جست‌وجوی استاد و پژوهشگر

Evangelos Kranakisمشاهده پروفایل

استاد

• Algorithmics
• Distributed Computing
• Mobile Agent Computing
• +۳ مورد دیگر

Evangelos Kranakis is the Chancellor's Professor at Carleton University's School of Computer Science (SCS), where he has been since 1991 and served as director from 1994 to 2000. He holds a Ph.D. in Mathematics from the University of Minnesota (1980) and a B.Sc. from the National Technical University of Athens (1973). His research focuses on Algorithmics, Distributed and Mobile Agent Computing, Networks (Ad Hoc/Wireless/Sensor), Cryptographic Security, and Computational Biology . He has held visiting positions at institutions worldwide, including ETH Zurich, Université de Paris Sud, and Simon Fraser University. Research interests emphasize algorithmic foundations for distributed systems, mobile agents, and network security. His work bridges theoretical models with practical applications in wireless networks, robotic search strategies, and underwater communication. He leads the Distributed and Network Computing research group and maintains an academic homepage with publications and ORCID profile ( orcid.org/0000-0002-8959-4428 ). Key articles explore topics like optimal task offloading in edge computing, robot coordination for search/evacuation, and UAV trajectory design using reinforcement learning. His contributions span interdisciplinary fields, with a focus on fault-tolerant systems and network optimization. Notable technical achievements include pioneering work on distributed algorithms for mobile agents and underwater acoustic networks. His research also addresses quantum network protocols and multi-agent systems in dynamic environments.

Hongkai Zhaoمشاهده پروفایل

استاد

• Applied and Computational Mathematics
• Inverse Problems
• Imaging
• +۴ مورد دیگر

Professor Hongkai Zhao is a Chancellor’s Professor and Chair of the Mathematics Department at the University of California, Irvine (UCI), with a joint appointment in Computer Science. He holds a B.S. from Peking University, M.S. from USC, and Ph.D. from UCLA, all in Mathematics. His research focuses on computational and applied mathematics, including moving interface problems, inverse problems, imaging, and Hamilton-Jacobi equations. He is renowned for developing the Fast Sweeping Method (FSM) for solving hyperbolic PDEs efficiently. Education: B.S. (Peking University, 1990), M.S. (USC, 1992), Ph.D. (UCLA, 1996). Employment: UCI faculty since 1999, Szego Assistant Professor at Stanford (1996–1999). Research interests span computational fluid dynamics (moving interfaces), inverse problems (tomography, wave propagation), and imaging (medical imaging, computer vision). Key contributions include numerical methods for surfactant-laden drops, fast algorithms for Hamilton-Jacobi equations, and 4D cone-beam CT reconstruction. Awards include the Feng Kang Prize (2007), Sloan Fellowship (2002–2004), and Chancellor’s Professorship (2016–present). He has authored over 100 publications on numerical methods, inverse problems, and PDEs. Lab affiliations: Active in interdisciplinary research at UCI, leading projects in computational mathematics and imaging science. Current work includes high-frequency wave propagation, multi-scale modeling, and geometric data analysis.

