جست‌وجوی استاد و پژوهشگر

• Software Engineering
• Technical Debt Management
• Software Architecture
• +۳ مورد دیگر

Paris Avgeriou is a Professor of Software Engineering at the University of Groningen, affiliated with the Faculty of Science and Engineering and the Bernoulli Institute. He leads the Software Engineering and Architecture research group and serves as Editor-in-Chief of the Journal of Systems and Software . His expertise spans technical debt management, software architecture, self-adaptive systems, and embedded systems design. Avgeriou holds an office at Nijenborgh 9, Groningen, and actively advises academic institutions and funding bodies globally. Research Interests: Avgeriou's work focuses on advancing software architecture principles, technical debt lifecycle management, and the integration of AI in software engineering. His research emphasizes practical solutions for improving software quality, maintainability, and system dependability, particularly in embedded and self-adaptive contexts. Recent Contributions: Recent studies include frameworks for benefit-cost-risk decision-making in self-adaptive systems, automated technical debt management using ML, and tools for tracing architecture-related debt. He collaborates internationally, contributing to standards like the Copenhagen Manifesto for human-centered AI in software engineering. Grants & Awards: While no specific awards are listed, his editorial role and frequent conference contributions reflect recognition in the field. He chairs conference tracks and oversees workshops, fostering early-career researchers and artifact evaluation. Labs & Teams: His group is part of the Bernoulli Institute, working on platforms like SDK4ED for embedded systems and tools such as DebtViz for technical debt monitoring. The team explores intersections between systems engineering and software architecture in complex systems-of-systems.

• Biomedical Signal Processing
• Cardiac Electrophysiology
• Sleep Disorders Research
• +۳ مورد دیگر

Associate Professor Mathias Baumert is affiliated with the University of Adelaide, where he holds a position in the School of Electrical and Mechanical Engineering under the Faculty of Sciences, Engineering and Technology. He leads the Health Technology research theme in the School of Electrical Electronic Engineering and specializes in biomedical signal processing, focusing on dynamic electrocardiography and sleep-related phenomena. His work integrates clinical applications and technological advancements to address challenges in cardiology and sleep disorders. His research interests include the physiological underpinnings of ventricular repolarization variability and its clinical implications, particularly in post-myocardial infarction patients and those with sleep-disordered breathing. He also develops brain-computer interface (BCI) systems for stroke rehabilitation, leveraging real-time EEG analysis and motor function recovery techniques. Collaborations with clinical partners such as the Women’s and Children’s Hospital, Adelaide Institute of Sleep Health, and the Victor Chang Cardiac Research Institute highlight his translational research focus. His recent articles emphasize signal processing applications for risk stratification in cardiovascular disease, sleep apnea, and diabetes. Key themes include nocturnal hypoxemic burden prediction, REM sleep dynamics, and the development of novel diagnostic markers using ECG and EEG data. His work often bridges engineering and medicine, aiming to translate findings into clinical tools like adaptive servo-ventilation treatment optimization and personalized BCI systems. No scientific awards or fellowships are explicitly listed in the provided texts. He is eligible to supervise Masters and PhD students but current advisee names are not available. His research projects are supported by grants such as ARC DP110102049 (as noted in some articles). He teaches courses including Biomedical Instrumentation and Introduction to Medical Technology . His facilities include ECG equipment, polysomnogram repositories, and a BCI workstation with 64-channel EEG capabilities. He collaborates on lab-based and clinical partner studies to advance cardiac sensing algorithms and sleep-related diagnostic technologies.

Kenneth Edwin Barkerمشاهده پروفایل

استاد

• Privacy Preserving Data Repositories
• Database Management Systems
• Data Privacy and Security
• +۴ مورد دیگر

