جست‌وجوی استاد و پژوهشگر

• Medical Statistics
• Biostatistics
• Epidemiology
• +۳ مورد دیگر

Ruth Keogh is a Professor of Biostatistics and Epidemiology at the London School of Hygiene & Tropical Medicine (LSHTM), affiliated with the Medical Statistics Department within the Faculty of Epidemiology and Population Health. She is Co-Director of the Centre for Data and Statistical Science for Health (DASH) and serves as Departmental Research Degrees Coordinator. Her academic career has spanned roles from Lecturer (2012–2015) to Associate Professor (2015–2019) before attaining her current rank in 2019. Keogh holds advanced degrees including a DPhil in Medical Statistics/Epidemiology (University of Oxford, 2007), MSc in Applied Statistics (Oxford, 2003), and BSc in Mathematics and Statistics (University of Edinburgh, 2002). Her research focuses on causal inference, clinical trial emulation using real-world data, and applications in cystic fibrosis, infectious diseases, and public health. She leads projects on lung function trajectories, vaccine efficacy, and healthcare policy analysis. Her work integrates biostatistical methods with epidemiological studies, emphasizing rigorous analysis of observational data to inform clinical decisions. Notable areas include evaluating antibiotic treatments for cystic fibrosis patients, assessing diagnostic test accuracy for dengue and leptospirosis, and modeling vaccine effectiveness during the COVID-19 pandemic. She teaches courses in survival analysis, electronic health records, and health data science at LSHTM. Keogh has held leadership roles in the International Biometric Society and the STRATOS Initiative, and she has delivered keynote addresses at international conferences on trial emulation and biostatistical methods. Her contributions bridge methodological innovation and practical health challenges, with over 190 publications and active engagement in global health research networks.

Il Memming Parkمشاهده پروفایل

استاد

• Computational Neuroscience
• Neural Dynamics
• Machine Learning
• +۳ مورد دیگر

Il Memming Park is a Professor and Group Leader at the Centre for Restorative Neurotechnology within the Champalimaud Research division of the Champalimaud Foundation in Lisbon, Portugal. His work bridges computational neuroscience, machine learning, and statistical modeling to understand neural dynamics and computation. Dr. Park's research focuses on developing statistical and machine learning methods for analyzing neural time series data. His lab investigates the appropriate language for neural dynamics that can explain and generate specific predictions on neural data and behavior. He builds on foundations of dynamical systems and stochastic processes to create models of neural computation tightly tied to biology. His publications reveal a strong emphasis on developing methods like variational latent Gaussian processes and exponential family dynamical systems to extract meaningful patterns from complex neural recordings. His work spans both theoretical developments in computational methods and their application to real neural data from areas like visual cortex, parietal cortex, and other brain regions involved in perception and decision making. Dr. Park has previously held positions at Stony Brook University and the University of Texas at Austin, where he was affiliated with departments of Neurobiology and Behavior, Applied Mathematics and Statistics, Psychology, and Neuroscience. His lab at Champalimaud includes multiple PhD students, postdoctoral researchers, and research staff working collaboratively on various aspects of neural data analysis and modeling. The team employs an interdisciplinary approach combining neuroscience, statistics, machine learning, and dynamical systems theory.

• Artificial Intelligence for Power Systems
• Smart Grids
• Energy Management
• +۴ مورد دیگر

