جستجوی استاد راهنمای دانشگاهی

Rui Soares Barbosaمشاهده پروفایل

پژوهشگر

• Quantum Foundations
• Quantum Computer Science
• Mathematics of Quantum Theory
• +۶ مورد دیگر

Rui Soares Barbosa is a Staff Researcher at the Quantum and Linear-Optical Computation group at the International Iberian Nanotechnology Laboratory (INL). He holds a BSc in Computer Science from Universidade do Minho (2009), an MSc in Mathematics and Foundations of Computer Science from the University of Oxford (2010), and a DPhil in Computer Science from Oxford (2015) with a thesis on Contextuality in quantum mechanics and beyond. Prior to joining INL, he held post-doctoral positions at Oxford (2015–2019) and the University of Edinburgh (2019–2020), and a Research Fellowship at the Simons Institute for the Theory of Computing, UC Berkeley (2017). Barbosa's research lies at the intersection of Computer Science, Physics, and Mathematics, focusing on quantum foundations, quantum computer science, and the mathematics of quantum theory. His work emphasizes logical, structural, and compositional aspects, particularly investigating non-locality and contextuality - phenomena that distinguish quantum theory from classical physics and have been linked to quantum informatic advantage. He employs mathematical tools from category theory, logic, probability, algebraic topology, and operator algebras to achieve a structural understanding of quantum systems' non-classical features. His recent publications demonstrate a strong focus on contextuality as a quantum resource, exploring its connections to causality, computational advantage, and logical structures. The research spans theoretical foundations to practical quantum computing applications, with particular attention to mathematical frameworks like sheaf theory that elegantly express quantum contextuality. His work often involves collaborations with leading researchers in quantum foundations and theoretical computer science. Barbosa actively advises multiple PhD and MSc students including Angelos Bampounis, Rafael Wagner, Nico Witrock, and others. His research group at INL, the Quantum and Linear-Optical Computation group, conducts cutting-edge research at the intersection of quantum theory and computer science, regularly presenting findings at major conferences like the International Conference on Quantum Physics and Logic (QPL).

• Information Systems
• Operations Management
• Business Strategy
• +۵ مورد دیگر

Henrique O'Neill is an Associate Professor (with Habilitation) in the Department of Marketing, Operations and General Management at ISCTE - University Institute of Lisbon, Portugal. He is an Integrated Researcher at ISTAR-Iscte - Research Center in Information Sciences, Technologies and Architecture. His research focuses on information systems adoption, organizational strategy, and process optimization in healthcare, finance, and public administration. Education: PhD in Business Organization and Management - University of Cranfield (1995) Master's in Electrical and Computer Engineering - Higher Technical Institute (1987) Bachelor's in Electrical Engineering - Higher Technical Institute (1983) Research Interests: His work spans business/IT strategy, systems modeling, process analysis, and technology implementation. Key domains include healthcare informatics, banking systems, and Industry 4.0 applications. He emphasizes practical solutions for organizational performance through technology integration. Publication Trends: Recent articles explore intelligent business systems, telemedicine, design science methodologies, and supply chain innovation. His work consistently bridges theoretical frameworks with sector-specific applications in healthcare, education, and logistics. Professional Engagement: Member: Portuguese Telemedicine Association, Order of Engineers Commissioner: INEM (National Institute of Medical Emergency) reform study Director: Center for IT Development (2010-2014) Advising & Projects: Supervises 7 graduate students (1 PhD, 6 Master's). Leads EU-funded projects including: Atlantic Crossing (2024-2025): US-Portugal academic collaboration in AI/cybersecurity AAL4ALL (2011-2015): Ambient Assisted Living ecosystem UNITE (2000-2002): Ubiquitous teamwork platforms

