جست‌وجوی استاد و پژوهشگر

• Complex Systems
• Dynamical Systems
• Network Science
• +۱۳ مورد دیگر

Luc Berthouze is a Professor of Complex Systems (Informatics) at the School of Engineering and Informatics, University of Sussex, where he leads interdisciplinary research at the intersection of mathematics, engineering, and neurophysiology. He also holds an honorary appointment at the Great Ormond Street Hospital Institute of Child Health, University College London. His educational background includes a PhD in Applied Mathematics and Computer Science from the University of Evry Val d’Essonne (1996), followed by research positions at the Electrotechnical Laboratory (ETL) and the National Institute of Advanced Industrial Science and Technology (AIST) in Japan, before joining the University of Sussex faculty in 2006. His research focuses on dynamical processes on networks, including neuronal synchronization, epidemic spreading, and fault detection in IT infrastructures. He develops mathematical models and analysis methods rooted in dynamical systems, random processes, graph theory, control theory, and signal processing. Applications span neuroscience (EEG, EMG, MEG), robotics, and large-scale network management. The trend in his recent publications reveals a strong emphasis on network dynamics across biological and technological systems. Key themes include functional connectivity inference, metastability in oscillatory networks, epidemic modeling on structured networks, and scalable observability in microservices. His work increasingly bridges neuroscience and computer engineering, exemplified by projects like 'Rethinking large-scale network management through the lens of neuroscience.' Mathematical Neuroscience Mathematical Epidemiology Time Series Analysis Network Analysis Synchronization and Criticality Motor Control and Coordination He has received substantial research funding from EPSRC, Innovate UK, Moogsoft, Aviva, and the Leverhulme Trust, supporting work on network controllability, data-driven decision making, and Bayesian inference. His grants often involve collaborations with industry partners, indicating applied and translational impact. He supervises research projects and teaches courses such as 'Intelligence in Animals and Machines,' contributing to both undergraduate and postgraduate education. His lab and research team work on developing scalable mathematical frameworks for network analysis, with applications in healthcare, robotics, and IT infrastructure.

Lee McCluskeyمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Planning and Knowledge Engineering
• Traffic Control
• +۶ مورد دیگر

Lee McCluskey is a Research Professor in the Department of Computer Science at the University of Huddersfield's School of Computing and Engineering. Affiliated with the Centre for Planning, Autonomy and Representation of Knowledge and the Centre for Autonomous and Intelligent Systems, McCluskey actively supervises PhD students and contributes to research in artificial intelligence, planning, and knowledge engineering. BSc and MSc in Mathematics PhD by Publication in Computer Science McCluskey's research spans automated planning, knowledge engineering, and traffic control systems. Key projects include traffic signal optimization, ontology-based rolling stock maintenance, and domain modeling for autonomous systems. Collaborations with institutions like NATS Ltd and City University highlight their industry impact. Recent publications demonstrate expertise in deploying AI for real-time urban traffic management, PDDL+ modeling, and ontology-driven virtual depot systems. Research output trends emphasize practical applications of planning algorithms in transportation and maintenance domains. McCluskey's career began in mathematical modeling before transitioning to computer-aided design and academic roles at Hatfield Polytechnic and City University. Current work focuses on integrating large language models with planning systems through the Centre for Planning, Autonomy and Representation of Knowledge. Active in organizing conferences like the International Conference on Automated Planning and Scheduling, McCluskey contributes to advancing AI techniques in scheduling and domain modeling. Research outputs include foundational work in knowledge engineering, macros, and heuristic algorithms.

Jinhee Kimمشاهده پروفایل

استادیار

• Learning Sciences
• Human-Computer Interaction in Education
• Instructional Design
• +۶ مورد دیگر

Dr. Jinhee Kim is an Assistant Professor in the Instructional Design and Technology (IDT) program at the Department of STEM Education & Professional Studies, Darden College of Education and Professional Studies, Old Dominion University. Her prior roles include faculty at Xi'an Jiaotong-Liverpool University, consultant at UNESCO International Bureau of Education, program specialist at APEC e-Learning training center, and researcher at Central American Bank for Economic Integration. She specializes in AI-driven educational innovation and interdisciplinary research. Her research interests include Artificial Intelligence in Education Human-Computer Interaction Learning Sciences Student-Centered Learning Learning and Teaching Analytics Technology for International Development Recent publications highlight her focus on AI collaboration in K-12 classrooms, data mining for online learning preferences, and cross-cultural technology adoption models. Her work applies quantitative and qualitative methods to understand educational processes.