Zita Vale is a Full Professor at the Institute of Engineering (ISEP) of the Polytechnic of Porto (IPP), where she holds the first Full Professor position since 2017. She is a co-founder of GECAD (1999) and coordinates GECAD's Power and Energy (PES) activities. GECAD is recognized by FCT since 2004 and classified as Excellent. She has served as GECAD director (2010-2017), vice-director (1999-2009, 2017-present), and is a member of the administration board. She is also co-founder and member of the coordination board of the National Associated Laboratory on Intelligent Systems. Her educational background includes a PhD (1993) and Agregação/Habilitation (2003) in Electrical and Computer Engineering from the University of Porto. She began her academic career at the University of Porto as a Teaching Monitor (1985), Assistant (1985-1993), and Professor (1993-1998) before moving to ISEP in 1998. Zita Vale's research focuses on the design and development of artificial intelligence-based models for Power and Energy Systems. Her work spans knowledge-based systems, multiagent systems, machine learning, metaheuristics, and semantics, with applications in smart grids, energy management, electricity markets, and renewable energy integration. She has an extensive international network and has participated in 80 R&D projects, raising over 22 million Euros for GECAD. Her recent publications demonstrate a strong emphasis on optimization techniques, explainable AI, energy storage systems, and the integration of distributed energy resources in power systems. She serves as Editor-in-Chief of Applied Energy (Elsevier), a leading journal in the field with an Impact Factor of 11.2. Her citation metrics are impressive, with over 17,000 citations on Google Scholar and an H-index of 64. Editor-in-Chief of Applied Energy (Elsevier) Over 17,000 citations on Google Scholar H-index of 64 Zita Vale has supervised 29 PhD students (25 completed) and 72 MSc students (66 completed), demonstrating her strong commitment to academic mentorship. She has also been involved in numerous international and national evaluation processes, including project proposals, faculty positions, and PhD juries across 15+ countries. She has contributed to over 225 evaluation processes from 2018-2023, including 150+ project proposals/execution, 50+ Faculty/Researchers positions, 2 Habilitation juries, and 25+ PhD juries. She leads GECAD's involvement in several major research initiatives, including the National Associated Laboratory on Intelligent Systems and various European projects such as IoTalentum, TRADERES, DOMINOES, and EcoRural-IoT from Horizon 2020, as well as PRODUTECH EU DIH from Horizon Europe. Her leadership extends to international organizations where she serves as President of Intelligent Systems Applications in Power (ISAP) and Technical Committee Program Chair of IEEE PES Analytic Methods for Power Systems Committee.

• Machine Learning
• Electrical Engineering
• Computer Science
• +۳ مورد دیگر

Luís Miguel Mendonça Rato is an Associate Professor at the Universidade de Évora and a Senior Researcher with a PhD at Centro ALGORITMI. He is affiliated with the CST R&D Group and VISTA Lab R&D Lab, focusing on interdisciplinary research at the intersection of Electrical Engineering, Computer Science, and Agricultural/Biomedical applications. Academic Degree: PhD Current Position: Associate Professor Labs: VISTA Lab Researcher IDs: ORCID 0000-0003-4492-7548, ResearcherID A-9152-2013, CiênciaID A914-6344-CD2D His research spans machine learning applications in Agricultural Engineering (Sentinel-2 satellite data for nutrient analysis), Biomedical Imaging (MRI-ADC texture analysis for tumor classification), and Control Systems (predictive control algorithms for water delivery canals and solar fields). With an h-index of 11 and 51 publications, his work emphasizes hybrid systems combining traditional engineering with computational innovation. Recent publications highlight trends in SLAM efficiency (2024), cloud service optimization (2022), and deep learning for medical imaging (2022-2023). He has contributed to Smart Cities initiatives through projects like M-Traffic (2006) and NanoSen-AQM (2020). As a senior researcher, he leads projects in the CST R&D Group and VISTA Lab , with notable work in the Universidade de Évora ecosystem.

• Macroeconomic modeling of health disorders
• Infectious disease economics
• Computable General Equilibrium (CGE) Modeling
• +۷ مورد دیگر