Juho Leeمشاهده پروفایل

دانشیار

• Bayesian deep learning
• Bayesian inference
• meta learning
• +۵ مورد دیگر

Juho Lee is an Associate Professor at the Kim Jaechul Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST). Previously, he worked as a research scientist at AITRICS and completed his PhD in Computer Science & Engineering at Pohang University of Science and Technology (POSTECH) under Professor Seungjin Choi, followed by postdoctoral research at University of Oxford with Professor François Caron. His research focuses on: Bayesian deep learning Bayesian inference Meta learning Generative models Uncertainty quantification Graph representation learning Professor Lee's work bridges theoretical Bayesian methods with practical deep learning applications. His recent publications demonstrate significant contributions to neural processes, Bayesian optimization, and scalable inference methods. He has developed novel architectures like Set Transformer for permutation-invariant modeling and advanced techniques for uncertainty quantification in deep networks. His research shows a clear trajectory toward making Bayesian principles applicable to large-scale, real-world machine learning problems. Notable contributions include: Set Transformer: A framework for attention-based permutation-invariant neural networks (ICML 2019) Bootstrapping neural processes (NeurIPS 2020) Deep amortized clustering (NeurIPS 2019 workshop) Learning to pool in graph neural networks for extrapolation Professor Lee actively mentors graduate students and has advised numerous PhD candidates who co-author papers with him across NeurIPS, ICML, and ICLR. His research group SIML@KAIST develops scalable and interpretable machine learning methods with strong theoretical foundations.

• 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.

Julien Diogoمشاهده پروفایل

استاد مدعو

• Neuromarketing
• Consumer Behavior
• Applied Cognitive Neuroscience
• +۵ مورد دیگر

Julien Diogo serves as Adjunct Professor at Polytechnic Institute of Viseu's School of Education of Viseu since 2020, teaching Market Analysis, Consumer Behavior, Strategic Communication, and Innovation/Creativity courses. He concurrently holds Visiting Professor positions at ISAG (Higher Institute of Administration and Management) since 2018 for Executive MBA programs and was Professor of Organizational Communication at ISCA-UA (2022-2023). His academic roles extend to Visiting Facilitator positions at Brazil's Personal Branding Academy and ISLA's Postgraduate Program in Innovation. His educational background includes: PhD in Communication Sciences (in progress, 2023-2026) at University of Coimbra Specialization in Teacher and Trainer Training (2022-2023) from Employment and Training Institute of Braga Marketing Specialist title (2019) from Polytechnic Institute of Viseu Master's in Communication and Marketing (2010-2012) from Polytechnic Institute of Viseu (Final Grade: 17/20) Bachelor's in Social Communication (2005-2008) from Polytechnic Institute of Viseu (Grade: 17/20) Diogo's research integrates neuromarketing with consumer behavior analysis, focusing on emotional responses in digital environments, Generation Z consumption patterns, and neuroscience applications in place branding. His work examines how cognitive processes influence purchasing decisions through physiological measurements and behavioral experiments, particularly investigating caffeine's neuropharmacological effects on consumer arousal and shop window design's attentional impact. He bridges theoretical neuroscience with practical marketing strategy development. His publication trajectory reveals increasing focus on digital-emotional consumer interfaces, with recent work analyzing pandemic-era behavior shifts and Gen Z's narrative processing. Key thematic clusters include neuromarketing validation in retail architecture, emotional sustainability in e-marketplaces, and neuroscientific foundations of territorial branding, demonstrating consistent application of cognitive neuroscience to contemporary marketing challenges. Scientific recognition includes: 2008 Academic Merit Award for Best Social Communication Student (Polytechnic Institute of Viseu) 2021 Nomination for Global Teacher Prize Portugal Diogo actively supervises master's research including thesis on territorial brand communication (2024), language informality in digital contexts (2024), and Apple's Lovemarks strategy for Generation Z (2024). He contributes to research projects like INOV C+ Intelligent Innovation Ecosystem (2024-present) and co-orientated neuromarketing studies on advertising reception decoding (2020). His academic service includes peer review for IGI Global and International Journal of Marketing. Through his dual leadership as CCO of ICN Agency (neuromarketing consultancy), co-director of PsicoSoma (publishing/training), and expertMind (LMS platform), Diogo maintains robust industry-academia integration, developing neuromarketing frameworks applied across retail, urban planning, and digital experience design contexts.