Stoicuta Olimpiuمشاهده پروفایل

دانشیار

• Control Systems
• Electrical Engineering
• Renewable Energy
• +۴ مورد دیگر

Associate Professor Olimpiu Stoicuta is affiliated with the Polytechnic University of Timișoara's Faculty of Mechanical and Electrical Engineering, Department of Automation, Computers, Electrical and Power Engineering. His research focuses on advanced control systems for electrical motors, renewable energy integration, and econometric analysis of energy policies. He has extensive expertise in sensorless vector control, induction motor modeling, and optical communication technologies. Education details are not explicitly stated in the provided text, but his work indicates a strong background in electrical engineering and control systems. He has published widely on topics including adaptive observers, energy transformation systems, and underground communication solutions. His research interests span multiple domains: (1) Electrical Engineering with emphasis on motor control and power electronics; (2) Renewable Energy focusing on system integration and efficiency improvements; (3) Data Communication involving LiFi and optical networks for industrial applications; and (4) Econometric Modeling related to energy policy analysis in Romania and the EU. Recent publications (2020-2025) highlight trends in AI-driven network optimization, sensorless motor control advancements, and energy policy studies. Articles frequently address practical engineering challenges like underground communication reliability and EV autonomy enhancement. No specific awards or grants are mentioned, though his prolific publication record suggests sustained research activity. Laboratory and team involvement can be inferred through his work on robotics (exoskeleton control) and collaborative projects in industrial automation systems.

• Robotics
• Biomedical Engineering
• Artificial Intelligence
• +۳ مورد دیگر

Panaite Arun Fabian is an Assistant Professor of Engineering at the Faculty of Mechanical and Electrical Engineering, Department of Automation, Computers, Electrical and Power Engineering, affiliated with UPET. His research focuses on interdisciplinary engineering applications, including robotics, biomedical systems, and human-machine interaction. Notable projects include AI-driven gait analysis for neurodegenerative diseases, brain-computer interfaces for educational robotics, and biomimetic prosthetic devices. His work bridges mechanical engineering with healthcare technology, emphasizing assistive technologies and motion capture systems. Research interests span robotics, biomedical engineering, and sensor technologies, with a focus on applications like prosthetics, human motion analysis, and augmented reality in robotics control. His publications since 2019 highlight trends in assistive robotics, educational robotics, and bio-inspired mechanisms. While no specific awards are listed, his contributions to neurotechnology and rehabilitation engineering demonstrate impactful research. Advising and grants details are not provided in available texts. His work often involves collaborations within the department's automation and electrical engineering fields.

Maurizio Leottaمشاهده پروفایل

پژوهشگر

• Test Automation
• Empirical Software Engineering
• Requirements Engineering
• +۶ مورد دیگر

Maurizio Leotta is a faculty member at the Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS) at the University of Genova, Italy. His research focuses on software testing automation, empirical software engineering, requirements engineering, business process modeling, and model-driven software development. He has contributed to advancing end-to-end web testing methodologies through tools like Assessor, STILE, and SleepReplacer-GPT, emphasizing robust locators, thread sleep replacement, and parallel test execution optimization. Primary Affiliation : DIBRIS, University of Genova Research Themes : Test Automation, Gamification in Software Testing, Web Accessibility, IoT Systems Testing In recent years, Leotta has explored the integration of large language models (LLMs) in automated testing, comparing browser automation tools (Selenium, Cypress, Puppeteer, Playwright), and analyzing job market trends post-pandemic. His work spans both practical tool development (e.g., TESTQUEST, Mutta) and empirical studies evaluating testing approaches. He actively participates in program committees for testing workshops and collaborates on gamification initiatives in software development education. The 15 most recent publications reflect his expertise in test automation frameworks, gamification strategies, and accessibility enhancements. Articles cover topics such as explicit wait management in web testing, LLM applications for image captioning, and comparative studies of automation tools. His research also extends to IoT system testing, runtime verification, and job market analysis using large-scale job advertisement data.