Dr Marcus Keogh-Brown is an Associate Professor in the Department of Global Health and Development within the Faculty of Public Health and Policy at the London School of Hygiene & Tropical Medicine (LSHTM). His position is split between research focusing on macroeconomic modeling of health and serving as Deputy Programme Director for the school's public health distance learning program. Education: BSc in Mathematics and Statistics, Queen Mary University of London (1995-1998) MSc in Computer Studies, University of Essex (1998-1999) PhD in "A Statistical Model of Internet Traffic," Queen Mary University of London (1999-2004) PGCILT Modules 1 and 2, London School of Hygiene and Tropical Medicine (2008-2012) Dr Keogh-Brown's research focuses on analyzing the macro-economic impact of health disorders and developing macro-economic models in health contexts. His areas of interest include infectious diseases (SARS, influenza, COVID-19, tuberculosis, malaria) and non-communicable diseases (Alzheimer's Disease, Dementia). He specializes in health-related applications of Computable General Equilibrium (CGE) Modeling with GAMS, with current work on health and macroeconomic modeling of COVID-19, tuberculosis, child labor, and health-related food policies. His publication record shows a strong trend toward integrated macroeconomic-epidemiological modeling, particularly for infectious disease outbreaks and public health interventions. Recent work focuses on tuberculosis in India, Covid-19 impacts in Pakistan, and food policy interventions like the UK Soft Drinks Industry Levy. His research consistently applies economic modeling frameworks to evaluate the health and economic impacts of disease and health policies across multiple countries including Ghana, India, Thailand, Myanmar, UK, and China. Grants: Current: "Modelling the health social care and macroeconomic impacts of dementia policies in the UK" (NIHR, 2025-2026) Current: "Co-designing food system fiscal policy for healthy people and planet" (University of Oxford, 2022-2025) Completed: "COVID-19 vaccine scenario analysis for health economic and social impacts" (WHO, 2022) Completed: "Evaluation of the impact of the UK industry levy of sugar-sweetened beverages" (University of Cambridge, 2017-2023) Completed: "Macroeconomic Burden of Alzheimers in China" (Jansen Global Services LLC, 2014-2015) Dr Keogh-Brown is affiliated with several research centers at LSHTM including the Malaria Centre, Global Health Economics Centre, and Centre for Mathematical Modelling of Infectious Diseases. His collaborative work spans multiple countries and addresses critical intersections between health, economics, and policy.

Leid Zejnilovicمشاهده پروفایل

استادیار

• Technology and Innovation Management
• Human-Computer Interaction
• Machine Learning
• +۳ مورد دیگر

Leid Zejnilovic is an Assistant Professor at Nova School of Business and Economics (Nova SBE), where he co-founded the Data Science Knowledge Center and serves as Academic Director, and co-founded the Open and User Innovation Knowledge Center as Scientific Deputy Director. He also co-founded the Patient Innovation platform, enabling patients and caregivers to share self-made healthcare solutions. With a double PhD from Carnegie Mellon University and Católica-Lisbon School of Business and Economics, his career spans over 20 years of international consulting, academic entrepreneurship, and teaching at institutions like Imperial College Business School and Ludwig Boltzmann Institute. PhD in Strategy, Entrepreneurship and Technological Change (Carnegie Mellon University / Catholic University of Portugal, 2014) Master in Engineering and Public Policy (Carnegie Mellon University, 2012) Master in Information Technology (Dzemal Bijedic University, 2007) Bachelor in Telecommunications (University of Sarajevo, 2002) His research focuses on Technology and Innovation Management, Human-Computer Interaction, and data-driven solutions across healthcare, tourism, and education. He has published extensively in journals like California Management Review , PLoS ONE , and Marine Policy , with recent work analyzing big data in tourism, machine learning for oral health, and pandemic impacts on fisheries. As an Associate Editor for Data & Policy Journal , his contributions bridge academic research and real-world applications. Co-founding the Data Science for Social Good Foundation and leading over 100 talks in industry and academia, Zejnilovic's career emphasizes translating innovation into social and economic impact through platforms, policy, and education.