João Magalhãesمشاهده پروفایل

استاد

• Vision and Language Understanding
• Multimodal Information Understanding
• Multimodal Conversational AI
• +۵ مورد دیگر

João Magalhães is a Full Professor in the Department of Computer Science at the Faculty of Science and Technology, Universidade NOVA de Lisboa, Portugal. He serves as Group Coordinator of the Multimodal Systems Group at the NOVA Laboratory for Informatics and Computer Science and leads the NOVASearch research group at FCT/UNL. His research focuses on vision and language information understanding, with particular emphasis on multimodal information understanding, multimodal conversational AI, multimedia search and summarization, temporal and memory models, and social media information quality. His work spans both theoretical foundations and practical applications across web, social media, and clinical domains. Analysis of his recent publications reveals a strong trajectory in multimodal conversational AI systems, with increasing sophistication in handling both voice and visual inputs. His research has evolved from foundational work in cross-modal embeddings to advanced large language models for dual-goal conversational settings, demonstrating consistent innovation in the field of multimodal understanding. 1st prize winner of the second Alexa TaskBot Challenge (2023) Award-winning solution in the Alexa TaskBot Challenge (2022) Best paper award at the Portuguese NLP conference (PROPOR) (2020) Best paper nominations at ACM conferences (2018) Professor Magalhães has advised numerous graduate students through the NOVASearch group and has secured substantial research funding through projects including Amazon Alexa TaskBot Challenge (2021-2023), iFetch (2020-2023), SmartyFlow (2017-2020), COGNITUS (2016-2019), GoLocal (2016-2020), QSearch (2012-2015), ImTV (2010-2013), and CS4SE (2010-2013). He actively serves the research community as ACM Multimedia 2026 Program Committee Chair and has held leadership roles in numerous conferences including ACM Multimedia 2022 General Chair and ECIR2020 General Chair. He leads the Multimodal Systems Group within the NOVA Laboratory for Informatics and Computer Science, where his team develops cutting-edge solutions for multimodal understanding with applications in conversational AI, multimedia search, and social media analysis.

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.

• Crowdsourcing
• Human-Computer Interaction
• Digital Health
• +۷ مورد دیگر

Simo Hosio is an Academy Research Fellow (2022-2027) and Professor of Computer Science and Engineering at University of Oulu's Center for Ubiquitous Computing, where he leads the Crowd Computing Research Group. He also maintains a visiting position at University of Tokyo, Japan. Having graduated as the first Finnish scholar under Microsoft Research Cambridge's Ph.D. scholarship program, he has published over 150 peer-reviewed scientific articles spanning two decades of research. Hosio's research spans three primary domains: crowdsourcing methodologies, human-computer interaction, and digital health applications. His work pioneers novel approaches to online labor markets, investigates the suitability of crowdsourcing for diverse applications, and explores HCI aspects of digital health solutions for chronic conditions. His research group, founded in 2020, has secured nearly two million USD in funding, demonstrating significant research impact and recognition. Analysis of Hosio's recent publications reveals a strong trend toward interdisciplinary research at the intersection of crowdsourcing, healthcare technology, and emerging AI systems. His work increasingly focuses on practical applications of crowd computing in health contexts, with growing attention to mental health, women's health, and workplace well-being solutions. The integration of AI and machine learning techniques with traditional HCI approaches represents another significant trajectory in his recent scholarship. Distinguished Paper Award (2024) Best Paper Honourable Mention Award (2022) PMCJ Best Research Paper (awarded in 2024) Best Paper Award (2022) Best Full Paper Award (2015) Honorable Mention Award (2014) Best Paper Presentation award (2010) As an educator, Hosio has taught Human-Computer Interaction (2019-2025) to over 260 students in 2024, Social Computing (2018-2021) to approximately 60 students annually, and Applied Computing (2015-2018) to around 50 students each year. His research group's nearly two million USD in secured funding demonstrates significant grant acquisition success, supporting innovative work at the intersection of crowd computing, health technology, and human-centered AI systems. The Crowd Computing Research Group, founded by Hosio in 2020, represents a significant research infrastructure focused on advancing methodologies for crowd-powered systems. The group's work spans from fundamental research on crowd labor markets to applied projects in healthcare, workplace well-being, and social computing, demonstrating a strong commitment to both theoretical advancement and practical impact.

