جست‌وجوی استاد و پژوهشگر

Puren Ouyangمشاهده پروفایل

دانشیار

• Robotics and Control
• Mechatronics
• Integrated Design and Control
• +۱ مورد دیگر

Dr. Puren Ouyang serves as an Associate Professor in the Department of Aerospace Engineering at Toronto Metropolitan University, where he holds a Professional Engineering license (PEng). His academic foundation includes a BASc from Huazhong University of Science and Technology (1985), followed by MSc and PhD degrees from the University of Saskatchewan (2002, 2005). He teaches core courses including AER 509 Control Systems, AER 520 Stress Analysis, and AE 8141 Advanced Aerospace Manufacturing. His educational credentials: PhD in Engineering, University of Saskatchewan (2005) MSc in Engineering, University of Saskatchewan (2002) BASc in Engineering, Huazhong University of Science and Technology (1985) Ouyang pioneered position domain control methodology, replacing traditional time/frequency references with position-based systems to enhance robotic precision in contour tracking. His research directly addresses industrial manufacturing challenges where 24/7 machine reliability determines product accuracy. Key focus areas include robotic control systems, mechatronics integration, hybrid system dynamics, and synchronized multi-DOF manipulation for CNC applications. His 2013-2016 publications reveal consistent innovation in position-domain robotics control, with emphasis on contour tracking algorithms, multi-axis synchronization, and adaptive learning techniques. These works bridge theoretical control frameworks with industrial manufacturing applications, frequently targeting CNC machine optimization where 80% of North American factories rely on automated systems. Key recognitions: Best Conference Paper in Integration Award at IEEE ICIA 2011 NSERC Postdoctoral Fellowship (2005-2007) As an active supervisor, Ouyang mentors graduate students in robotics and control systems through the ISRMM Laboratory. His NSERC fellowship demonstrates sustained research capability, while his industry-focused publications suggest ongoing grant activity in advanced manufacturing automation. Current supervision availability indicates active research program development. The Intelligent Systems & Robotics / Micro Manufacturing (ISRMM) Laboratory serves as his primary research hub, driving innovations in robotic precision manufacturing, micro-scale production systems, and real-time control architectures for industrial applications.

Abolfazl Simorghمشاهده پروفایل

پژوهشگر

• Aircraft Trajectory Optimization
• Climate Change Mitigation in Aviation
• Robust Control
• +۳ مورد دیگر

Abolfazl Simorgh is a researcher at Charles III University of Madrid's Department of Aerospace Engineering, specializing in climate-optimized aviation systems. His work bridges mathematical control theory with practical climate impact mitigation, focusing on robust trajectory optimization under environmental and operational uncertainties. He leads development of open-source tools for sustainable flight planning while contributing to major European aviation initiatives. Education: B.Sc. in Control Engineering (2017) M.Sc. in Control Engineering (2020) Ph.D. in Aerospace Engineering from Charles III University of Madrid Dr. Simorgh's research centers on developing mathematical frameworks that reconcile aircraft trajectory optimization with climate impact reduction. His expertise spans robust control systems, optimization under uncertainty, and climate modeling integration, with particular emphasis on non-CO₂ emissions. His methodology addresses both CO₂ and non-CO₂ climate forcing mechanisms through computationally efficient algorithms that account for weather variability and climate metric uncertainties. This work directly supports aviation's decarbonization by providing operational strategies that reduce environmental footprint without prohibitive cost increases. Analysis of his 15 most recent publications reveals a cohesive research trajectory focused on operationalizing climate-optimal flight planning. His work consistently integrates climate science with aerospace engineering through robust optimization frameworks, demonstrating particular innovation in handling multiple uncertainty sources (weather, climate models, emissions). The publications cluster around three interconnected themes: 1) Development of open-source computational tools (ROOST, CLIMaCCF), 2) Network-scale implementation of climate-aware air traffic management, and 3) Risk analysis of climate mitigation strategies. This body of work establishes new methodological standards for quantifying and minimizing aviation's total climate impact. Scientific Awards: Luis Azcárraga Aeronautical Innovation Award for collaborative research impact Best Paper Award (2022) from a high-impact aerospace journal Dr. Simorgh secures significant research funding through European Commission projects including FlyATM4E (climate-optimized flight planning), ALARM (aviation emissions reduction), and RefMAP (sustainable aviation pathways). His grant portfolio emphasizes practical implementation of climate mitigation strategies, with strong industry-academia collaboration. He mentors junior researchers through project teams and has developed three major open-source Python libraries (CLIMaCCF, ROOST, ROC) that have become community standards for climate impact assessment in aviation research. His current work focuses on scaling climate-optimized trajectories to continental airspace while addressing operational constraints and economic viability. He leads a research group focused on climate-aware air traffic management, developing the ROOST simulation framework for GPU-accelerated trajectory optimization and the CLIMaCCF library for standardized climate metric calculations. His team collaborates with European air navigation service providers and aircraft manufacturers to transition research into operational practice, with current projects emphasizing real-time implementation and regulatory compliance frameworks.