Chris Phillipsمشاهده پروفایل

دانشیار

• Internet Technologies
• Optical Networking
• Network Security
• +۵ مورد دیگر

Dr. Chris Phillips is a Reader in the School of Electronic Engineering and Computer Science at Queen Mary University of London. He holds a BEng in Telecommunications Engineering and a PhD in Telecommunications from Queen Mary. His roles include Director of Recruitment and Admissions for EECS, Programme Director of Computer Systems Engineering, and member of the Networks Research Group. His research focuses on Internet Technologies, Optical Networking, Network Security, and Energy-Efficient systems, with emphasis on resilient communication, wireless sensor networks, and nomadic computing. Education: BEng Telecommunications Engineering (1st Class Honours), Queen Mary University of London (1984–1987); PhD in Telecommunications, Queen Mary University of London (1987–1991). Professional experience includes roles at Bell Northern Research, Siemens–Roke Manor Research, Nortel Networks, and academic leadership at Queen Mary since 2000. He has supervised over 20 PhD students and contributed to multiple research grants, including projects on energy management in wired networks and resilient overlay systems. Research Interests: Internet protocols, optical networking, network security, energy efficiency, wireless sensor networks, and resilient communication systems. His work spans theoretical advancements and practical implementations, with applications in healthcare, agriculture, and vehicular systems. Recent publications explore IoT optimization, cooperative routing in MANETs, and energy-efficient optical networks. Grants and Awards: Secured funding from EPSRC, Royal Society, Nortel, Nokia, and the UK-China Government Office for Science. Notable grants include the EPSRC-funded project on machine learning in optical networks and Royal Society collaborations on intelligent connection management. Teaching: Currently teaches Computer Architecture and Networks (Postgraduate) and Microprocessor Systems Design (Undergraduate). Previously lectured on topics like MPLS networks, G-MPLS, and real-time transport protocols. His teaching integrates practical lab work with theoretical frameworks, emphasizing hands-on experience with microcontrollers and network protocols. Labs/Teams: Active member of the Networks Research Group, collaborating with institutions like Technical University of Denmark and University of Girona. His research team focuses on developing innovative solutions for network resilience, energy efficiency, and distributed systems.

Srikanth Saripalliمشاهده پروفایل

استاد

• Autonomous Vehicles
• UAV Guidance Systems
• Vision-Based Control
• +۲ مورد دیگر

Srikanth Saripalli is Professor and Director of the Center for Autonomous Vehicles and Sensor Systems at Texas A&M. His research develops autonomous navigation systems for UAVs and ground vehicles, specializing in vision-based control, sensor calibration, and path planning algorithms for GPS-denied environments.

• Communications engineering
• Electronics, sensors and digital hardware
• Aerospace engineering
• +۷ مورد دیگر

Bill Moran is a Professor (Research Focused) in the School of Engineering at RMIT University. He specializes in research areas including communications engineering, applied mathematics, and sensor systems. His work focuses on localization algorithms, sensor networks, and signal processing applications. His email is bill.moran@rmit.edu.au. Research Interests: Moran’s research spans communications engineering, electronics, aerospace engineering, and applied mathematics. He has contributed to advancements in multi-sensor positioning, hidden Markov models, and Bayesian algorithms. His work often integrates theoretical frameworks with practical applications in robotics, underwater surveillance, and autonomous systems. Articles Trends: His publications (2018–2021) emphasize localization systems, sensor fusion, and gravitational wave detection. Key themes include Bayesian algorithms, multi-objective optimization, and trajectory planning for autonomous vehicles. Recent work explores underwater threat detection and RRT* algorithms for path planning. No scientific awards or honors explicitly mentioned. Supervised one project: Localization Using Hidden Markov Models in a Multipath Environment (2017). Labs/Teams: Affiliated with RMIT’s School of Engineering research groups focused on signal processing and autonomous systems.

Shigang Yueمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Robotics
• +۴ مورد دیگر

Professor Shigang Yue is a Professor of Computer Science at the University of Leicester's Computing and Mathematical Sciences department. His research focuses on artificial intelligence, computer vision, robotics, neuroscience, and bio-inspired systems. He has published over 200 papers and led EU-funded projects. He holds a PhD from Beijing University of Technology (1996) and was an Alexander von Humboldt Research Fellow (2000-2001). Research interests include bio-inspired visual neural networks, autonomous robotics, medical image analysis, machine learning, and swarm intelligence. He has coordinated EU FP7 and Horizon 2020 projects and examined over 20 PhD theses. His work bridges biological systems and robotics, emphasizing collision avoidance, motion detection, and swarm robotics. Notable contributions include the I2Bot platform for insect navigation simulation, bio-inspired collision detection models (e.g., LGMD), and frameworks for small target tracking. He is an EPSRC peer reviewer and editorial board member for international journals. Labs and teams: Active in developing bio-inspired robotics systems and collaborative platforms like Colcos φ for swarm robotics. His group welcomes PhD and visiting students in AI and robotics.