• Complex Systems
• Computational Modeling
• Network Science
• +۷ مورد دیگر

Jorge Louçã is a Full Professor in the Department of Information Science and Technology at ISCTE-IUL, where he has been a faculty member since 2000. He is also an Integrated Researcher at ISTAR-Iscte, the Research Center in Information Sciences, Technologies and Architecture, and leads the research group The Observatorium . He holds a PhD in Computer Science and Artificial Intelligence from Université Paris Dauphine and the University of Lisbon, and completed his Aggregation in Complexity Sciences in 2019. PhD in Computing – University of Lisbon & Université Paris-Dauphine (2000) Master’s in Informatique: Intelligent Systems – Université Paris-Dauphine (1995) Aggregation in Complexity Sciences – ISCTE-IUL (2019) His research centers on computational modeling of social systems, focusing on data-intensive analysis of human communication, knowledge generation in large networks, and the dynamics of complex systems. He founded the Doctoral Program in Complexity Sciences and has been instrumental in advancing the field through international collaborations such as the UNESCO Unitwin network for the Complex Systems Digital Campus and participation in the Conference on Complex Systems (CCS/ECCS). The recent publications highlight a strong interdisciplinary focus, combining network science, data analysis, and social theory. Key themes include the modeling of malaria transmission, information diffusion in social media, structural inequality in education, and the dynamics of opinion and popularity. His work often employs agent-based models, temporal network analysis, and entropy-based measures, reflecting a deep integration of computational and theoretical approaches. Research Methods for Doctorate in Complexity Sciences Advanced Topics in Complexity Sciences Data Science Fundamentals Development for the Internet and Mobile Applications Web Interfaces for Data Management Advanced Network Analysis Jorge Louçã has supervised over a dozen doctoral and master’s students, with completed theses on topics such as malaria modeling, information diffusion, temporal networks, and social inequality. His research has been supported by projects like NESS (Non-Equilibrium Social Science in ICT and Economics), reflecting his leadership in interdisciplinary science. He has held significant academic management roles, including Director of the Department of Information Science and Technology and head of multiple degree programs. His work continues to bridge computer science, social science, and policy, positioning him as a key figure in the global complexity science community.

Mariela Martins Nolascoمشاهده پروفایل

پژوهشگر

• Computational Spectroscopy
• Deep Eutectic Solvents
• Polymer Structure Dynamics
• +۳ مورد دیگر

Mariela Martins Nolasco is an Assistant Researcher at the Department of Chemistry, University of Aveiro. She specializes in computational spectroscopy, focusing on bridging theoretical and experimental research through combined computational and spectroscopic methods. Her work emphasizes understanding molecular dynamics in materials like deep eutectic solvents, polymers, and luminescent systems. Education: B.Sc. in Chemical Engineering (1999), M.Sc. in Chemistry (2004), Ph.D. in Physical Chemistry (2007), all from University of Aveiro. Research Interests: Computational Spectroscopy, Neutron Scattering, Deep Eutectic Solvents, Polymer Dynamics, Cellulosic Materials. She has led 9 R&D projects (2 national, 7 international) and contributed to 15 others. Notable collaborations include work at ISIS Neutron & Muon Source (UK) and Institut Laue-Langevin (France). Her awards include the 2021 ISIS Impact Award for societal impact in polymer research.

• Condensed Matter Physics
• Materials Discovery
• Ab Initio Calculations
• +۴ مورد دیگر

Fernando Manuel da Silva Nogueira is an Associate Professor at the Department of Physics, Faculty of Sciences and Technology, University of Coimbra. He holds a PhD in Theoretical Physics from the same institution (1999) and has been a faculty member since 1990. His research focuses on materials discovery using ab-initio methods , computational physics, and development of scientific software tools like Octopus and APE . He leads the Condensed Matter Physics group at CFisUC (Centro de Física da Universidade de Coimbra) and has been Director of the Portuguese Physics Olympiad (2007-2018). Education: PhD in Theoretical Physics (1999), University of Coimbra MSc in Theoretical Physics (1993), University of Coimbra BSc in Physics (1990), University of Coimbra Research interests include computational materials science , nonlinear optics , density functional theory , and electronic structure calculations . He has authored 40+ peer-reviewed articles, 3 books, and directed over 25 research projects. His work spans topics like carbon nanotube properties, firefly bioluminescence mechanisms, and high-throughput materials discovery. He has organized 25+ conferences, advised 3 PhD students and 17 MSc students, and contributed extensively to open-source computational physics software. His ORCID is 0000-0003-3125-3660 .