Philip Damesمشاهده پروفایل

دانشیار

• Robotics
• Probabilistic Robotics
• Multi-Robot Systems
• +۷ مورد دیگر

Philip Dames is an Associate Professor in the Department of Mechanical Engineering at the College of Engineering, Temple University, where he leads the Temple Robotics and Artificial Intelligence Lab (TRAIL). His research focuses on enabling robots to operate effectively in complex, real-world environments to meet societal needs. Research Interests: His work spans robotics, probabilistic reasoning, multi-robot systems, active sensing, mapping, and target tracking. He develops algorithms for distributed coordination, uncertainty-aware navigation, and semantic perception, with applications in autonomous systems and human-robot interaction. Publication Trends: His recent publications (2020–2025) appear in top robotics journals like IEEE Transactions on Robotics and Autonomous Robots . The research emphasizes probabilistic methods, deep reinforcement learning, large language models for planning, and real-time navigation in dynamic and uncertain environments, reflecting a strong trend toward intelligent, adaptive robotic systems. Scientific Awards: NSF CAREER Award Advising and Grants: While specific advisees are not listed, he leads a research lab and has secured competitive funding such as the NSF CAREER award. He mentors students through research in robotics and advises on projects related to autonomous navigation and multi-robot systems. Labs and Teams: He directs the Temple Robotics and Artificial Intelligence Lab (TRAIL), which focuses on developing advanced robotic capabilities through collaborative, interdisciplinary research in perception, planning, and control.

• Robotics Perception
• Alternative Sensing
• Inertial Fusion
• +۶ مورد دیگر

Teresa Vidal-Calleja is an Associate Professor and Research Director at the Robotics Institute, University of Technology Sydney (UTS). She holds a Deputy Head of School (Research) role in the School of Mechanical and Mechatronic Engineering. Her research focuses on robotics perception, alternative sensing, inertial fusion, SLAM, and applications in manufacturing, agriculture, mining, and construction. Education: B.Sc. Mechanical Engineering (UNAM, 2000), M.Sc. Electrical Engineering (CINVESTAV-IPN, 2002), Ph.D. Automatic Control (Polytechnic University of Catalonia, 2007). Postdoctoral Experience: LAAS-CNRS (France), Australian Centre for Field Robotics (Sydney). Research Interests: Teresa’s work spans robotics perception, sensor fusion, autonomous navigation, and collaborative robotics. She leads projects on next-gen infrastructure robotics (ARC Discovery Grant) and is co-lead of the Australian Cobot Centre. Her innovations target hazardous environments, infrastructure maintenance, and human-robot collaboration. Funded Research: Includes grants for robotic sensors, satellite docking systems, and multi-robot collaboration. Recent projects involve Navantia, the NSW Space Research Network, and industry partnerships. Professional Roles: IEEE Senior Member, Treasurer of the Australian Robotics and Automation Association, and Associate Editor for IEEE Transactions on Robotics and other journals. She chairs conferences like the Australasian Conference on Robotics and Automation. Labs/Teams: UTS Robotics Institute, collaborating with global institutions like ETH Zürich and DLR. Her work integrates robotics with industries such as agriculture and construction, emphasizing sustainability and safety.