Joe Patonمشاهده پروفایل

استاد

• Neural Mechanisms of Time
• Interval Timing
• Rodent Neurophysiology
• +۵ مورد دیگر

Joe Paton is a Professor and Principal Investigator at the Champalimaud Neuroscience Programme, Champalimaud Foundation in Lisbon, Portugal. He leads the Paton Lab which focuses on understanding how animals determine which environmental cues are predictive of behaviorally relevant events, known as the credit assignment problem. His research combines behavioral experiments with neurophysiological recordings in rodents to investigate neural mechanisms of time perception and decision making. Dr. Paton's research interests center on interval timing, temporal processing in the brain, and the neural basis of learning. His work particularly examines how the striatum and dopamine systems contribute to time perception and how animals solve the credit assignment problem through statistical inference in the time domain. His lab employs advanced techniques including optogenetics, neural recordings, and computational modeling to address these questions. Analysis of Dr. Paton's recent publications reveals a strong focus on striatal function in timing processes, with particular attention to how neural populations encode temporal information. His work bridges behavioral neuroscience with computational approaches, demonstrating how timing mechanisms influence decision making and learning processes. The research spans multiple levels from cellular mechanisms to behavioral outputs. Midbrain dopamine neurons control judgment of time (2016) Striatal dynamics explain duration judgments (2015) A Scalable Population Code for Time in the Striatum (2015) The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions (2018) Dr. Paton has mentored numerous PhD students and postdoctoral researchers through the INDP (International Neuroscience Doctoral Program) and supervises a diverse team including research technicians, postdocs, and students. His lab has contributed significantly to understanding the neural basis of time perception and its role in learning and decision making. The Paton Lab also develops experimental tools and frameworks like Bonsai for behavioral neuroscience research.

• Artificial Intelligence
• Healthcare Informatics
• Data Science
• +۵ مورد دیگر

Luís B. Elvas is an Assistant Professor at ISCTE-University Institute of Lisbon's Department of Social and Business Sciences (SINTRA) and a Research Assistant at ISTAR-Iscte Research Center. He holds qualifications including a Technical Specialization in TensorFlow for AI (Coursera, 2021) and certifications in IoT/Blockchain from ISCTE and cybersecurity from Palo Alto Networks. His research spans artificial intelligence, healthcare informatics, smart cities, and blockchain, with applied work in medical imaging, data sharing, and urban analytics. Research interests include: Healthcare AI : Developing deep learning models for cardiac diagnostics, medical imaging analysis, and blockchain-based health data systems Smart Cities : Implementing IoT solutions for urban mobility optimization, disaster management, and sustainable transportation Data Science : Creating predictive analytics frameworks for clinical decision support and urban planning His publications demonstrate a strong focus on AI-driven healthcare solutions (67% of recent works) and smart city technologies (33%), with emerging interests in blockchain and NLP. Research consistently targets real-world applications in clinical settings and urban environments. Awards: Award for best internship, Order of Engineers (2022) Distinction for best internship, Order of Engineers (2021) He leads/contributes to multiple EU research consortia including AMR-EDUCare (antimicrobial resistance education), NEEM (e-health in Nepal), and Blockchain.PT. Coordinates the IEEE Computational Intelligence Society Student Branch Chapter at ISCTE and developed the ManagiDiTH master's program in digital health transformation.

Pedro Oliveiraمشاهده پروفایل

استاد

• Open and User Innovation
• Patient Innovation
• Social and Impact Innovation
• +۳ مورد دیگر

Pedro Oliveira is a leading academic and administrator with diverse roles across institutions. He currently serves as Dean at Nova School of Business and Economics , where he holds the Cascais Chair in Operations, Technology, and Innovation Management . Additionally, he is a Professor MSO at Copenhagen Business School , Academic Fellow at Cornell University , and Adjunct Professor at MIT Sloan School of Management . He also founded the Patient Innovation platform and co-founded PPL Crowdfunding . Education: Ph.D. in Operations, Technology, and Innovation Management (2004), University of North Carolina at Chapel Hill M.Sc. in Operations Research and Systems Engineering (2000), Instituto Superior Técnico Licenciatura in Naval Engineering (1996), Instituto Superior Técnico Research Focus: Pedro Oliveira's work centers on Open and User Innovation , Patient Innovation , and Social and Impact Innovation , with a strong emphasis on Service Operations Management and Artificial Intelligence in Innovation . His studies often bridge Technology Strategy with Healthcare and Financial Services , exploring how users can drive innovation in resource-constrained environments. Publication Trends: His recent works emphasize collaborative innovation in public and semi-public domains , patient-driven healthcare solutions , and user innovation in digital finance . He has also published extensively on knowledge commons and innovation during crises , such as the COVID-19 pandemic . Leadership and Advisory Roles: Pedro has held significant administrative roles, including Senior Associate Dean for Faculty & Research and Director of the Research Unit in Business and Economics . He has advised the Portuguese Ministry of Science, Technology, and Higher Education and served on the Environment & Sustainability Council at EDP Energias de Portugal . He is also the President of the Open and User Innovation Society and a counselor on the National Council for Science, Technology, and Innovation (CNCTI) and Economic and Social Council (CES) in Portugal. Labs and Teams: As founder of Patient Innovation , he has established a global platform for user-driven healthcare solutions. His work also includes collaborative digital health initiatives , such as the Saúde.Come Senior program addressing food insecurity in elderly populations through TV-based eHealth interventions.