Silvia Ferrariمشاهده پروفایل

استاد

• Robotics and Autonomy
• Artificial Intelligence
• Neuroscience
• +۵ مورد دیگر

Silvia Ferrari is the John Brancaccio Professor of Mechanical and Aerospace Engineering at Cornell University, leading the Laboratory for Intelligent Systems and Controls (LISC) in Ithaca and co-directing the Cornell-Unibo Věho Institute on Vehicle Intelligence at Cornell Tech. She holds academic affiliations with both Cornell Engineering and Cornell Tech, focusing on interdisciplinary research in autonomy, robotics, and intelligent systems. Education: B.S., Aerospace Engineering, Embry-Riddle Aeronautical University (1997) M.A. and Ph.D., Mechanical and Aerospace Engineering, Princeton University (1999–2002) Research Interests: Her work spans computational intelligence, sensorimotor learning, adaptive control, and robotic autonomy. Key areas include active perception, neural network modeling, distributed sensor networks, and decision-making under uncertainty. She has pioneered methods in information-driven path planning and reinforcement learning, with applications to robotics, neuroscience, and environmental monitoring. Awards: Presidential Early Career Award for Scientists and Engineers (2006) NSF CAREER Award (2005) ONR Young Investigator Award (2004) Fellow of ASME and AIAA (2020) Labs & Leadership: As Director of LISC and co-Director of the Věho Institute, she fosters cross-campus collaborations in autonomy and urban technology. Her recent initiatives include organizing the Autonomy and Mobility Workshop, advancing Cornell’s ‘One Cornell’ research strategy.

Poul Løgstrup Bjergمشاهده پروفایل

استاد

• Environmental Risk Assessment
• Groundwater Remediation
• Contaminated Site Management
• +۱۲ مورد دیگر

Poul Løgstrup Bjerg is a Professor in the Department of Environmental and Resource Engineering at the Technical University of Denmark (DTU), where he conducts research in environmental contamination and chemicals. His work focuses on risk assessment and remediation technologies for contaminated soil, groundwater, and surface water, contributing to sustainable water resource management and UN Sustainable Development Goals. University: Technical University of Denmark School: College of Engineering Department: Department of Environmental and Resource Engineering Email: plbj@dtu.dk Phone: +45 29471605 ORCID: 0000-0002-1977-1871 Website: https://sustain.dtu.dk/ His research interests include environmental risk assessment, groundwater remediation, PFAS and pesticide contamination, isotope analysis, and geostatistical modeling of contaminant transport. He employs interdisciplinary methods combining hydrogeology, microbiology, and advanced monitoring technologies to assess and manage contaminated sites. The trend in his recent publications shows a strong focus on persistent pollutants such as PFAS and pesticides, with increasing use of innovative techniques like fluorescence spectroscopy, stable isotope analysis, and cross-borehole electrical resistivity tomography for contaminant detection and remediation monitoring. His work bridges scientific research with policy and practical applications in environmental management. Poul Løgstrup Bjerg has secured funding from major agencies including the European Commission and Innovation Fund Denmark and has led numerous collaborative projects with consulting firms (e.g., Rambøll, Cowi) and governmental bodies (e.g., Danish EPA). His research has significant societal impact, particularly in safeguarding drinking water resources. Supervisor of 25 completed PhD projects Mentor to over 100 master’s thesis students Current supervision of multiple PhD candidates in PFAS and pesticide transport projects He leads or participates in active research projects focused on PFAS attenuation, contaminant mass discharge quantification, and landfill leachate impacts. His lab collaborates extensively across Denmark and internationally, employing field investigations, laboratory experiments, and numerical modeling.

Johnathan Votionمشاهده پروفایل

استادیار

• Machine Learning
• Robotics
• Control Systems
• +۳ مورد دیگر

Johnathan Votion is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio (UTSA), affiliated with the Klesse College of Engineering and Integrated Design. His work spans machine learning, robotics, and control systems, with a focus on multi-agent coordination, sensor networks, and risk-aware optimization. Education: Ph.D. in Electrical Engineering from UTSA (2016) Research trends in his publications emphasize autonomous systems , data reliability , and uncertainty propagation , including applications in UAV trajectory planning , multi-robot collaboration , and nonholonomic control . His work integrates machine learning with engineering systems to address complex, real-world constraints.

