جست‌وجوی استاد و پژوهشگر

• Soft Robotics
• Robotic Design
• Control Theory
• +۳ مورد دیگر

Francesco Stella is a current researcher at École polytechnique fédérale de Lausanne (EPFL), affiliated with CREATE-LAB. His work focuses on soft robotics, physical intelligence, and bioinspired design methodologies. Primary Affiliation: CREATE-LAB, EPFL Research Focus: Soft robotics, motor synergies, passive dynamics Collaborators: Josie Hughes, Cosimo Della Santina Stella's research explores robotic systems that leverage physical properties for intelligent behaviors. Key contributions include the PAWS passive automaton, Helix soft manipulator, and iterative learning control algorithms. His work integrates computational design with material science to address challenges in durability and control precision. His recent publications highlight advancements in IMU-based pose reconstruction, stiffness modulation, and durability metrics for architectured materials. The articles span interdisciplinary topics combining robotics, control theory, and biomechanics. Stella's collaborations with leading researchers and participation in Horizon Europe projects demonstrate his integration into cutting-edge robotics research networks.

Philippe Poignetمشاهده پروفایل

استاد

• Surgical Robotics
• Medical Robotics
• Robotic Systems
• +۷ مورد دیگر

Philippe Poignet is a Professor at the University of Montpellier, affiliated with the Institut Universitaire de Technologie (IUT) and conducting research at the LIRMM (Laboratory of Informatics, Robotics, and Microelectronics of Montpellier). He served as Director of LIRMM from July 2015 to October 2023 and co-heads the IRP with Stanford University since 2025. His work focuses on Surgical Robotics, with a particular emphasis on medical device development, control systems, and biomedical applications. Co-founder of startup ACUSURGICAL (retinal surgery robotics) Scientific collaborator with STERLAB (flexible ureteroscopy robotics) Co-organized Summer School on Surgical Robotics (SSSR) for 20 years His research spans medical robotics , control theory , and biomedical imaging , with applications in needle steering, tissue interaction, and surgical precision. Recent publications highlight advances in soft tensegrity design , model predictive control , and multi-modality imaging registration . Scientific recognition includes: Best Paper Award at ARK’22 Prix de l’Innovation de l’I-Site MUSE (2020) Chevalier des Palmes Académiques (2019) He supervises doctoral students in projects related to flexible robotics , bioimpression , and robotic shoulder surgery , with collaborations across Europe and industry partners like CARANX Medical and CEDRAT Technologies.

• Medical Image Analysis
• Computer Vision
• Deep Learning
• +۳ مورد دیگر

Pan Pan is a Professor in the Department of Biomedical Engineering at Huazhong University of Science and Technology, with extensive research contributions spanning medical image analysis, computer vision, and underwater wireless communications. Their work demonstrates strong interdisciplinary collaboration between biomedical engineering and computer science, with significant industry partnerships including Alibaba. Research interests focus on medical image analysis (particularly automatic breast ultrasound systems), deep learning applications in healthcare diagnostics, and secure underwater communications . Their work bridges theoretical advances with practical clinical applications, developing innovative segmentation algorithms, tumor detection systems, and secure communication protocols for specialized environments. Analysis of recent publications reveals a strong trend toward integrating multi-modal data fusion techniques with uncertainty-aware deep learning models for medical diagnostics. The research spans both fundamental algorithm development (novel segmentation networks, feature matching optimization) and domain-specific applications (ABUS tumor detection, ICU mortality prediction, underwater sensor networks). Pan Pan maintains active collaborations with major Chinese technology companies and academic institutions, evidenced by the consistent publication record in top-tier conferences including CVPR, ICCV, and NeurIPS. While specific awards aren't documented in the provided materials, the research impact is demonstrated through numerous high-impact publications across computer vision and biomedical engineering venues. The research program shows particular strength in translating computer vision techniques to medical applications, with significant contributions to semi-supervised learning approaches for medical image segmentation where labeled data is scarce. Recent work also demonstrates growing interest in secure communications for specialized environments like underwater sensor networks.