Cynthia F. Mossمشاهده پروفایل

استاد

• Sensory coding
• Auditory neuroscience
• Spatial perception
• +۶ مورد دیگر

Cynthia F. Moss is a Professor in the Department of Psychological and Brain Sciences at Johns Hopkins University (JHU), with joint appointments in Neuroscience and Mechanical Engineering. She directs the Comparative Neural Systems and Behavior Laboratory (Bat Lab), investigating neural mechanisms of sensory perception and spatial navigation in echolocating bats. Her work combines neurophysiology, behavioral ecology, and engineering to study how bats process auditory information for navigation, communication, and obstacle avoidance. Dr. Moss earned a B.S. (summa cum laude) from the University of Massachusetts, Amherst, and a Ph.D. from Brown University. She held prior faculty positions at Harvard University and the University of Maryland, where she directed the Neuroscience and Cognitive Science graduate program. Her research has received prestigious awards including the Hartmann Award (2017), James McKeen Cattell Award (2018), and Alexander von Humboldt Research Prize (2019). Her research focuses on sensory coding of natural stimuli, spatial perception, attention, and adaptive motor control. Key findings include discoveries about 3D auditory space representation in the midbrain, age-resistant hearing in bats, and the role of wing hairs in flight control. Her lab employs innovative techniques like wireless neural recording, two-photon imaging, and DREADDs-mediated inactivation to study neural circuits. Dr. Moss collaborates across disciplines, bridging neurobiology, robotics, and sensory systems engineering. Her work informs biomimetic technologies for sonar navigation and adaptive control systems. She actively mentors students and postdocs in the Krieger School of Arts and Sciences, Whiting School of Engineering, and School of Medicine at JHU.

• 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.

Tarunraj Singhمشاهده پروفایل

استاد

• Target tracking
• Human-vehicle control
• Optimal control
• +۷ مورد دیگر

Tarunraj Singh is a Professor in the Department of Mechanical and Aerospace Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on control systems, robotics, and dynamics, with emphasis on target tracking, optimal control, and vibration mitigation in complex systems. He holds a PhD from the University of Waterloo (1991) and earlier degrees from Indian educational institutions. His work integrates advanced mathematical techniques like polynomial chaos expansions and differential flatness with practical applications in aerospace, robotics, and biomedical engineering. Education : PhD, Mechanical Engineering, University of Waterloo, 1991 ME, Mechanical Engineering, Indian Institute of Science, 1988 BE, Mechanical Engineering, Bangalore University, 1986 Research Interests : Dr. Singh specializes in developing robust control strategies for nonlinear systems, with notable contributions to: Reference shaping for precision motion control Uncertainty quantification in dynamical systems Vibration suppression in robotic systems Bioengineering applications including blood glucose control for diabetics Space systems and tethered satellite dynamics His lab focuses on bridging theoretical advancements with real-world implementation through experiments involving UAVs, robotic manipulators, and biomedical devices. Research Trends : Recent work emphasizes energy-efficient trajectory planning, probabilistic control under uncertainty, and real-time sensor integration. His publications (2020–2025) consistently address challenges in optimal control with practical applications across robotics, aerospace, and biomedical systems. Lab Activities : Directs the Control, Dynamics and Estimation Laboratory, which develops novel algorithms for motion control, system identification, and safety-critical applications. Current projects include UAV payload stabilization, autonomous vehicle navigation, and smart agricultural robotics.