• Manufacturing Management
• Production Planning
• Production Control
• +۱۴ مورد دیگر

Maria Leonilde Rocha Varela is an Associate Professor with Habilitation at the School of Engineering, University of Minho, Portugal, where she also serves as a Senior Researcher at the Algoritmi Research Centre. She has been an integrated member of the Algoritmi Research Centre since 2012 and works in the Department of Production and Systems. Dr. Varela earned her degree in Production Engineering from the University of Minho in 1994, completed a Master's in Computer Integrated Production at DPS-UMinho in 1999, and received her Ph.D. in Production and Systems from the University of Minho in 2007. Her primary research focuses on Manufacturing Management, particularly Production Planning, Control and Optimization, and Collaborative Paradigms, Networks and Decision Making Models. She maintains extensive international collaborations with institutions worldwide including the National Institute of Industrial Engineering, VSB-Technick Univerzita Ostrava, University of Belgrade, and others. Her research spans Web Applications and Services for supporting Engineering and Production Management, with increasing emphasis on Artificial Intelligence, Robotic Process Automation, and Industry 4.0/5.0 applications. She has made significant contributions to scheduling algorithms, optimization techniques, and decision support systems for manufacturing environments. Analysis of her recent publications reveals a strong trend toward integrating Artificial Intelligence with traditional manufacturing processes, particularly in Robotic Process Automation applications. Her research increasingly focuses on sustainable manufacturing practices, with numerous publications addressing energy efficiency, environmental sustainability, and resource optimization. There is a clear emphasis on multi-objective optimization approaches to solve complex manufacturing problems, particularly in distributed job shop scheduling. Her work demonstrates an evolution from traditional production planning methods to more advanced AI-driven approaches for Industry 4.0 and 5.0 environments. Dr. Varela has held significant academic leadership roles, currently serving as the director of the master's course in Engineering and Quality Management at DPS-UMinho. She previously coordinated the industrial management and systems subgroup from 2012 to 2021 and was part of the steering committee for the master's course in systems engineering between 2016 and 2019. She has successfully supervised more than 70 MSc projects, with over 15 currently ongoing, focusing on Production and Systems Engineering. Her supervision encompasses collaborative management models, traditional decision approaches, and web-based platforms incorporating AI techniques. She coordinates research projects including 2 concluded Ph.D. projects and 6 ongoing ones. She collaborates as a research member in several R&D projects with national and international industrial enterprises and institutions, and in international Erasmus projects. Dr. Varela is an active participant in the academic community, serving on editorial boards of several international journals and as a member of organizing and scientific committees for numerous international conferences. She is a member of several prestigious research networks including the Euro Working Group of Decision Support Systems (EWG-DSS), Institute of Electrical and Electronics Engineers (IEEE), Industrial Engineering Network, and the Institute of Industrial and Systems Engineers (IISE).