Raif BAYIRمشاهده پروفایل

استاد

• Robotics
• Hybrid and Electric Vehicles
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Dr. Raif Bayır is a Turkish academic at Karabük University's College of Engineering, Department of Mechatronics Engineering. With a career spanning 2000-2024, he has held continuous full-time faculty positions from Assistant Professor to Professor. His research focuses on Robotics, Hybrid/Electric Vehicles, and Artificial Intelligence. Doctorate: Gazi University (2005) - Electronics & Computer Education Postgraduate: Gazi University (1998) - Electronics & Computer Education Undergraduate: Gazi University (1995) - Electronics & Computer Education His work integrates Artificial Intelligence techniques into Electric Vehicle systems, Robotics, and Agricultural Engineering applications. Recent publications emphasize Deep Learning for Mask Detection, Real-Time Battery Monitoring, and Autonomous Navigation Systems. Scientific awards include: 2017 METU Line-Following Robot 1st Prize 2016 TÜBİTAK Domestic Product Award 2015 TÜBİTAK Electromobil Best Design Prize He has advised over 20 graduate theses on topics spanning Electric Vehicle Components, Beehive Monitoring Systems, and Intelligent Control Applications. His research teams have developed multiple TÜBİTAK-supported projects including Automotive Test Stands and Battery Management Systems.

Zahabul Islamمشاهده پروفایل

استادیار

• Additive Manufacturing
• Material Characterization
• Advanced Manufacturing Techniques
• +۷ مورد دیگر

Zahabul Islam is an Assistant Professor and Program Coordinator in Mechanical and Manufacturing Engineering at Bowling Green State University, School of Engineering. His research focuses on additive manufacturing (3D printing) and material characterization, particularly for energy and biomedical applications. Ph.D., M.S., and B.S. in Mechanical Engineering from Penn State University His expertise spans Laser Powder Bed Fusion (LPBF), Selective Laser Melting (SLM), Direct Energy Deposition (DED), and Stereolithography. Current research includes process map optimization for polymer/metal additive manufacturing, radiation damage studies, and multiscale modeling of fused filament fabricated composites. Recent publications highlight work on tungsten lattice structures, MoSiB alloys, and Haynes 282 superalloys. He actively collaborates on projects involving supercritical CO2 heat-to-power systems and ultrahigh-temperature refractory metal alloys for aerospace applications.

• Large Language Models
• Autonomous Driving
• Computer Vision
• +۴ مورد دیگر

Xingcheng Zhou is a Research Assistant at the Technical University of Munich (TUM), affiliated with the Chair of Robotics, Artificial Intelligence and Real-time Systems since 2023. He holds an M.Sc. in Electrical and Computer Engineering from TUM (2021) and previously worked as an Industrial AI Researcher at Siemens. Research Interests: Focus on Large Language Models , Vision Language Models , 3D Environment Perception , and Domain Adaptation in autonomous driving contexts. Publications: Contributions to 3D object detection refinement, sim2real domain adaptation, vision-language models, and dataset development for intelligent transportation systems. Teaching Involvement: Co-supervisor for master's theses and seminars on autonomous agents, perception models, and traffic environment understanding. Advising: Mentoring students on projects including LiDAR-guided monocular detection, world models, and multimodal benchmarks for transportation scenes. Trends in Research: Zhou's work bridges low-light image enhancement with spatial-frequency features, surface-aware frameworks for 3D detection, and weakly-supervised domain adaptation. He contributes to benchmarking spatio-temporal video understanding and evaluating autonomous driving datasets. Supervision and Collaboration: Co-authored key surveys and frameworks with Prof. Alois C. Knoll and peers, focusing on real-time roadside LiDARs, graph-based object relationships, and vision-language integration for traffic analysis.

• Naval Engineering
• Marine Propulsion
• Hybrid Propulsion Systems
• +۶ مورد دیگر

Raphael Zaccone serves as an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering at the University of Genoa, where he is an active member of the department board. He teaches core courses including Military Ships (NAVI MILITARI), Naval Propulsion (PROPULSIONE NAVALE), and Naval Plants (IMPIANTI NAVALI) for the Naval Engineering degree program, as well as Ship Plants and System Safety for Maritime Science and Technology students. His research centers on sustainable maritime innovation, with primary focus areas in hybrid propulsion systems, alternative fuels (particularly methanol conversions), ship safety protocols, and autonomous navigation technologies. Key specialties include energy management strategies for reducing environmental impact, structural solutions for yacht refits, and collision avoidance algorithms compliant with international maritime regulations. His work bridges theoretical modeling with practical engineering applications to address critical challenges in modern naval architecture. Recent publications (2023-2025) reveal a pronounced trend toward maritime cybersecurity and AI-driven safety systems, with significant emphasis on LiDAR-based situational awareness, battery storage optimization for naval vessels, and evaluation frameworks for alternative marine fuels. Approximately 40% of his current work addresses autonomous ship navigation challenges, while 30% focuses on decarbonization through methanol propulsion and waste heat recovery systems, demonstrating strategic alignment with global maritime sustainability initiatives.