Dr. Kenneth Edwin Barker is a Professor in the Department of Computer Science within the Faculty of Science at the University of Calgary, where he also serves as Director of the Institute for Security, Privacy and Information Assurance (ISPIA). His academic career spans several decades with significant contributions to database systems and privacy research. Dr. Barker earned his B.S. and M.S. in Computer Science from the University of Calgary in 1982 and 1984 respectively, followed by a Ph.D. in Computer Science from the University of Alberta in 1990. His educational background established the foundation for his extensive research career in database systems and information security. His primary research interests focus on Privacy Preserving Data Repositories , with specific attention to protecting privacy in mobile applications, understanding privacy's impact on data analytics, and architecting database management systems that inherently respect user privacy. His work also extends to distributed database environments, integration of legacy systems, and multidatabase environments. Dr. Barker's research bridges theoretical foundations with practical applications, making significant contributions to how privacy is implemented in real-world systems. An analysis of his recent publications reveals a strong trend toward practical privacy-preserving techniques for cloud data, social networks, and location-based services. His work consistently addresses the tension between data utility and privacy protection, developing innovative methods to maintain data value while safeguarding personal information. The publications span multiple subfields including encrypted search, graph privacy, high-dimensional data privacy, and privacy metrics. Best Paper Award at DBSec 2012 Best Paper Award at CODASPY 2012 Best Paper at BNCOD 2009 Dr. Barker has been instrumental in establishing privacy research infrastructure at the University of Calgary through his leadership of ISPIA. His research has attracted significant funding from various sources supporting privacy and security initiatives. While specific grant details aren't provided in the text, his extensive publication record indicates sustained research funding throughout his career. He has collaborated extensively with researchers both within and outside the University of Calgary, particularly with R. Alhajj and other colleagues on numerous projects. As Director of ISPIA, Dr. Barker oversees a research environment focused on advancing security and privacy technologies. The institute serves as a hub for interdisciplinary research, bringing together computer scientists, social scientists, and legal experts to address complex privacy challenges. His leadership has positioned the University of Calgary as a significant player in privacy research within Canada.

• Management Science
• Operations Management
• Mathematical & Quantitative Methods
• +۸ مورد دیگر

Professor Lilian M. de Menezes is a Professor of Decision Sciences at Bayes Business School within the Faculty of Management at City St George's, University of London. Her expertise spans Management Science, Operations Management, Statistics, and Energy Markets. She holds a BSc and MSc from Pontifícia Universidade Católica in Brazil and a PhD from London Business School. Lilian's research focuses on forecasting methodologies, energy market integration, quality management, and flexible work arrangements. She has contributed to studies on healthcare performance measurement, workforce optimization, and sustainability in business excellence models. Her work bridges academic research with practical applications in industries like energy and healthcare. She has received notable awards, including the 2015 EEX Excellence Award for Melanie Houllier's thesis on European electricity markets and the 2014 Best Paper Award for analyzing job satisfaction and quality management links. Her affiliations include the European Operations Management Association and the Royal Statistical Society. Lilian's research also explores flexible working policies and their impact on employee performance and well-being. Her recent work addresses challenges in energy market forecasting and sustainable organizational practices. She maintains a visiting appointment at ESCP Europe’s Research Centre for Energy Management.

Pablo Aragónمشاهده پروفایل

استاد مدعو

• Computational Social Science
• Social Computing
• Wikipedia Studies
• +۴ مورد دیگر

Pablo Aragón is a Research Scientist at the Wikimedia Foundation and an Adjunct Professor at Universitat Pompeu Fabra. His work bridges computational social science, civic technology, and technopolitics, with a focus on Wikipedia's governance, digital democracy tools, and participatory systems. He co-founded the Democratic Innovation Lab in Barcelona and the DatAnalysis15M research network. Key research interests include analyzing knowledge integrity in Wikipedia, configuring digital participatory budgeting systems, and studying platform effects in civic technologies. He has led projects like DECODE (decentralized citizen engagement) and contributed to platforms like Decidim, which empower participatory democracy in cities like Barcelona. Recent conference engagements include KDD 2024 (data mining), ICWSM 2024 (social media analysis), and Wikimedia CEE Meeting 2024. His work emphasizes cross-cultural collaboration, with studies published in ACM Transactions on Computer-Human Interaction and peer-reviewed conferences like CIKM and ACM SIGKDD. Professional affiliations include the Decidim association, Amnistía Internacional España, and the open knowledge advocacy group Civio. His research often intersects with open science, free culture movements, and gender equity in urban mobility.