• Information Technology Governance
• Business Process Management
• IT Service Management
• +۱۲ مورد دیگر

Ruben Filipe de Sousa Pereira is an Assistant Professor in the Department of Information Science and Technology at ISCTE – Instituto Universitário de Lisboa, where he also contributes as Director and Coordinator of the Master's Degree in Computer Science and Management. He is an Integrated Researcher at the Institute of Telecommunications - IUL, focusing on applied research in digital transformation and information systems. His academic background includes a PhD and an Integrated Master’s in Information Systems and Computer Engineering from Instituto Superior Técnico (IST). His research interests center on Information Technology Governance (ITG) , Business Process Management (BPM) , IT Service Management (ITSM) , DevOps , and digital transformation , with practical applications in healthcare, telecommunications, and higher education. His work often involves developing tools and models for process optimization, risk management, and automation. The recent articles reflect a strong trend in applying digital technologies to real-world organizational challenges, particularly in DevOps automation , BPM in healthcare , RPA , and metaverse applications in B2B . His research combines technical development with strategic IT management, emphasizing maturity models, dashboards, and governance frameworks. Scientific journal editor, Information (Since 2023) Member of editorial team, Iberian Journal of Information Systems and Technologies (Since 2023) Member of scientific committee, World Conference on Information Systems and Technologies (Since 2016) Member of scientific committee, Iberian Conference on Information Systems and Technologies (Since 2016) Ruben has advised and led multiple research projects, often in collaboration with industry partners such as Siemens, EDP, REMAX, and HSM. He has coordinated numerous knowledge dissemination events and workshops on IT governance, GDPR, digital transformation, and AI. His academic management roles demonstrate leadership in curriculum development and program coordination. He has also contributed to projects on MOOC platforms, CRM systems, and decision-making dashboards for universities and hospitals. He is actively involved in developing tools for digital quality assurance, incident management, and hospital productivity measurement, reflecting a commitment to bridging academic research with practical industry needs.

• Multibody System Dynamics
• Computational Kinematics
• Biomechanics of Human Motion
• +۹ مورد دیگر

Francisco Javier Cuadrado Aranda is a faculty member in the Department of Naval and Industrial Engineering at the Ferrol Engineering Polytechnic School, University of A Coruña (UDC), Spain. His academic work spans teaching, research, and industrial collaboration, with a focus on mechanical engineering, multibody dynamics, and biomechanics. His research interests include: Multibody System Dynamics Computational Kinematics and Dynamics Biomechanics of Human Motion Gait Analysis and Orthosis Design Machine and Maintenance Engineering Simulation and Numerical Integration His recent publications (2021–2025) reflect a strong trend in applying multibody dynamics to biomechanics and robotics, particularly in human gait simulation, exoskeletons, assistive devices, and industrial applications. The research combines modeling, optimization, real-time simulation, and sensor integration, often with industrial or medical applications in automotive, maritime, and rehabilitation sectors. He has secured significant research funding from national (MINECO, Xunta de Galicia), European (EU), and industrial sources (GKN Driveline, NAVANTIA, Pixee Medical), and has directed multiple final-year and master’s theses. He is also involved in patents and software development through collaborations with Tecnalia and spin-offs like ABLE Human Motion. He leads the Laboratorio de Ingeniería Mecánica, where he supervises student projects and conducts applied research. His teaching includes Machine Design, Maintenance Engineering, Theory of Machines, and Biomechanics across Mechanical, Industrial, and Podiatry programs.