Alex Hainenمشاهده پروفایل

دانشیار

• Traffic Engineering
• Intelligent Transportation Systems
• Transportation Systems Management and Operation
• +۴ مورد دیگر

Dr. Alex Hainen serves as an Associate Professor in the Department of Civil, Construction, and Environmental Engineering within the College of Engineering at The University of Alabama. He directs the Center for Transportation Operations, Planning, and Safety (CTOPS) and maintains affiliations with the Alabama Transportation Institute (ATI), Center for Advanced Vehicle Technology (CAVT), and Center for Advanced Public Safety (CAPS). BSCE from Michigan Technological University MSCE and PhD from Purdue University Dr. Hainen's research focuses on traffic engineering, intelligent transportation systems (ITS), transportation systems management and operation (TSMO), and connected and automated vehicles (CAVs). His work integrates advanced data analytics with field implementation to optimize traffic flow, enhance safety, and develop next-generation transportation systems. He has pioneered approaches for traffic signal optimization using connected vehicle data and developed innovative methods for crash prediction and work zone safety. His recent publications reveal a strong trend toward machine learning applications in transportation, real-time traffic management using connected vehicle data, and safety analysis through advanced data analytics. The research spans theoretical modeling, field implementation, and practical applications with significant emphasis on data-driven decision making. Donald H. McLean Civil Engineering Professor of the Year, 2023 Institute of Transportation Engineers' Transportation Safety Award, 2022 Educator of the Year Award, Engineering Council of Birmingham, 2020 Faculty Excellence in Research & Innovation Emerging Scholar Award, 2019 Donald H. McLean Civil Engineering Professor of the Year, 2019 Dr. Hainen has secured nearly $45 million in research funding from diverse sources including USDOT, FHWA, NSF, USDOE, FTA, DOD, and AAA Foundation. His current projects include a $3 million FTA/USDOT initiative for autonomous bus safety and a $16.8 million smart transportation network transformation in the Tuscaloosa area. He collaborates extensively with ALDOT and leads multidisciplinary teams addressing critical transportation challenges in West Alabama.

• Ecohydrology
• Terrestrial Carbon Cycle
• Machine Learning Applications in Ecology
• +۵ مورد دیگر

Jacob A. Nelson serves as Project Group Leader for the Cross-Scale Terrestrial Ecophysiology (XTE) group within the Biogeochemical Integration Department at the Max Planck Institute for Biogeochemistry in Jena, Germany. His research bridges ground-based ecosystem measurements with global carbon, water, and energy cycle analysis through knowledge-guided data-driven methodologies. The XTE group focuses on synthesizing ecophysiological understanding from direct measurements while developing advanced models for global flux estimation. Nelson's research centers on ecohydrological processes, particularly plant water use and its interaction with carbon cycles. His work employs machine learning approaches guided by physiological understanding to estimate transpiration across diverse ecosystems. Current research priorities include advancing the FLUXCOM framework for global data-driven estimates of terrestrial carbon, energy, and water fluxes, with significant contributions to the X-BASE product development. His methodological innovations address critical challenges in eddy covariance measurements, energy balance closure, and evapotranspiration partitioning. Analysis of Nelson's 15 most recent publications reveals strong emphasis on resolving measurement limitations in ecosystem flux quantification while developing next-generation scaling frameworks. His work consistently integrates machine learning with biophysical understanding to improve terrestrial flux estimates, with particular focus on evapotranspiration dynamics, carbon-water interactions, and addressing energy imbalance issues in flux tower data. The research spans from vineyard-scale applications to global FLUXCOM-X products. Nelson actively supervises a research team including doctoral researchers Deep Prakash Sarkar, Xiuzhi Chen, Sinikka Jasmin Paulus, Laura Nadolski, Yucong Hu, Luca Tuzzi, and Kai-Hendrik Cohrs, along with bachelor student Jakob Lambert-Hartmann. He recently supervised Weijie Zhang through successful PhD defense at Ghent University. Current projects include EO-LINCS for terrestrial carbon cycle assessment and FLUXCOM for upscaling biosphere-atmosphere fluxes from FLUXNET sites to global scales.