• Drone Autonomy
• Drone-Based Remote Sensing
• Aerospace Engineering
• +۷ مورد دیگر

Dr. Fernando Vanegas Alvarez is a Lecturer at the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT). He holds a M.Sc. in Electrical Engineering from Halmstad University and a PhD in Aerial Robotics from QUT. His research focuses on Drone Autonomy, UAV navigation in GNSS-denied environments, and AI-assisted remote sensing. Education: M.Sc. in Electrical Engineering, Halmstad University PhD in Aerial Robotics, QUT Research Interests: Dr. Vanegas' work emphasizes motion planning for UAV exploration , POMDP , SLAM , Visual Odometry , and AI-driven remote sensing applications . His projects include UAV frameworks for planetary exploration, invasive species mapping, and multi-UAV coordination in challenging environments. Scientific Awards: Advanced Queensland Industry Research Fellowship Grant (2024) Supervision & Grants: Dr. Vanegas has supervised three postgraduate students, including topics like planetary exploration UAV systems and multi-agent UAV search algorithms. He actively accepts new students for Honours, Masters, and PhD programs. His research is supported by grants and collaborations with the QUT Centre for Robotics. Teams & Affiliations: He is a core member of the QUT Centre for Robotics and contributes to the School of Electrical Engineering & Robotics. His work bridges robotics, AI, and environmental science.

• Wireless Communications
• Information Theory
• Communication Networks
• +۱۸ مورد دیگر

Cenk Gursoy is a Professor in the Department of Electrical Engineering and Computer Science at the College of Engineering and Computer Science, Syracuse University. He previously served as a faculty member at the University of Nebraska-Lincoln from 2004 to 2011. He holds a Ph.D. in Electrical Engineering from Princeton University and a B.S. from Bogazici University, Turkey. His research spans wireless communications, information theory, signal processing, and networking. Key areas include 5G/6G technologies, millimeter-wave communications, UAV-assisted networks, energy efficiency, intelligent reflecting surfaces, and machine learning for networking. He has made significant contributions to finite blocklength communications, QoS provisioning, and secure wireless transmissions. The recent publications highlight a strong trend in integrating machine learning—particularly deep reinforcement learning—into wireless resource allocation, network slicing, UAV trajectory planning, and anomaly detection. His work increasingly bridges theoretical information-theoretic models with practical implementations in emerging wireless systems such as RIS-aided networks, NOMA, and edge computing. NSF CAREER Award, 2006 2020 IEEE Region 1 Technological Innovation (Academic) Award IEEE Green Communications & Computing Technical Committee Best Journal Paper Award EURASIP Journal of Wireless Communications and Networking Best Paper Award IEEE PIMRC Best Paper Award Maude Hammond Fling Faculty Research Fellowship All-University Doctoral Prize (awarded twice to his students) Dr. Gursoy has advised over 20 Ph.D. and M.S. students, many of whom now hold positions at leading universities and tech companies. His research has been funded by multiple National Science Foundation grants as Principal or Co-Principal Investigator, focusing on fundamental limits of wireless systems, millimeter-wave networking, and green cloud platforms. He serves as an Area Editor for IEEE Transactions on Vehicular Technology and as an Editor for several other IEEE Transactions journals. He leads the Wireless Communications & Networking Lab and the Smart Vision Systems Lab at Syracuse University, fostering interdisciplinary research in smart networks, IoT, and intelligent sensing systems.

Stefana Paraschoمشاهده پروفایل

استادیار

• Digital Fabrication
• Robotic Construction
• Sustainable Architecture
• +۳ مورد دیگر