Maryam Fouad Abdelatyمشاهده پروفایل

پژوهشگر

• Deep Learning
• Medical Ultrasound Imaging
• Harmonic Imaging
• +۳ مورد دیگر

Maryam Fouad Abdelaty is a researcher in the Department of Medical Engineering at Ruhr University Bochum, where she completed her PhD in September 2024. Her work focuses on applying deep learning techniques to medical ultrasound imaging, including harmonic imaging, synthetic data generation, and contrast-enhanced imaging. She holds a bachelor's degree in electronics engineering from the German University in Cairo (2015), a master's degree in bio-impedance spectroscopy for non-invasive glucose monitoring (2017), and a Dr.-Ing. degree from Ruhr University Bochum (2024). Bachelor's: German University in Cairo (2015) Master's: Thesis on joint NIR and bio-impedance spectroscopy for glucose monitoring (2017) PhD: Focused on deep learning in medical ultrasound (2024) Her research emphasizes improving imaging resolution, reducing invasiveness, and enhancing diagnostic accuracy through AI-driven methodologies. Recent work includes comparative studies of deep learning vs. traditional amplitude modulation in contrast-enhanced ultrasound, as well as semi-supervised approaches for needle localization. Her publications span conferences like IEEE Ultrasonics Symposium and IEEE ISBI, with a focus on deep learning applications in biomedical imaging. Notable contributions include synthetic ultrasound signal generation using GANs and single-shot harmonic imaging techniques. While no formal advising or grants are explicitly listed, her research demonstrates significant contributions to medical imaging innovation. No lab affiliations or teams are mentioned in the provided text.

• Databases
• Big Data
• Data Storage
• +۱۲ مورد دیگر

Alberto Abello Gamazo is a full professor at the Facultat d'Informàtica de Barcelona (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Services and Information Systems Engineering. He coordinates the Erasmus Mundus Doctoral Program in Information Technologies for Business Intelligence and leads research within the inSSIDE and inLab FIB groups. His work bridges computer science and healthcare, focusing on data-intensive systems and their real-world applications. Research Interests: His expertise spans databases, big data, NoSQL, OLAP, data storage, and data science. He investigates automated data pipelines, federated data management, feature selection, and AI-driven analytics. His work increasingly integrates healthcare applications, particularly in automated diagnosis using AI and digital microscopy for diseases such as malaria and schistosomiasis. Publication Trends: His recent articles (2023–2025) emphasize automated data science pipelines (e.g., Hyppo), fairness and interpretability in machine learning, efficient data management in document stores, and the application of AI to medical diagnostics. A strong trend is the development of low-cost, open-source robotic microscopy systems for global health challenges. Scientific Awards: Premiada (recognized activity) XXV Congreso Nacional de la Sociedad Española de Enfermedades Infecciosas y Microbiologia Clínica Advising and Grants: He has advised numerous PhD students and leads multiple competitive R&D+i projects funded by national and European programs (e.g., HORIZON 2020, Plan Nacional). His projects include 'Graph-driven federated data management,' 'EXPeriment driven and user eXPerience oriented analytics,' and health-focused initiatives like 'For an improvement of Health through rapid and economic diagnosis (iH-red).' He collaborates extensively with institutions like the Hospital de la Vall d'Hebron and Fundació PROBITAS. Labs and Teams: He is a core member of the inSSIDE (integrated Software, Services, Information and Data Engineering) and inLab FIB research groups, both affiliated with CIT-UPC. These groups focus on cutting-edge data engineering, information systems, and their societal applications.

• Robotics
• Computational Kinematics and Dynamics
• Motion Planning and Control
• +۳ مورد دیگر

Ros Giralt, Lluis is an Associate Professor at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Mechanical Engineering and the CRG - Grup de Robòtica Computacional . His primary roles include academic research and teaching in robotics, with a focus on computational kinematics, dynamic motion planning, and singularity analysis in robotic systems. He holds a Doctorate in Industrial Engineering from UPC. Research Interests: His work centers on advanced robotics topics such as trajectory optimization for constrained systems, singularity-aware control, and motion planning for parallel and closed-chain robots. Key contributions include collocation methods for trajectory optimization and algorithms for singularity avoidance in complex mechanisms. Recent Research Trends: Recent publications emphasize trajectory optimization techniques (e.g., Legendre-Gauss pseudospectral methods), randomized kinodynamic planning for closed-chain robots, and cable-driven parallel robot control. His work bridges numerical computation and practical robotic applications, often involving collaboration with industry partners. Awards: Honorary Mention for the Planets Project (2017), Best Final Year Engineering Project (1991-1992). Advising & Grants: Advised PhD students like Ricard Bordalba and Carlos Rosales. Involved in projects like Synthesis of Optimally Agile and Graceful Robot Motions (2022) funded by competitive R&D grants. Labs/Teams: Leads the CRG - Computational Robotics Group , collaborating with institutions like the Institut de Robòtica i Informàtica Industrial (CSIC-UPC). Active in developing the CUIK Suite , a tool for analyzing multibody system motion.