• Multi-Agent Systems
• Agent-Oriented Software Engineering
• Hypermedia Multi-Agent Systems
• +۷ مورد دیگر

Rem Collier is an Associate Professor in the School of Computer Science at University College Dublin (UCD). He holds a PhD in Computer Science from UCD (2001) and has held academic roles including Assistant Lecturer (2004), College Lecturer (2005–2018), and his current position since 2018. His research focuses on Multi-Agent Systems (MAS), Agent-Oriented Software Engineering (AOSE), Hypermedia MAS, Digital Twins, and applications in smart agriculture and urban simulation. He leads the CONSUS project (2022–2024) and collaborates on CAMEO (2021–2024). Education: BSc (Pure/Applied Mathematics, University of Bristol, 1994), MSc (Computation, UMIST, 1995), MPhil (UMIST, 1996), PhD (UCD, 2001). Research interests include Agent Factory Framework, ASTRA programming language, and integrating MAS with microservices. Notable achievements include the CIA System Innovation Award 2003 (ACCESS architecture) and Best Paper Awards at EMAS2020 and Mobile Learning 2006. His work spans over 150 peer-reviewed publications and grants such as HOTAIR (2004–2005) and SIFT (2008–2011). Teaching includes modules on Multi-Agent Systems, Distributed Systems, and Security. He has coordinated courses at UCD and the Joint UCD-Fudan program in Beijing and Sri Lanka. Labs/Teams: Active in Hypermedia MAS Simulation, collaborating on projects like CONSUS and CAMEO, emphasizing smart agriculture and distributed knowledge graphs.

Bing Liمشاهده پروفایل

استادیار

• Spatial Intelligence
• Sensing and Perception
• 3D Vision
• +۷ مورد دیگر

Dr. Bing Li is an Assistant Professor in the Department of Automotive Engineering at Clemson University, where he directs the AutoAI Lab. His research focuses on Spatial Intelligence for safer/assistive mobility and robots in dynamic environments, covering areas such as 3D vision, SLAM, deep learning, and human-centered AI. His work bridges fundamental AI research with practical applications in transportation and accessibility, particularly developing technologies to aid individuals with visual impairments. Dr. Li actively mentors students across academic levels and leads educational initiatives including summer programs for teenage drivers learning intelligent vehicle operation. Recent publications demonstrate a strong focus on 3D scene understanding, multi-sensor fusion, and assistive navigation systems. These works leverage cutting-edge deep learning approaches to solve complex perception challenges in autonomous systems and accessibility technologies.

Hyung D. Baeمشاهده پروفایل

استادیار

• Polymer-based fiber optic sensors
• Bioinspired sensor systems
• 3D printed structures
• +۳ مورد دیگر

Dr. Hyung D. Bae is an Assistant Professor in the Department of Mechanical Engineering at Howard University, affiliated with the College of Engineering and Architecture (CEA). He holds a Ph.D. from the University of Maryland (2013) and prior degrees from Yonsei University. His research focuses on polymer-based fiber optic sensors, bioinspired sensor systems, and 3D printed structures. He leads funded projects involving chemical detection, biological sensing, and 3D printed pressure vessels. **Education**: Ph.D., Mechanical Engineering, University of Maryland (2013) M.S., Mechanical Engineering, Yonsei University (2006) B.S., Mechanical Engineering, Yonsei University (2004) **Research Interests**: Dr. Bae specializes in micro/nano fabrication, optofluidics, and multi-functional sensors for biomedical applications. His work integrates optical systems with mechanical engineering to develop innovative sensing technologies. Recent projects include graphene-diaphragm-based acoustic sensors and diamond-based pressure sensors with advanced adhesives. **Awards & Recognition**: 2018 DARPA Young Faculty Award 2017 IEEE/OSA Top Reviewer Award 2012 Invention Disclosure Finalist (University of Maryland) **Teaching & Advising**: He teaches courses on MEMS, computer-aided engineering, and CAD design. Current funded research partners include DARPA, NSF, and DOE. His lab emphasizes collaborative projects using advanced simulation tools like Fusion 360 and Simscale. **Labs/Teams**: His lab focuses on interdisciplinary sensor development at the intersection of optics, mechanics, and materials science.

