جست‌وجوی استاد و پژوهشگر

Graeme Bestمشاهده پروفایل

مدرس

• Robotics
• Field Robotics
• Multi-Robot Systems
• +۵ مورد دیگر

Graeme Best is a Lecturer in robotics at the University of Technology Sydney's School of Mechanical and Mechatronic Engineering within the Faculty of Engineering and Information Technology. He joined UTS in April 2022 after working as a Postdoctoral Scholar at Oregon State University from 2018 to 2022, where he collaborated with Carnegie Mellon University and University of Washington on projects funded by DARPA, ONR, NSF, and NAVFAC. Dr. Best completed his PhD titled "Planning Algorithms for Multi-Robot Active Perception" at the University of Sydney's Australian Centre for Field Robotics. His educational background includes a BE (Electrical and Computer Systems) and BSc (Computer Science) from Monash University, both completed in 2014. His research focuses on developing fundamental algorithms for multi-robot systems, with particular emphasis on active perception, where robots plan their motion to obtain high-value observations. His work spans from theoretical algorithm development to full-scale system demonstrations across diverse environments including subterranean spaces, marine settings, precision agriculture, and planetary exploration. He has pioneered approaches such as decentralized Monte Carlo tree search, self-organizing maps for active perception, and spatiotemporal optimal stopping to address challenges like online planning, decentralized coordination, long planning horizons, and unreliable communication. Dr. Best's publication record shows a consistent trajectory of high-impact research in top robotics venues, with recent work focusing on behavior trees for intent communication, multi-room exploration, and resilient multi-sensor systems. His publications demonstrate strong interdisciplinary connections between theoretical computer science, control theory, and practical field robotics applications. Google Research Scholar Program Award (2023) DARPA Subterranean Challenge: Winner for the Tunnel Circuit (2019) DARPA Subterranean Challenge: Second Place for the Urban Circuit (2022) IEEE ICRA Best Paper Award on Multi-Robot Systems (2021) RSS Best Systems Paper Award, Finalist (2022) Dr. Best actively contributes to the robotics community through editorial roles at major conferences including IEEE ICRA, IROS, and MRS. He currently serves as Program Director for UTS's undergraduate Mechatronics major and teaches courses related to robotics software and algorithms. His funded research includes projects like the Multi-Robot Mission Control System for Maritime Autonomous Systems and the Online Behaviour Tree Synthesis for Adaptive Multi-Agent Coordination project funded by Google. He leads the UTS Motorsports Autonomous Vehicle team and supervises capstone projects, demonstrating his commitment to translating research into practical student experiences. His work on the DARPA Subterranean Challenge, where his team won the "Most Sectors Explored" award, exemplifies his ability to bridge theoretical research with real-world field applications.

Alainya Kavaloskiمشاهده پروفایل

دانشیار

• Writing Pedagogy
• Digital Media Poetics
• American Literature (20th-21st Century)
• +۵ مورد دیگر

Dr. Alainya Kavaloski is an Associate Professor of English and Humanities at SUNY Canton , teaching courses in digital graphic storytelling, electronic literature, and critical game design. Her research examines rhetorical infrastructures in emerging media (graphic narratives, AR games, hybrid storyscapes) to analyze geopolitical border representations in U.S. and Israel-Palestine contexts. Education : PhD (English, UW-Madison), MA (Literary Studies, Hebrew University), BA (English, Edgewood College) Research Focus : Digital media poetics, critical security studies, transnational Jewish literature, and game studies Leadership : Department Chair (2021-present), MLA Delegate Assembly Member Her work bridges decolonial mapping and digital pedagogy , including collaborations with Games Learning Society and co-editorship of SUNY Canton’s Grasse Roots journal. Awards include SUNY IITG Grant (2017) for digital writing lab development and UW-Madison’s Innovation in Teaching Award (2015). Key publications analyze: Security logics in ISIS-focused war games (2018) Graphic narratives’ affective border representations (2015) Postcolonial digital homeland construction (2015) She has developed studio-based pedagogical models like ARIT (Augmented Reality Interactive Theory) and co-founded SUNY Canton’s New Media Writing major.