Carla Curadoمشاهده پروفایل

دانشیار

• Knowledge Management
• Human Resource Management
• Organizational Behavior
• +۳ مورد دیگر

Carla Curado is an Associate Professor with Habilitation in Organizational Behavior and Human Resource Management at ISEG – Lisbon School of Economics and Management, University of Lisbon. She serves as a founding researcher at the ADVANCE research center and holds leadership roles including Master's Program Coordinator for Human Resource Management and Business Sciences. She represents the University of Lisbon at the International Organization for Standardization and is an Associate Editor for the Journal of Organizational Effectiveness: People and Performance . Her research explores: Knowledge Management in healthcare, SMEs, and NGOs Digital leadership and workplace happiness HRM's role in innovation and sustainability Mixed-method approaches to organizational analysis Recent publications (2023-2025) emphasize digital transformation, healthcare efficiency, and methodological innovations in operations management. Key trends include configurational analysis of leadership and knowledge behaviors in hybrid work environments. Awards: Stanford's Top 2% World Scientist (2021, 2022, 2023) She supervises 65+ Master's students with theses on: Knowledge sharing mechanisms Leadership/organizational commitment Healthcare workplace dynamics Sustainability in HR practices At ADVANCE Research Center, she contributes to teams studying management innovation and organizational resilience, with active participation in EU research consortia.

Jan Theeuwesمشاهده پروفایل

استاد

• Visual Attention
• Perception
• Statistical Learning
• +۷ مورد دیگر

Jan Theeuwes is a full Professor and current Head of Department at Vrije Universiteit Amsterdam's Department of Cognitive Psychology. With over 250 peer-reviewed publications, he leads research in visual attention, statistical learning, and distractor suppression mechanisms. His work bridges fundamental cognitive science with practical applications in road design and human factors. His educational background includes: BSc in Mechanical Engineering (1981) BSc and MSc in Experimental Psychology with highest honors (cum laude) from Tilburg University (1987) PhD from Vrije Universiteit with highest honors (1992) Theeuwes' research focuses on fundamental knowledge acquisition regarding perception, attention, memory, and emotion using diverse methodologies including behavioral measurements, eye tracking, fMRI, psychophysiological recordings, patient studies, and computational modeling. His specific contributions span attentional and oculomotor capture, working memory, multimodal integration, remapping, face perception, visual search, emotion processing, unconscious processing, the attentional blink, reward processing, and applied road design research. His recent work demonstrates how statistical learning shapes attentional selection by creating predictive models of where and when to expect relevant information. Analysis of his recent publications reveals a strong focus on the neural and behavioral mechanisms of learned distractor suppression, with particular emphasis on how statistical regularities in the environment shape attentional priority maps. His research increasingly integrates electrophysiological methods with behavioral paradigms to uncover the temporal dynamics of attentional selection and suppression processes. His notable scientific achievements include: Election to the Royal Dutch Academy of Science (KNAW) in 2010 Receiving the first Bertelson Award for outstanding psychological research from the European Society for Cognitive Psychology in 2001 Serving as president of ESCOP (European Society for Cognitive Psychology) from 2016 to 2018 Theeuwes serves as principal advisor to the Dutch Department of Transportation (Rijkswaterstaat) regarding road design and signing. In 2023, he co-founded Attention Architects with two former PhD students, a company applying eye-tracking research to practical settings. His work has received substantial research funding supporting his investigations into attentional mechanisms and their real-world applications. Theeuwes has established collaborations across multiple institutions and mentored numerous researchers who have gone on to establish their own careers in cognitive science. He leads the Cognition Team at Vrije Universiteit Amsterdam, which investigates fundamental attentional processes using cutting-edge methodologies. The team maintains strong connections with applied research settings through projects with government agencies and industry partners, particularly in transportation safety. Their current work focuses on how statistical learning dynamically shapes attentional selection in complex visual environments.