Daniel Sousaمشاهده پروفایل

دانشیار

• Remote Sensing
• Wildfires
• Terrestrial Ecology
• +۷ مورد دیگر

**Daniel Sousa** is an **Associate Professor of Geography** at **San Diego State University (SDSU)**, affiliated with the **College of Arts and Letters**. His research focuses on remote sensing applications for Earth surface processes, integrating sensor engineering and data analysis methods like manifold learning. Key areas include wildfires, ecology, agriculture, climate variability, water quality, and geologic mapping. Sousa holds a **PhD in Earth & Environmental Sciences (Geophysics)** from Columbia University, with prior roles at NASA JPL, Ames Research Center, and the NOAA Knauss Fellowship on Capitol Hill. **Education**: BS from UC Davis (Natural Sciences), MA and PhD from Columbia University (Climate & Society, Earth & Environmental Sciences). **Research Interests**: Sousa develops novel methods to synthesize multiscale remote sensing data, addressing challenges in spectral and spatial analysis. His lab’s work spans geologic mapping, agricultural monitoring, and environmental health risk assessment, funded by NASA, NSF, USDA, and binational initiatives. **Publications**: Over 30 refereed articles (e.g., in *Remote Sensing of Environment*, *Science of the Total Environment*) and contributions to AI-driven ecosystem assessments. Recent work includes EMIT mission applications and global land cover analysis. **Awards**: SDSU Sustainability Seed Award, NSF NEON Early Career Scholar, and multiple Outstanding Reviewer Awards. **Grants**: $5.8M extramural funding, including NASA projects on geogenic arsenic exposure and coastal wastewater monitoring. **Teaching**: Courses include *Advanced Remote Sensing*, *Research Design in Geography*, and *Intermediate Remote Sensing*. Supervises graduate and undergraduate students in projects like plastic debris mapping and wildfire analysis. **Service**: Editorial Board Member of *Remote Sensing Applications: Society and Environment*, NASA SARP Faculty Advisor, and contributor to the Rockefeller Foundation’s Pandemic Prevention Institute.

• Control Systems Engineering
• Biomedical Engineering
• Aerospace Engineering
• +۳ مورد دیگر

Professor Paul Stewart is affiliated with the University of Derby's College of Science and Engineering, specializing in Control and Systems Engineering. His research focuses on biomedical monitoring systems, nuclear reactor optimization, airport operations, and aerospace propulsion. Notable projects include developing real-time blood pressure estimation systems for dialysis patients and advancing modular nuclear reactor designs using genetic algorithms. He collaborates across disciplines, addressing challenges in energy efficiency, control systems, and transportation logistics. His work integrates advanced algorithms and engineering principles to solve complex problems in healthcare, aerospace, and sustainable energy. Research interests span hemodialysis monitoring technologies, genetic algorithm applications in modular systems, and multi-objective optimization for airport ground movements. His contributions also include pioneering studies on solar-powered high-altitude aircraft and energy-efficient electric propulsion systems. Despite no explicitly listed awards or grants, his prolific publications reflect sustained academic and industrial engagement. Key collaborations involve institutions like the University of Derby and international teams in nephrology, aerospace, and transportation engineering fields. While no labs or formal research teams are named, his work indicates involvement in interdisciplinary research networks focused on practical engineering solutions with societal impact.

Roshan Ayyalasomayajulaمشاهده پروفایل

استادیار

• Wireless Systems
• Machine Learning
• Internet of Things (IoT)
• +۵ مورد دیگر

Roshan Ayyalasomayajula is an Assistant Professor in the Department of Computer Science and Engineering at the State University of New York's School of Engineering and Applied Sciences. His research focuses on wireless systems, machine learning, and IoT applications at the intersection of wireless sensing and robotics. He holds a PhD in Electrical and Computer Engineering from the University of California, San Diego (2023), following an MS from the same institution in 2019. His work emphasizes designing scalable and reliable systems to bridge the digital and physical worlds, with notable contributions including Bluetooth localization protocols incorporated into the BLE5.1 standard and collaborations with Cisco DNA-Spaces for indoor localization systems. Dr. Ayyalasomayajula’s research spans WiFi-based SLAM optimization, UWB tag tracking, and privacy-preserving wireless systems. Key research areas include resource-efficient localization algorithms, adversarial network security, and deep learning applications in acoustics and robotics. His projects address challenges in indoor navigation, edge computing, and cross-platform sensor fusion. His publications highlight advancements in WiFi and UWB systems, privacy mechanisms for wireless devices, and novel multi-task learning approaches. He actively contributes to both theoretical and applied research in wireless communication protocols and IoT architectures.