• Signal Processing
• Image Processing
• Feature Extraction
• +۳ مورد دیگر

Rodrigo Dalvit Carvalho da Silva serves as a Research Fellow in the Department of Neurosurgery at Yale School of Medicine, Yale University, holding a primary appointment as a Postdoctoral Associate focused on computational biomedical research. His work bridges advanced signal processing with clinical neurosurgery applications through algorithmic innovation. His academic credentials include: PhD in Biomedical Engineering from Western University, Canada MSc in Teleinformatics Engineering from Federal University of Ceara, Brazil BSc in Mechatronics Engineering from University of Fortaleza, Brazil His research centers on signal/image processing, feature extraction (PCA, ICA, t-SNE, UMAP, Orthogonal moments), machine learning, deep learning, and Intracranial EEG analysis. He develops robust computational frameworks for medical image segmentation, classification, and analysis with direct applications in neurosurgery, cardiology, and craniofacial surgery. His methodological innovations target clinical challenges in brain tumor research, concussion biomechanics, and surgical planning through quantitative imaging biomarkers. Analysis of his publication record reveals a consistent trajectory from industrial computer vision (2014-2016) toward biomedical applications, culminating in recent neurosurgical and cardiological imaging breakthroughs. His signature contributions involve orthogonal moment theory for invariant feature extraction, deep learning integration with traditional image processing, and 3D reconstruction techniques for anatomical structures. The work demonstrates exceptional methodological transferability across domains while maintaining clinical relevance in neurological disorders. No scientific awards were documented in the source materials. While student mentorship and grant funding details remain unspecified in available records, his position within Yale's Neurosurgery research ecosystem suggests active participation in departmental training programs and collaborative projects. His technical expertise likely supports multiple research initiatives through computational infrastructure development. He operates within Yale Neurosurgery's research infrastructure, contributing to the Yale Program in Brain Tumor Research through computational methodologies. His work interfaces with clinical teams for intracranial EEG analysis and surgical planning, leveraging the department's imaging resources for algorithm validation against real-world neurological cases.

Zachary Grelewiczمشاهده پروفایل

استادیار

• Radiation Oncology
• Medical Physics
• Stereotactic Radiosurgery
• +۶ مورد دیگر

Zachary Grelewicz, PhD is an Assistant Professor in the Department of Radiation Oncology at Rush Medical College, Rush University. His research focuses on advanced radiation therapy techniques, including stereotactic radiosurgery (SRS), high-dose-rate (HDR) brachytherapy, and image-guided radiation therapy (IGRT). Developing innovative dosimetry methods for quality assurance in arc-based radiotherapy Optimizing real-time motion correction systems using robotic technology Advancing combined MV+ kV dose planning for improved tumor tracking Investigating medical imaging applications for precise radiation delivery His work emphasizes technical validation and implementation of novel equipment like Varian Halcyon systems, 6DOF robotic stages, and gamma cameras. Publications demonstrate expertise in radiation physics, treatment planning algorithms, and clinical applications of medical imaging technologies.

• Aeronautical Systems
• Autonomous Systems
• Control Systems
• +۵ مورد دیگر

Professor Hyo-sang Shin is a Lecturer at Cranfield University, specializing in Guidance, Navigation, and Control within the Autonomous and Intelligent Systems Group. He holds an MSc in Aerospace Engineering from KAIST and a PhD in cooperative missile guidance from Cranfield University. His expertise includes Aeronautical Systems, Autonomous Systems, and Vehicle Health Management. Research focuses on cooperative guidance/control for multiple vehicles, coordinated health monitoring, and information-driven sensing. He collaborates with industry partners like Leonardo, Airbus, and Lockheed Martin. Key awards include Silver and Most Popular Team awards from the 2004 Korea Robot Aircraft Competition. Publications emphasize advanced control algorithms, UAV trajectory optimization, and sensor fusion techniques. Over 150 peer-reviewed articles span journals like IEEE Transactions on Aerospace and Electronic Systems and International Journal of Robust and Nonlinear Control. Labs/Teams: Active contributor to the Centre for Autonomous and Cyberphysical Systems at Cranfield, leading projects on UAV swarms, autonomous systems, and hypersonic vehicle control.