Minjoon Seoمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Minjoon Seo is an Associate Professor at KAIST AI, Korea Advanced Institute of Science and Technology. He holds a BS in Electrical Engineering & Computer Science from UC Berkeley and previously worked as a software engineer at Oracle. His research focuses on natural language understanding, large-scale end-to-end question answering, and multimodal AI systems combining language and vision. Research Interests: His work spans Natural Language Processing, Machine Learning, Deep Learning, and Language-Vision integration. He develops neural network architectures for machine comprehension and multimodal understanding, with applications in question answering systems and diagram interpretation. Publications: His research demonstrates a consistent focus on multimodal AI systems, with recent works advancing neural approaches to machine comprehension and diagram understanding. Publications show strong emphasis on NLP-CV integration and practical applications in healthcare and education. Awards: Best Paper Nomination at UbiComp 2014 for BiliCam research Professional Activities: Maintains active open-source contributions through GitHub repositories related to question answering systems and NLP research. Co-founded Config Intelligence while maintaining academic position.

Nuno Luis Madureiraمشاهده پروفایل

استاد

• Energy History
• Environmental History
• Economic History
• +۱۵ مورد دیگر

Nuno Luis Madureira is a Full Professor in the Department of History at ISCTE – Lisbon University Institute, where he is also an Integrated Researcher at CIES-Iscte – Center for Research and Studies in Sociology. His academic affiliations include the School of Social Sciences and Humanities and the research group Historical Dynamics and Global Integration of the World . He has been a visiting scholar at Harvard University and the University of California, Berkeley, and serves on the review boards of the European Science Foundation, Research Foundation – Flanders (FWO), and the Netherlands Organization for Scientific Research (NWO). Madureira holds a PhD in Contemporary Social History from ISCTE-IUL (1996), a Master’s in Historical Economics and Sociology from the Faculty of Social Sciences and Humanities at UNL (1990), and a Bachelor’s in History from the Faculty of Arts at UL (1984). His research spans energy and environmental history, economic and business history, the history of technology and science, and historical occupations. He has authored thirteen books, including Key Concepts in Energy: Technology, Economy and History (Springer, 2014), and numerous peer-reviewed articles in journals such as Energy Policy , Technology & Culture , Business History Review , and Environment and History . His recent publications reflect a deep engagement with energy transitions, fossil fuel history, nuclearization, and the socio-political dimensions of energy systems. Themes such as energy paradoxes, oil pricing, and the historical development of electricity infrastructure recur throughout his work. He has also contributed to major encyclopedias and edited volumes in economic and social history. Madureira is the editor of Frontiers in Sustainability and has coordinated multiple collective research projects. He maintains an active research blog and is fluent in French and English. His work is interdisciplinary, combining historical analysis with insights from economics, engineering, and environmental sciences. Scientific Awards and Recognitions: Member of the permanent pool of referees of the European Science Foundation (2006–2013) Member of the College of Reviewers of the European Science Foundation (2016–2023) Member of the Research Foundation – Flanders (FWO) Review College Consultant for the Netherlands Organization for Scientific Research (NWO) He has advised on research policy and evaluation at national and European levels and is a member of ISCTE's General Board. His work on historical occupations and classification systems has been foundational in Portuguese social history. He has not advised any named PhD or Master’s students in the provided texts. He is not part-time, not retired, and currently active in research and teaching.

Claudio Tebaldiمشاهده پروفایل

دانشیار

• Financial Economics
• Derivative Pricing
• Risk Management
• +۴ مورد دیگر

Claudio Tebaldi is an Associate Professor at Università Bocconi , specializing in financial economics and quantitative methods. He serves as Managing Editor of Quantitative Finance and has collaborated with institutions including UCLA, NYU, the Federal Reserve Board, and ECB. Education : Ph.D. in Statistical Mechanics from SISSA; Master in Economics and Finance from Venice International University His research spans financial economics (asset/derivative pricing, risk management) and mathematical/physical sciences (complexity theory, collective phenomena). He employs advanced statistical methods like machine learning and big data analysis to develop decision rules for uncertain environments. Key publication themes include computational finance (2025), pension economics (2024), network-based financial contagion (2024), and optimal trading algorithms (2024). Earlier works focus on econometric theory (2023) and risk measurement frameworks (2022). Scientific Recognition : Excellence in Research Award (2023), Best Paper in Derivatives (NFA 2019), Best Paper (Swiss Econometrics and Finance Society meeting 2007)