Stefana Parascho serves as Tenure Track Assistant Professor at the Swiss Federal Institute of Technology in Lausanne (EPFL) within the School of Architecture, Civil and Environmental Engineering (ENAC), specifically in the Institute of Architecture (IA). She leads the Laboratory for Creative Computation (CRCL) and concurrently heads the Diversity Office at ENAC, demonstrating dual commitments to technological innovation and institutional equity. Her research pioneers intersections of digital fabrication, robotics, and sustainable architecture, with particular focus on transforming construction waste into valuable resources. Through computational design and robotic assembly, she develops novel methodologies for upcycling concrete rubble and timber into structurally sound building components, directly addressing circular economy challenges in construction. Her work bridges theoretical frameworks with physical prototyping, emphasizing human-robot collaboration and material reintegration. Analysis of her recent publications reveals a cohesive trajectory toward waste valorization through digital processes, with concrete rubble masonry and timber reuse forming the core technical pillars. These investigations consistently integrate robotic fabrication, structural validation, and circular design principles across 15+ publications since 2023, establishing new paradigms for resource-efficient construction. As an academic advisor, she supervises four PhD candidates (Grangeot Maxence, Skevaki Eleni Maria, Vallat Gabriel Rémi, Wang Jingwen) while contributing to architectural education through courses like "Digital design and making: A critical introduction" that merge technical skill development with theoretical critique. Her leadership extends to the ENAC Teaching Committee and institutional diversity initiatives, reflecting comprehensive engagement with academic community development. Her operational base at CRCL (https://crcl.epfl.ch) provides the technical infrastructure for robotic experimentation, while her Diversity Office role (https://www.epfl.ch/schools/enac/about/diversity-office/) demonstrates parallel commitment to inclusive academic environments. This dual focus positions her at the forefront of both technological innovation and cultural transformation within architectural academia.

Tomonari Furukawaمشاهده پروفایل

استاد

• Robotics
• Computational Mechanics
• Autonomous Systems
• +۳ مورد دیگر

Tomonari Furukawa is a Professor and Zinn Faculty Scholar at the University of Virginia, leading the VICTOR Lab. He holds a B.Eng. in Mechanical Engineering from Waseda University (1990), an M.Eng. in Mechatronic Engineering from the University of Sydney (1993), and a Ph.D. in Quantum Engineering and Systems Science from the University of Tokyo (1996). His research focuses on robotics, computational mechanics, autonomous systems, and advanced sensor technologies. He has published over 300 papers, contributed to editorial boards, and secured grants such as the U.S. DOD DURIP grants for advanced research infrastructure. His work spans topics like autonomous robotic mapping, sensor fusion, and real-time deformation measurement for automotive safety. He has developed systems for tire tread profiling, crash deformation analysis, and 3D road surface reconstruction. Furukawa’s methodologies often integrate Bayesian approaches, neural networks, and multi-sensor data fusion to solve complex engineering challenges. His contributions to the NSF I/UCRC Centre for Tire Research highlight his impact on applied mechanics. Recipient of multiple career and paper awards, Furukawa emphasizes translational research. His VICTOR Lab explores cutting-edge robotics, including compliant bipedal designs for disaster response (e.g., DARPA Robotics Challenge) and autonomous navigation systems. Current projects leverage AI and advanced vision systems for infrastructure monitoring and human-robot collaboration.

Marko Bekoمشاهده پروفایل

پژوهشگر

• Computer Science
• Wireless Sensor Networks
• Localization
• +۳ مورد دیگر

Marko Beko is a researcher affiliated with Lusofona University in Lisbon, Portugal. He is actively involved in projects related to wireless sensor networks, localization algorithms, and machine learning applications in telecommunications. His work spans areas such as GNSS-denied navigation, federated learning, and IoT network optimization. Research Interests Localization in wireless networks Machine learning for IoT UAV navigation systems Signal processing and network optimization Stochastic geometry in massive IoT Energy-efficient communication protocols Recent publications focus on deep learning methods for unmanned aerial vehicle (UAV) navigation, linear precoding for MIMO systems, and federated learning in rural environmental monitoring. His work demonstrates strong interdisciplinary connections between computer science, telecommunications, and aerospace engineering.

Mahmood Azimi-Sadjadiمشاهده پروفایل

استاد

• Digital Signal Processing
• Machine Learning
• Distributed Sensor Networks
• +۳ مورد دیگر

