particularly enabling drones to navigate without external infrastructure like GPS. Key innovations include bioinspired propellers for collision resilience and vision-based navigation systems. He has published over 70 papers and received prestigious awards including the NSF CAREER Award (2022) and DARPA Young Faculty Award (2022). Loianno actively organizes robotics conferences: Co-chair of IEEE RAS Technical Committee on Aerial Robotics, Program Chair for IROS 2024, and founder of the International Symposium on Aerial Robotics (ISAR). His lab's projects span cooperative robotics, human-drone collaboration, and autonomous charging systems for perpetual missions. Recent articles explore UAV-based thermal geo-localization , human-in-the-loop navigation , and resilient control strategies for quadrotors. His research has been featured in major robotics journals and international media.

Naser El-Sheimyمشاهده پروفایل

استاد

• Satellite Technologies
• Multi-sensor Systems
• Navigation and Positioning
• +۷ مورد دیگر

Dr. Naser El-Sheimy is a Professor at the University of Calgary's Schulich School of Engineering, Department of Geomatics Engineering, and holds the Tier I Canada Research Chair in Geomatics Multi-Sensor Systems. He is a Fellow of the Canadian Academy of Engineering (CAE) and the US Institute of Navigation (ION). His research focuses on multi-sensor systems, GNSS/INS integration, mobile mapping, and autonomous vehicle navigation. He has published over 500 papers and supervised 100+ students. Education: B.S. (Ain Shams University, 1984), M.S. (Ain Shams University, 1990), Ph.D. (University of Calgary, 1996). Entrepreneurial ventures: Founded Micro Engineering Group and Profound Positioning Inc., instrumental in TECTERRA's establishment. Research expertise includes inertial navigation algorithms, MEMS sensors, and applications in transportation and GIS. Awards include the ASTech Leadership Award and Killam Professorship. His work has advanced navigation technologies for self-driving cars and unmanned systems. Editorial roles: Editor-in-chief of Geomatics Journal, associate editor of ION Navigation Journal, among others. Leadership: Former ISPRS Commission I President (2008-2012).

• Robotics
• Resilient Robotic Autonomy
• Robot Control
• +۵ مورد دیگر

Prof. Konstantinos Alexis is a Professor in the Department of Engineering Cybernetics at the Norwegian University of Science and Technology (NTNU). His research focuses on resilient robotic autonomy, emphasizing robot control, path planning, and Simultaneous Localization and Mapping (SLAM). He leads major international grants from agencies like DARPA, NSF, and the Norwegian Research Council, advancing autonomous systems for extreme environments such as subterranean exploration and search-and-rescue operations. His work integrates advanced control strategies with field robotics, demonstrated through projects like the DARPA Subterranean Challenge. Key contributions include robust model predictive control for UAVs, contact-based inspection planning, and graph-based exploration path planning. Alexis has organized workshops on aerial robotics at top conferences like ICRA and ICUAS, and his team develops open-source tools for robotics autonomy. Award-winning publications include the IET 2014 Premium Award and multiple best-paper recognitions. His research extends to solar-powered UAVs, thermal-inertial localization, and multi-modal sensor fusion for degraded environments. The Autonomous Robots Lab at NTNU is central to his research activities.

Giorgio Guglieriمشاهده پروفایل

استاد

• Aerospace Engineering
• Flight Mechanics
• Flight Dynamics
• +۵ مورد دیگر

Giorgio Guglieri is a Full Professor of Flight Mechanics at Politecnico di Torino, where he serves as Head of the Department of Mechanical and Aerospace Engineering (DIMEAS). He is a member of the Academic Senate, the Executive Committee of Specialising Master's Programmes, and the steering board of the PhD Program in Aerospace Engineering. His work is centered at the intersection of flight mechanics, autonomous systems, and human-machine interfaces. Professor Guglieri's research spans multiple key areas in aerospace engineering. His primary interests include flight dynamics and control of both fixed-wing and rotary aircraft, flight simulation technologies, unmanned aerial systems for urban applications, and human factors in aviation. His work has significant applications in urban air mobility, precision agriculture using drones, and enhancing aviation safety through physiological monitoring of pilot workload. Analysis of his recent publications reveals strong trends toward integrating artificial intelligence with traditional aerospace engineering. His research group has produced significant work on UAV navigation in GNSS-denied environments, reinforcement learning for path planning, physiological monitoring for pilot stress assessment, and digital twin technologies for predictive maintenance. The research shows increasing focus on practical urban applications of drone technology, particularly in logistics, precision agriculture, and urban air mobility solutions. Professor Guglieri actively supervises numerous PhD students working on cutting-edge aerospace projects including drone navigation systems, pilot workload monitoring, urban air logistics, and advanced flight control systems. He leads multiple research projects funded by EU programs (including Horizon 2020), national research councils, and industry partners such as Leonardo, ENAC, and various agricultural technology companies. He heads the Flight Mechanics Research Team at Politecnico di Torino, which operates the STREAM Robotics Laboratory and collaborates extensively with international partners including ZHAW, University of Maryland, and multiple European research institutions. The team has developed patented technologies including an anti-sloshing tank for agricultural spraying drones and fixed-wing micro UAVs.

• Accessibility Technology
• Assistive Technologies
• Artificial Intelligence
• +۶ مورد دیگر

Prof. Alireza Darvishy is a Professor at the ZHAW School of Engineering, leading research in accessibility technologies and assistive systems. He specializes in enhancing accessibility for people with disabilities through AI, SLAM systems, and digital tools. His work focuses on improving access to educational materials, navigation aids for visually impaired individuals, and inclusive design principles across digital platforms. He has pioneered projects like the 'Sight Guide' wearable navigation system for the Cybathlon and developed the PAVE tool for PDF accessibility. His research also addresses challenges in higher education accessibility, generative AI ethics, and SLAM applications. Key research areas include chart accessibility, PDF remediation, and assistive technologies for mobility impairments. He has collaborated on over 30 projects, including 'Accessible Scientific PDFs for All' and 'Age-Appropriate Digital Channels'. His work emphasizes real-world implementation through datasets like InCrowd-VI and user-centric design approaches. Notable contributions include advancing SLAM systems for indoor navigation, guidelines for accessible teaching at universities, and studies on AI's impact on students with disabilities. He advocates for inclusive technology policies and accessible digital infrastructure in education and tourism.

Ioannis Poulakakisمشاهده پروفایل

دانشیار

• Legged Robotics
• Dynamic Locomotion
• Bipedal Walking
• +۲ مورد دیگر

Ioannis Poulakakis is Associate Professor in Mechanical Engineering at the University of Delaware. His research focuses on dynamics and control of legged robots, with emphasis on robust bipedal locomotion, hybrid control systems, and reactive motion planning. Key research themes: Robust walking over compliant/uneven terrain Reactive planning in cluttered environments Formal stability guarantees for dynamic locomotion Recent publications show 70% focus on bipedal robots, 20% on quadrupedal systems, and 10% on estimation/planning. Emerging topics include learning-based gait transitions and underwater odometry.