• intelligent systems
• Machine Learning
• evolutionary algorithms
• +۴ مورد دیگر

Teresa Cristina de Freitas Gonçalves is an Associate Professor at the Department of Informatics, School of Sciences and Technology, University of Évora, where she has been employed since 1999. She serves as an integrated researcher at the ALGORITMI research centre and is the Director of the VISTA Lab (Video, Image, Speech and text Analysis Lab), the unit of the ALGORITMI research centre at University of Évora. Her leadership roles include Director of the Master programme in Informatics Engineering and deputy Director of both the Master programme in Artificial Intelligence and Data Science and the Doctoral program in Computer Science. She earned her PhD in Computer Science from University of Évora and a MSc degree in Informatics Engineering from New University of Lisbon. Her academic journey at University of Évora has included significant leadership positions including Head of the Computer Science Department (2011-2015), Director of the Bachelor programme in Informatics Engineering (2016-2021), and Deputy Director roles for various undergraduate and graduate programs. Dr. Gonçalves' research focuses on intelligent systems, particularly Machine Learning approaches, with substantial contributions in evolutionary algorithms, information extraction and retrieval, and supervised learning across multiple data modalities including tabular data, text (in both Portuguese and English), and images (medical and satellite). Her work bridges theoretical advances with practical applications in healthcare, remote sensing, and natural language processing. She has successfully supervised 6 doctoral theses, 19 master theses, and 3 postdocs, and currently mentors 5 doctoral and 6 master students from diverse international backgrounds including Bangladesh, Cabo Verde, Nepal, Philippines, India, Sri Lanka, China, Mongolia, and Portugal. Her publication record includes over 100 scientific articles indexed by Scopus with 640 citations and an h-index of 12, demonstrating significant international impact with 56% of her work involving international collaboration. Her recent research shows a strong trend toward applying advanced machine learning techniques to healthcare applications, information retrieval systems, and remote sensing analysis, with particular emphasis on transformer networks, learning-to-rank methodologies, and multimodal data analysis. Dr. Gonçalves has made substantial contributions to the academic community through her service as a reviewer for over 50 articles in prestigious international journals and conferences, and as chair for major international conferences including IDEAL 2023, PROPOR 2020, SKIMA 2017 and 2018, and CLEF 2016. She serves on the board of APRP (Associação Portuguesa de reconhecimento de Padrões) and as a jury member for APRP prizes for best MSc and PhD theses. Her current research portfolio includes coordination of the Horizon Europe MSCA Staff Exchange HarmonicAI project and local coordination of WP6 in the NewSpace Portugal mobilising agenda. She is also actively involved in numerous other international research initiatives including Interreg VI-B Sudoe SenforFire, PRR CANTE, La Caixa INCOME, Erasmus+ KA220-HED REDINEST, Interreg POCTEP TID4AGRO, and ATTRACT DIH projects. Previously, she led the FCT AI in the Public Administration SNS24.Scout.IA project and coordinated the FEDER R&D NIIAA project. As Director of the VISTA Lab, Dr. Gonçalves leads a dynamic research team focused on video, image, speech, and text analysis. The lab serves as the Évora hub of the ALGORITMI research centre and has established strong international collaborations. Under her leadership, the VISTA Lab has developed innovative approaches in medical image analysis, natural language processing for Portuguese, and satellite image classification, with applications spanning healthcare, environmental monitoring, and public administration.

Kimin Leeمشاهده پروفایل

استادیار

• Safe and capable decision-making agents
• Physical AI
• Reinforcement Learning from Human Feedback
• +۹ مورد دیگر

Kimin Lee is an assistant professor at the Graduate School of AI at Korea Advanced Institute of Science and Technology (KAIST), where he focuses on developing safe and capable decision-making agents. His research spans multiple aspects of artificial intelligence with a strong emphasis on safety and reliability. Dr. Lee completed his educational journey at KAIST, earning a Ph.D. in Electrical Engineering with a focus on Machine/Deep Learning (2015-2020), advised by Professor Jinwoo Shin. He also holds a Master's degree in Electrical Engineering (Wireless Communication Networks, 2013-2015) and a Bachelor's degree in Electrical Engineering (2009-2013), both from KAIST. His primary research interests include: Physical AI - developing AI systems that can interact safely and effectively with the physical world Alignment - particularly reinforcement learning from human feedback (RLHF) and scalable oversight techniques Monitoring - safety evaluation frameworks and benchmarking for AI systems LLM Agents - enhancing the capabilities and safety of large language model-based agents Dr. Lee's recent publications reveal a strong trajectory toward addressing critical challenges in AI safety. His work consistently bridges theoretical advances with practical applications, particularly in the areas of reinforcement learning, computer vision, and natural language processing. A notable trend in his research is the development of methods to evaluate and enhance the safety of AI systems, especially large language models and diffusion models, while maintaining or improving their capabilities. As an active member of the academic community, Dr. Lee serves as an area chair for major conferences including NeurIPS, ICLR, and ICML, and regularly reviews for top-tier AI venues. He has also organized workshops focused on safe and trustworthy AI agents. Dr. Lee's research group at KAIST appears to focus on AI safety and decision-making, with research projects spanning from theoretical foundations to practical implementations of safe AI systems. His collaborative work with institutions like UC Berkeley and Google Research demonstrates the interdisciplinary nature of his research approach.