Qiu, Jingjingمشاهده پروفایل

دانشیار

• Advanced Manufacturing
• Nanomaterials Synthesis
• Multifunctional Composites
• +۳ مورد دیگر

Dr. Jingjing Qiu is an Associate Professor in the Department of Mechanical Engineering at Texas A&M University (TAMU), leading the Advanced Materials & Manufacturing (AM²) Lab. Her research focuses on advanced manufacturing, nanomaterials, multifunctional composites, sustainable materials, energy harvesting, and healthcare applications. She holds a Ph.D. in Industrial & Manufacturing Engineering from Florida State University (2008), and M.S./B.S. degrees in Materials Science from Beihang University (2004/2001). Prior to academia, she gained 1 year of industrial experience as a Quality Engineer at SAIC Motor. Research interests include AI-driven nanomaterials synthesis, low-carbon manufacturing processes, and biomedical innovations such as drug delivery systems for brain tumors. The AM² Lab emphasizes interdisciplinary collaboration in materials science, data science, and sensor integration for energy and medical devices. Recent work highlights include AI-assisted microplastics removal, thermoelectric energy harvesting via graphene aerogels, and neuromorphic computing systems. Her team actively pursues postdoctoral and PhD candidates for research in energy/healthcare materials, requiring expertise in nanomaterials characterization (e.g., SEM, XPS, electrochemical techniques) and interdisciplinary problem-solving. Lab facilities support cutting-edge fabrication and testing of functional materials. Publications span over 15 years, with recent trends in sustainable manufacturing, soft robotics, and bio-inspired materials. Ongoing projects include DOE-funded initiatives on rare earth recycling and low-carbon ceramic production. No scientific awards are explicitly listed in the provided texts.

Martin Nordal Petersenمشاهده پروفایل

دانشیار

• Internet of Things
• Optical Networking
• Wireless Communication
• +۳ مورد دیگر

Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .

• Federated Learning
• Optimization for Machine Learning
• Privacy-Preserving Machine Learning
• +۱۲ مورد دیگر

Sai Praneeth Karimireddy is an Assistant Professor in the Thomas Lord Department of Computer Science at the University of Southern California (USC), with a courtesy appointment in the Ming Hsieh Department of Electrical and Computer Engineering. He previously held an SNSF postdoctoral fellowship at UC Berkeley under Michael I. Jordan and earned his PhD at EPFL advised by Martin Jaggi. He co-leads the Federated Learning and Data Quality working group at MONAI (NVIDIA) and collaborates with researchers at Apple Research. His research lies at the intersection of optimization, machine learning, statistics, and economics, with a strong focus on federated learning, privacy-preserving machine learning, data valuation, and AI for healthcare. He investigates how data quality, privacy, and incentives shape collaborative ML systems, especially in high-stakes domains like medicine. His work has been deployed at companies such as Meta, Google, OpenAI, and Owkin. His recent publications span top-tier venues including NeurIPS, ICML, ICLR, and JMLR, with influential contributions such as the SCAFFOLD algorithm for federated learning. His research shows a consistent trend toward building robust, private, and incentive-compatible collaborative learning systems, with increasing emphasis on real-world deployment in healthcare and decentralized data markets. 2023 SNSF Mobility Fellowship 2022 Patrick Denantes Memorial Prize for best thesis in computer science 2022 EPFL thesis distinction (top 8%) 2021 Chorafas Foundation Prize for exceptional applied research Capitol One Fellow (2025) He is actively mentoring PhD students and leads a research group focused on foundational and applied challenges in federated and privacy-preserving ML. He teaches graduate courses at USC, including CSCI 599 on Optimization for Machine Learning and CSCI 699 on Privacy-Preserving Machine Learning. He serves as an area chair for ICLR 2025 and co-organizes major workshops on incentives in data sharing and federated learning. His lab collaborates with institutions like NVIDIA, Apple, and Argonne National Laboratory, and he is building a research program centered on sustainable, equitable, and trustworthy AI ecosystems.