Lucia Rita Quitadamoمشاهده پروفایل

پژوهشگر ارشد

• Epilepsy Research
• Neurophysiology
• Neural Signal Processing
• +۳ مورد دیگر

Lucia Rita Quitadamo is an Honorary Senior Research Fellow in the School of Psychology , focusing on neurophysiological research and biomedical engineering. Her work intersects epilepsy studies, brain-computer interfaces (BCI), and signal processing. Key research areas include: High-frequency oscillations (HFOs) in epilepsy surgery planning Intracranial EEG and MEG analysis for seizure onset zone localization Development of BCI systems using SSVEP and P300 protocols Sensory technology applications in surgery skill evaluation and prosthetic control Her contributions include the EPINETLAB software for epilepsy diagnosis and innovative sensory glove systems for surgical training assessment. Research spans over 20 years with notable work in neuroimaging, machine learning for medical signals, and clinical neurophysiology. Labs/Teams: Collaborates with neurology and biomedical engineering groups on interdisciplinary projects involving clinical neurophysiology and assistive technologies.

David M W Powersمشاهده پروفایل

استاد

• Artificial Intelligence
• Cognitive Science
• Robotics
• +۴ مورد دیگر

Professor David M W Powers is a leading academic at Flinders University of South Australia, holding the Professor of Computer and Cognitive Science position. He serves as Visiting Professor at Beijing University of Technology and contributes extensively to editorial and program committees, including as Editor-in-Chief of Springer's Cognitive Science and Technology series. PhD in Computational Psycholinguistics (UNSW) Founding President of ACL SIGNLL and CoNLL conference series Recipient of 15+ major research grants including multiple ARC and NSF awards His research spans Artificial Intelligence, Cognitive Science, Robotics, and Biomedical Engineering with a focus on: Embodied Conversational Agents Brain-Computer Interfaces Parallel Logic Programming Evaluation Metrics in Machine Learning Assistive Technologies for disability support AI in Health and Education Recent publications emphasize optimization algorithms for autonomous systems (AUV routing models) and evaluation methodology advancements . Scientific awards include the Loebner Prize Bronze Medal and multiple ARC grants totaling over $30M in funding. Teaching roles include coordination of courses in Artificial Intelligence, Computational Intelligence, and Human-Computer Interaction . Professional engagements span leadership roles in ACL, ACM, and IEEE, with significant industry collaboration through startups like YourAmigo Pty Ltd.

Armin Lechlerمشاهده پروفایل

پژوهشگر

• Automation Technology
• Industrial Robotics
• Control Systems
• +۴ مورد دیگر

Armin Lechler , holding the title of Dr.-Ing. , is a Senior Researcher at the Institute for Control Engineering of Machine Tools and Manufacturing Units (ISW) at the University of Stuttgart. He is also a key member of the Cluster of Excellence IntCDC (Integrative Computational Design and Construction for Architecture). His work focuses on control engineering, automation technology, and robotics, with a particular emphasis on data-driven manufacturing systems and cyber-physical platforms.

Mairieli Wesselمشاهده پروفایل

استادیار

• Software Engineering
• Computer Supported Cooperative Work (CSCW)
• Open Source Software (OSS)
• +۳ مورد دیگر

Dr. Mairieli Wessel is an Assistant Professor at the Department of Software Science, Radboud University (Netherlands) , focusing on the intersection of Software Engineering (SE) and Computer Supported Cooperative Work (CSCW) . Her research explores how software bots can enhance collaboration in Open Source Software (OSS) communities. PhD in Computer Science from University of São Paulo (USP) (2021) Postdoctoral Researcher at Delft University of Technology (2021-2022) Visiting PhD Student at Concordia University (2021) Her recent work examines GitHub Actions , code review bots , and bot comment analysis . She serves as Guest Editor for IEEE Software and chairs tracks at MSR and CHASE conferences. 2024 Best Runner-up Paper (AST) 2024/2022 Distinguished Reviewer Awards (ICPC, MSR) 2020 IEEE TCSE Distinguished Paper Award (ICSME) Dr. Wessel actively supervises PhD students and develops tools like BotHunter for bot detection. Her practical experience includes software development roles at IBM Research and 4Makers STEM Education .