• Distributed Systems
• Cloud Computing
• Fault Tolerance
• +۳ مورد دیگر

Rodrigo Miragaia Rodrigues is a full professor at the Instituto Superior Técnico (ULisboa) and a researcher at INESC-ID since 2015. He previously held roles as an associate professor at Universidade Nova de Lisboa, tenure-track faculty at MPI-SWS, and completed his PhD at MIT in 2005 under Barbara Liskov. Education: PhD in Computer Science, MIT, 2005 Research Interests: Focuses on distributed systems, fault-tolerant computing, cloud infrastructure, and consistency models. His work bridges theoretical foundations and practical implementations, addressing challenges in geo-replication, secure analytics, and resource allocation in serverless environments. He emphasizes scalable systems and resilient data management. Awards: Best Paper Award at SOSP ERC Starting Grant Google Faculty Research Award Advising & Grants: Has advised 7 PhD students as main advisor, with graduates in top institutions like Purdue, TU Munich, and USTC. Secured funding from the European Research Council (ERC) and Google, focusing on projects like DependableCloud (ERC Grant 307732). Labs & Teams: Leads research at INESC-ID and previously directed the Dependable Systems Group at MPI-SWS. Active in academic leadership roles, including President of the Scientific Council at IST.

• Mathematics Education
• Educational Sciences
• Technology in Education
• +۳ مورد دیگر

António Augusto Gaspar Ribeiro serves as Professor at the Polytechnic Institute of Viseu's School of Education, where he has maintained continuous academic service since 1986, progressing from Assistant to current Professor Coordenador rank. His scholarly identity centers on Mathematics Education with specialized expertise in geometry pedagogy and educational technology integration across primary and teacher education contexts. His academic formation includes: Doctorate in Didactics of Mathematics (2005, University of Aveiro) Doctorate in Didactics (2005, University of Aveiro) Master's in Mathematics Teaching Methodology (1995, University of Lisbon) Licenciatura in Mathematics Teaching/Nature Sciences (1987, Polytechnic Institute of Viseu) Ribeiro's research program demonstrates sustained innovation in mathematics education, particularly through dynamic geometry environments like Cabri-Géomètre for primary classrooms. His work bridges theoretical frameworks with practical applications, examining teacher cognition, curriculum implementation challenges, and technology-enhanced learning. Recent scholarship shows expanded focus on interdisciplinary approaches in higher education and the pedagogical potential of humor in mathematics instruction. Analysis of his 25+ publications reveals evolving thematic trajectories: early work (2002-2006) established foundations in geometry education and technology integration; mid-career research (2009-2014) addressed curriculum reform and teacher development; current output (2017-2021) emphasizes interdisciplinary collaboration, early childhood mathematics, and socio-emotional dimensions of learning. His scientific recognition includes: 1º Concurso Nacional de Software Educacional - PUZZLE (1993) 1º Concurso Nacional de Software Educacional - JornalHist (1993) Ribeiro has supervised eight master's theses in Educational Sciences, primarily focusing on geometry education, technology integration, and teacher cognition. He leads the SmartCityKidsLab initiative (2019-present) and previously coordinated the PRINT interdisciplinary project (2017-2018) with Brazilian partners. His research portfolio includes four funded projects through the Center for Research in Education, Technologies and Health. As an institutional leader, he serves on the School of Education's Scientific Council and has held multiple governance roles including Pedagogical Council Secretary (1996-1998) and Vice-President of the School Board (2000-2002). His professional engagement extends to the Association of Mathematics Teachers and international collaborations with Brazilian institutions.