• Multi-sensor Data Fusion
• Intelligent Systems
• Neural Networks
• +۴ مورد دیگر

Kathleen Kramer is a Professor of Electrical Engineering at the University of San Diego (USD), specializing in multi-sensor data fusion, intelligent systems, and neural/fuzzy systems. She holds a BS in Electrical Engineering (magna cum laude) from Loyola Marymount University, and MS/PhD in Electrical Engineering from California Institute of Technology. Her professional roles include serving on ABET's Engineering Accreditation Commission, IEEE's Board of Governors for the Aerospace Electronics Society, and leadership in the San Diego IEEE Chapter. Dr. Kramer's research focuses on advanced tracking systems, autonomous navigation, and cybersecurity in avionics. She has published over 100 papers, including work on Kalman filters, unmanned systems navigation, and cyber threat analysis. Notable recognitions include an ATHENA Pinnacle Award nomination and leadership awards from IEEE/SWE. She actively contributes to engineering education through USD's electrical engineering senior design program and outreach initiatives like FIRST Robotics. Her service includes advising USD's Tau Beta Pi chapter and supporting veteran engineering education. Research collaborations span industries like ViaSat and Bell Communications Research, emphasizing practical applications of theoretical frameworks in aerospace and robotics.

Angelo Cenedeseمشاهده پروفایل

دانشیار

• Robotics
• Control Systems
• Multi-Agent Systems
• +۵ مورد دیگر

Angelo Cenedese is an Associate Professor at the Department of Information Engineering (DEI), University of Padova, and leads the SPARCS Lab (Flying Arena and Mobile Robotics Laboratory). He co-leads the NAVLAB (Autonomous Navigation Laboratory) and holds senior roles in IEEE societies, including the Control Systems Society (CSS) and Robotics and Automation Society (RAS). His academic activities span teaching, editorial work as Associate Editor for IEEE Transactions on Industrial Informatics, and leadership in research projects focusing on robotics, control systems, and multi-agent networks. His research interests include robotics , control systems , multi-agent coordination , computer vision , autonomous navigation , and industrial automation . His recent publications emphasize machine learning for industrial vision systems, adaptive control in aerospace robotics, distributed state estimation , and secure UAV navigation under GNSS spoofing. Key trends involve edge computing , collaborative robotics , and AI-driven optimization . Scientific Awards: Award for 'Most Innovative Application' at Quality Control by Artificial Vision Conference (QCAV 2019) His projects include AI in Manufacturing (AIMS5.0), Sustainable Mobility (PNRR-MOST), and 6G Networking (PREDICT-6G), often in collaboration with Italian and international institutions. Teaching roles cover Robotics and Control , Networked Control Systems , and Computer Vision courses at both undergraduate and graduate levels.

Peter Veelaertمشاهده پروفایل

استاد

• Computer Vision
• Sensor Fusion
• Intelligent Vehicles
• +۶ مورد دیگر

Peter Veelaert is a Professor in the Department of Telecommunication and Information Processing at Ghent University, Belgium. He was born in Mortsel in 1958 and earned both his M.S. and Ph.D. in electrical engineering from Ghent University in 1981 and 1992. His research focuses on computer vision, sensor fusion, and intelligent vehicles, with a particular emphasis on digital geometry and embedded systems applications. Education: M.S. (1981) and Ph.D. (1992) in Electrical Engineering from Ghent University Veelaert teaches courses in computer vision, multimedia, algorithms on embedded systems, and digital design. His research unit, Image Processing and Interpretation (IPI), investigates geometric constructions, multi-target tracking, and behavior analysis through sensor fusion techniques. Key publication trends include advancements in digital planarity, geometric primitives, and robotics obstacle avoidance systems. Contact: Email Peter.Veelaert@UGent.be | Publications