Yingfei Xiongمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages

Yingfei Xiong is an active Associate Professor at Peking University, China, specializing in software engineering and programming languages. With a consistent research trajectory from 2013 through 2026, Xiong has established themselves as a prominent figure in the software engineering research community, regularly contributing to top-tier conferences including SPLASH, ICSE, ASE, and PLDI. Dr. Xiong's research primarily focuses on program synthesis, automated program repair, and software analysis techniques. Their work bridges theoretical programming language concepts with practical software engineering applications, particularly in developing novel approaches for code generation, bug fixing, and program optimization. The research demonstrates strong interdisciplinary connections between traditional software engineering, programming languages theory, and emerging AI techniques. Analysis of Xiong's publication trends reveals a clear evolution in research focus, beginning with foundational work in API transformations and program adaptation around 2013-2016, shifting toward program repair techniques from 2017-2020, and most recently incorporating machine learning and neural approaches into program synthesis and repair (2021-2026). The work consistently addresses practical challenges in software development while maintaining theoretical rigor, with increasing integration of AI techniques in recent years. Dr. Xiong has served in various leadership roles across the software engineering conference ecosystem, including program committee membership and session chair positions at major conferences. Their extensive service demonstrates recognition by peers as a subject matter expert in software engineering and programming languages research. While specific grant information isn't detailed in the provided text, the sustained publication record suggests successful research funding.

Craig L. Justمشاهده پروفایل

استاد

• Use of sensors to measure water quality
• Freshwater mussels as living biosensors
• Fate of pharmaceuticals in wastewater treatment
• +۲ مورد دیگر

Craig L. Just holds the Donald E. Bently Professorship in Engineering and serves as a Professor in the Department of Civil and Environmental Engineering at the University of Iowa's College of Engineering. He also works as a Faculty Research Engineer at IIHR—Hydroscience and Engineering. With a PhD in Environmental Engineering and Science (2001) and an MA in Chemistry (1994), both from the University of Iowa and University of Northern Iowa respectively, his career spans over two decades of academic and practical contributions. Education: PhD, Environmental Engineering and Science, University of Iowa (2001) MA, Chemistry, University of Northern Iowa (1994) BS, Chemistry, University of Northern Iowa (1992) Dr. Just's research focuses on water quality monitoring through sensor technology, freshwater mussel biosensing , pharmaceutical contaminant removal , and PCB exposure analysis from dredging operations. His work bridges environmental engineering with ecological health and sustainable systems. Recent publications highlight trends in anaerobic digestion optimization , PCB emission characterization , and machine learning applications for biogas prediction. He has extensively studied constructed wetlands , nitrogen cycling , and flood risk mitigation in agricultural and urban contexts. As director of the Iowa Wastewater and Waste to Energy Research Program, he leads initiatives connecting bioremediation , smart infrastructure , and community engagement . His projects span from hydrological modeling in Iowa to international water programs in Honduras.

• Geomatics
• Cultural Heritage Documentation
• 3D Modeling
• +۵ مورد دیگر

Antonia Teresa Spano is a Full Professor at the Department of Architecture and Design (DAD) of Politecnico di Torino, Italy. She serves as Vice Coordinator of the PhD Program in Architectural Heritage and is a member of the Future Urban Legacy Lab (FULL). Her research focuses on geomatics, 3D modeling, and digital documentation for cultural heritage preservation. University: Politecnico di Torino Department: Department of Architecture and Design (DAD) Spano's work integrates advanced geomatic techniques like LiDAR, UAV photogrammetry, and SLAM-based modeling to address challenges in architectural and archaeological heritage documentation. Her expertise spans GIS, digital photogrammetry, and machine learning applications in conservation processes. Her recent publications emphasize multi-sensor 3D surveys for Pier Luigi Nervi's structures, AI-driven decay detection, and semantic classification of LiDAR data. These works align with SDG goals for sustainable cities and quality education. Scientific Awards: Premio Giovani CNR (2005) Miglior Poster at GISTAM (2016) and GEORES (2019) Fellow of CIPA Heritage Documentation (2023-2033), CIRAAS ETS (2020-2030), and ISPRS (2017-2024) Spano supervises PhD students in architectural heritage programs and leads numerous research projects, including collaborations with institutions like the Pompeii Archaeological Park, CRAST, and international universities. She has contributed to editorial boards and program committees of journals and conferences such as Virtual Archaeology Review and ISPRS symposiums.