• Web Development
• Programming Languages
• Software Engineering
• +۷ مورد دیگر

D.M. Groenewegen is a researcher at the Computer Science & Engineering department within the School of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His work focuses on domain-specific languages, particularly WebDSL , for web application development and academic workflow optimization. Research interests include domain-specific languages (DSL) , web programming , conference management systems , and software engineering . He has contributed to improving the reliability and modularity of DSLs through case studies and runtime evolution. Recent publications explore the use of WebDSL to build systems like Conf Researchr for managing academic conferences, incremental computation in persistent object graphs (e.g., IceDust ), and the integration of validation and UI concerns in web applications. These works highlight trends in DSL design , linguistic abstractions , and software reliability . He collaborates with researchers such as Elmer van Chastelet and Eelco Visser, emphasizing peer-reviewed contributions to conferences like ECOOP and workshops under ACM and Dagstuhl Publishing. His work has been published in venues such as OpenAccess Series in Informatics and PervasiveHealth .

K. Psarakisمشاهده پروفایل

پژوهشگر

• Cloud Computing
• Stream Processing
• Distributed Systems
• +۸ مورد دیگر

K. Psarakis is a researcher in the field of Data-Intensive Systems, focusing on cloud computing, stream processing, and distributed dataflows. Their work bridges theoretical and practical challenges in cloud-native applications and scalable systems. Institution: Affiliated with Data-Intensive Systems Research Focus: Cloud transaction management, autoscaling, geospatial data platforms, and fault tolerance Research Trends Recent publications like Styx and CheckMate highlight innovations in transactional stateful functions and checkpointing protocols. Psarakis also contributes to geospatial data federation (e.g., Topio ) and schema matching techniques ( Valentine ). Collaborations Collaborates with researchers such as G. C. Christodoulou, M. Fragkoulis, and A. Katsifodimos on projects involving open-source platforms and cloud-native systems.

Katherine Occhiutoمشاهده پروفایل

استادیار

• Critical social work practice
• Mental health
• Poverty and social inequality
• +۳ مورد دیگر

Katherine Occhiuto is an Assistant Professor at the School of Social Work , Carleton University. She holds a PhD and MSW from Carleton and a BA in Political Science and Communications Studies from York University. Her research focuses on critical clinical and community-based practice , mental health , poverty and the working poor , and simulation-based education . Her work integrates simulation methodologies into social work education, addressing challenges in clinical training, cross-sector partnerships, and technology adaptation. Recent publications highlight innovations in online simulations standardized client applications AI integration low-income mothers’ data collection peer support research . Occhiuto actively collaborates on projects examining healthcare simulations, curriculum design, and equity-focused pedagogy, with current research extending to 2025. She is based in Ottawa, Canada, and engages in community-oriented initiatives.

Karine Even-Mendozaمشاهده پروفایل

مدرس

• Software Testing
• Software Verification
• Programming Languages
• +۷ مورد دیگر