Dr. Mahmood Azimi-Sadjadi is a full Professor in the Department of Electrical and Computer Engineering at Colorado State University (CSU), affiliated with the Walter Scott, Jr. College of Engineering. He leads the Digital Signal/Image Processing Laboratory , focusing on advanced signal processing, machine learning, and underwater acoustics research. His work spans sonar systems, distributed sensor networks, and remote sensing applications. Educational Background: B.S. in Electrical Engineering, University of Tehran (1977) M.S. and Ph.D. in Electrical Engineering, Imperial College of Science and Technology, University of London (1978, 1982) Research Focus: His research emphasizes statistical signal/image processing, machine learning, and underwater target detection/classification using sonar. He has pioneered methods like manifold-based UXO classification and Bayesian occupancy grids. His lab develops both theoretical frameworks (e.g., canonical correlation analysis) and applied systems (e.g., acoustic tomography). Recent Publications Trends: Recent work includes adaptive machine learning for underwater UXO classification, wildfire prediction via satellite data, and autonomous systems navigation. His publications blend signal processing fundamentals with cutting-edge AI techniques. Awards & Affiliations: 1999 Abell Faculty Teaching Award (College of Engineering) Fellow of CIRA (Center for Information and Remote Sensing Research) Member of IEEE (Life Member) and IEEE Neural Network Society Advising & Labs: Directs the Digital Signal/Image Processing Lab, which collaborates on projects like acoustic source localization and sensor network optimization. His research has been supported by grants from agencies like SERDP (e.g., MR-2416 project).

Giuseppe FRANZE'مشاهده پروفایل

استاد

• Constrained Predictive Control
• Networked Control Systems
• Cyber-Physical Systems
• +۷ مورد دیگر

Giuseppe FRANZE' is a Full Professor at the Department of Mechanical, Energy and Management Engineering (DIMEG) of the University of Calabria since 2022. He has over 200 publications in archival journals, book chapters, and conference proceedings, with a focus on constrained predictive control, networked control systems, and resilient control for cyber-physical systems. His research includes theoretical and applied projects funded by MIUR/MUR, European Union, and international institutions. IEEE Senior Member (2019) Associate Editor for IEEE/CAA Journal of Automatica Sinica Guest Editor for Special Issue on Resilient Control in Large-Scale Networked Cyber-Physical Systems Organized sessions at CoDIT, ETFA, CASE conferences Collaborations with Carnegie Mellon, Concordia University, Georgia Tech, and others His research spans constrained predictive control, fault-tolerant strategies, obstacle avoidance for autonomous vehicles, and machine learning integration in control systems. Recent articles emphasize resilient control under network attacks, encrypted MPC, and reinforcement learning for multi-agent systems. He received Best Paper and Best Reviewer awards at international conferences. Best Paper - CoDIT’19 Best Reviewer - IEEE ICAS 2021 FRANZE' has taught undergraduate and graduate courses in Automatic Control, Digital Control, and Robotics at the University of Calabria for over 25 years. He has chaired institutional committees, including the Degree Course Council for Automation Engineering and the Research Committee at DIMEG. His scientific partnerships include institutions like Concordia University, Northeastern University, and Université Libre de Bruxelles.

Seongim Choiمشاهده پروفایل

استادیار

• Computational Design Optimization
• CFD (Computational Fluid Dynamics)
• Multidisciplinary Analysis and Design Optimization (MADO)
• +۵ مورد دیگر

Seongim Choi is an Assistant Professor in the Kevin T. Crofton Department of Aerospace and Ocean Engineering at Virginia Tech and an Adjunct Professor at KAIST's Graduate School of Transportation. His research focuses on computational design optimization, advanced CFD methods, and multidisciplinary analysis for aerospace systems. He holds a Ph.D. from Stanford University (2006) and degrees from Seoul National University (B.S. 1997, M.S. 1999). His expertise includes unsteady flow analysis, fluid-structure interaction, and rotorcraft design. Notable awards include the Young Investigator Award from the Asian/Australian Rotorcraft Forum (2012) and Best Paper Awards from AIAA conferences (2004). Professional roles span NASA Ames, the U.S. Army Aeroflightdynamics Directorate, and KAIST. Research interests emphasize adjoint-based sensitivity analysis, time-spectral methods for CFD, and machine learning integration in design optimization. Current work addresses low-boom supersonic jets, helicopter rotors, and autonomous UAV systems. His affiliations include the Virginia Tech College of Engineering and collaborations with KAIST's aerospace programs.