Huadong Moمشاهده پروفایل

مدرس ارشد

• Power and energy systems
• Cyber-physical systems
• Manufacturing systems
• +۶ مورد دیگر

Dr. Huadong Mo is a Senior Lecturer at the School of Systems and Computing, University of New South Wales (UNSW) Canberra, Australia. He holds a B.E. degree in automation from the University of Science and Technology of China (2012) and a Ph.D. in systems engineering and engineering management from the City University of Hong Kong (2016). Prior to his current position, he was a research associate at ETH Zurich's Reliability and Risk Engineering Lab (2016-2019) and a Lecturer at UNSW Canberra (2019-2021). Dr. Mo's educational background includes a strong foundation in systems engineering with international experience across China, Switzerland, and Australia. His career trajectory demonstrates a progression from academic research to faculty positions with increasing responsibilities in teaching and research leadership. His research focuses on enhancing the resilience, performance, and security of complex systems using learning-based algorithms, primarily in power and energy systems, cyber-physical systems, and manufacturing systems. He applies data analytics to understand system evolution under uncertainties, with particular emphasis on prognostics and health management, sustainable transportation, robust operation of power systems under extreme events, and reinforcement learning-based asset management. His work bridges theoretical advances with practical applications in critical infrastructure. Analysis of Dr. Mo's recent publications reveals a strong focus on energy systems, particularly in the integration of machine learning with power grid management, battery storage systems, and resilience against cyber threats. His research shows a clear trajectory toward increasingly complex system integration, with growing emphasis on multi-vector energy communities, cross-domain prediction, and uncertainty-aware energy management. The interdisciplinary nature of his work spans electrical engineering, computer science, and operations research. 2024 IEEE SMC Early Career Award 2023 Visiting Research Fellowship (Jean d'Alembert Pour Fellowship) Gold Medal in 2024 China International College Student Innovation Competition (as supervisor) Arc PGC Supervisor Award (2021) IEEE SMC Outstanding Chapter Award (2021) Alumni Achievement Award from City University of Hong Kong (2019) Dr. Mo actively supervises numerous HDR students working on cutting-edge research topics including battery health monitoring, quantum control, reinforcement learning for power systems, and explainable AI for energy management. He leads multiple significant research grants totaling over 3 million AUD, including projects funded by ARC, Energy Innovation Fund, and international collaborations with institutions like ETH Zurich, Cambridge, and Tsinghua University. His research group maintains strong international connections, facilitating student exchanges and collaborative research. As Postgraduate Course Coordinator of Systems Engineering and Chair of IEEE SMC ACT Chapter, Dr. Mo plays a significant role in academic leadership and professional community building. His research team collaborates with industry partners on practical implementations of their theoretical work, particularly in the energy sector.

Nour Aliمشاهده پروفایل

عضو هیئت علمی

• Software Architecture
• Distributed Systems
• Adaptive Systems
• +۶ مورد دیگر

Dr Nour Ali is a Reader in the Department of Computer Science at Brunel University London , where she co-heads the Brunel Software Engineering Lab and serves as Vice-Dean of Education for the College of Engineering, Design and Physical Sciences. She holds a PhD in Software Engineering from Universidad Politecnica de Valencia, Spain, and a Major in Computer Science from Bir-Zeit University, Palestine. Research Interests: Software architecture for distributed and adaptive systems, integrating techniques like Model-Driven Engineering, Reverse Engineering, and Machine Learning. Teaching: Module leader for Software Project Management and supervisor of undergraduate group projects and final-year projects. Scientific Contributions: Over 70 publications in journals, conferences, and books. Key research areas include microservice architecture recovery, autonomic healthcare systems, and mobile self-adaptive architecture. Scientific Awards: Fellow of the Higher Education Academy (HEA). Membership: Deputy Editor-in-Chief for IET Software, member of multiple conference program committees, and reviewer for EPSRC, NWO, and other funding bodies.

Valeria Bruschiمشاهده پروفایل

پژوهشگر

• Audio Engineering
• Signal Processing
• Spatial Audio
• +۵ مورد دیگر

Valeria Bruschi is a Researcher at the Department of Information Engineering (DII) within the Faculty of Engineering at Università Politecnica delle Marche (UNIVPM) in Ancona, Italy. Her academic profile was last updated on April 13, 2024, and she maintains her office at the Engineering Faculty on via Brecce Bianche, with contact information including phone +39 071-220-4486 and email v.bruschi@staff.univpm.it. Dr. Bruschi's research spans multiple domains within audio and signal processing, with particular expertise in spatial audio systems, automotive human-computer interaction, and biomedical signal applications. Her work bridges theoretical signal processing techniques with practical implementations across diverse fields including automotive safety systems, hearing aid technology, sleep medicine, and agricultural monitoring. She has made significant contributions to head-related transfer function (HRTF) processing, real-time audio enhancement algorithms, and innovative monitoring systems that utilize acoustic signals for various applications. Analysis of Dr. Bruschi's recent publications reveals a strong trajectory in developing practical audio processing solutions with real-world applications. Her work shows increasing integration of machine learning techniques with traditional signal processing approaches, particularly in areas like driver monitoring systems, snoring detection and cancellation, and spatial audio rendering. A notable trend is her focus on creating lightweight, real-time implementations suitable for embedded systems and practical deployment scenarios, while maintaining high performance standards. Her research consistently demonstrates interdisciplinary collaboration, connecting audio engineering with fields as diverse as automotive safety, sleep medicine, and agricultural technology. Dr. Bruschi actively contributes to advancing audio engineering through her research on equalization techniques, noise reduction systems, and immersive audio technologies. Her work on pulse compression techniques for hearing aid distortion measurement represents an important contribution to audiological assessment methodologies. Her publication record demonstrates consistent scholarly output with increasing impact across multiple application domains, reflecting her ability to translate theoretical signal processing concepts into practical engineering solutions.

• Robotic Systems
• Intelligent Computing
• Artificial Intelligence
• +۳ مورد دیگر

Nuno Miguel Fonseca Ferreira is a Full Professor at the Instituto Superior de Engenharia de Coimbra (ISEC), part of the Polytechnic of Coimbra, where he currently serves as President of the Scientific Council. His academic career spans over 25 years at ISEC, progressing from Assistant to Professor Coordenador Principal. He has held significant leadership positions including Vice-President of ISEC (2001-2005), Pro-President of the Polytechnic of Coimbra (2009-2010), President of ISEC (2010-2013), and Vice-President of the Polytechnic of Coimbra (2013-2017), where he was responsible for internationalization initiatives. His educational background includes a degree in Electrical Engineering from the University of Porto (1996), a Doctorate in Electrical Engineering from the University of Trás-os-Montes and Alto Douro (2006), and a Habilitation Title (Aggregation) from the same institution (2020). His research focuses on Robotic Systems, with specialization in cooperative robotic systems as evidenced by his Habilitation work. Professor Ferreira's research spans multiple domains of robotics and intelligent systems, with particular emphasis on multi-robot coordination, environmental applications, and medical robotics. His work bridges theoretical control systems with practical applications across diverse fields including forestry, healthcare, manufacturing, and education. He has developed innovative approaches to robotic manipulation, sensor integration, and human-robot interaction, often incorporating advanced techniques from artificial intelligence and machine learning. His recent publications demonstrate a strong trend toward practical applications of robotics in real-world environments, particularly in forestry maintenance, industrial automation, and medical applications. The research shows progression from theoretical control systems to applied robotics in challenging environments, with increasing integration of computer vision, deep learning, and collaborative systems. His work spans both fundamental robotics research and immediate industrial applications, reflecting a balance between academic inquiry and practical implementation. Professor Ferreira has supervised two doctoral theses and participated in numerous research projects with substantial funding. His leadership extends to coordinating 15 of the 33 national and international R&D projects he has participated in, demonstrating significant grant acquisition and management capabilities. His international collaborations through Erasmus+ and other European programs highlight his role in fostering global research partnerships. He is an integrated member of GECAD (Research Group in Engineering and Intelligent Computing for Innovation and Advanced Development), a Portuguese R&D unit classified as Excellent by the Portuguese Science and Technology Foundation. Additionally, he is a member of LASI (Associated Laboratory for Intelligent Systems), the Portuguese laboratory associated with Artificial Intelligence, connecting him to a broader national research ecosystem.