Karine Even-Mendoza is a Lecturer in Systems & Programming Languages at King's College London, working within the Department of Informatics in the Faculty of Natural, Mathematical & Engineering Sciences. Previously, she was a Research Associate at Imperial College London's Department of Computing, where she worked in the Software Reliability Group and Multicore Programming Group. She completed her PhD at King's College London, where she also spent four years working with the Software Systems (SSY) group. Dr. Even-Mendoza's research focuses on the intersection of software testing, verification, and programming languages, with recent work increasingly incorporating machine learning and quantum computing techniques. Her work addresses critical challenges in compiler testing, system simulation validation, and the application of large language models to software engineering problems. She has developed innovative approaches like ReFuzzer for enhancing the validity of LLM-generated test programs and SearchGEM5 for improving the reliability of system simulators through search-based testing. Her publication record demonstrates a strong trajectory in top-tier software engineering venues, with a notable shift toward incorporating large language models and quantum computing in recent years. She has become particularly active in applying AI techniques to traditional software engineering challenges, bridging the gap between classical software verification methods and modern AI approaches. Her work spans both theoretical foundations and practical applications, with implementations like CsmithEdge and GrayC contributing tangible tools to the software testing community. Dr. Even-Mendoza has been actively involved in the software engineering research community, serving on program committees for major conferences including ASE, ISSTA, ECOOP, and SPLASH. She has also contributed to artifact evaluation processes, demonstrating her commitment to research reproducibility and scientific rigor in software engineering.

Torrey Wagnerمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Data Analytics
• +۷ مورد دیگر

Dr. Torrey Wagner serves as an Assistant Professor of Data Analytics at the Air Force Institute of Technology (AFIT), where he supports the Data Analytics graduate certificate program. He develops and teaches core courses including DASC 522 Machine Learning, SATI 532 Data Visualization & Communication, and DASC 511 Object-Oriented Programming using Python. His instructional focus centers on applying data analytics techniques to solve military problems through the CRISP-DM process framework. Dr. Wagner earned his PhD in Electrical Engineering with an Electro-optics focus from AFIT in 2010, an MS in Aerospace Systems Engineering from Loughborough University (UK) in 2004, and a BS in Electrical Engineering from the University of Minnesota in 2000. His educational background bridges electrical engineering, aerospace systems, and advanced data analytics. His research concentrates on applying predictive and generative artificial intelligence techniques to enhance Department of Defense organizational efficiency and performance. Dr. Wagner's scholarly work spans machine learning applications for defense systems, energy optimization for military operations, quantum computing advancements, and natural language processing solutions for defense contexts. He has developed specialized methodologies for military problem-solving through data analytics, with emphasis on practical implementation in operational environments. Dr. Wagner's publication record reveals a strategic evolution toward cutting-edge AI applications. Recent work demonstrates significant focus on large language models, retrieval-augmented generation systems, and quantum computing implementations. His research portfolio includes machine learning applications for aircraft engine cost prediction, satellite imagery analysis, seismic event classification, and energy system optimization for austere military environments. This work consistently bridges theoretical AI advances with tangible defense applications. As an educator and mentor, Dr. Wagner has guided dozens of students through their first publications and presentations. His students frequently co-author peer-reviewed journal articles and conference papers, primarily at the master's level with several doctoral candidates. He has contributed to AI education within military contexts through his chapter "Augmenting a Curriculum Review with Generative AI" in the AFIT Generative AI Teaching Guidebook and other educational resources. Dr. Wagner's research supports multiple AFIT initiatives focused on data analytics for defense applications. His work involves extensive collaboration with Department of Defense organizations to implement AI technologies in practical military settings, particularly in energy systems optimization, aircraft operations analytics, and decision support tools for commanders. Current projects include secure offline large language model implementations, quantum communication network resilience, and advanced data visualization techniques for military decision-making.

• Search Based Software Engineering
• Software Testing
• Evolutionary Computation
• +۷ مورد دیگر

Giovani Guizzo is a Software Engineer at Kii working as a Blockchain Engineer and Front-end developer with React, while maintaining an active research profile in Search-Based Software Engineering. He earned his PhD in Computer Science from the Department of Informatics at Federal University of Paraná (UFPR) in Brazil under Professor Silvia Regina Vergilio in 2018. His academic collaborations include significant affiliations with University College London where he has published as a researcher. His research program centers on applying evolutionary computation and search-based techniques to software engineering challenges, particularly in software testing and optimization. Guizzo's work bridges theoretical advances in multi-objective optimization with practical software engineering applications, resulting in innovative solutions for test model inference, mutant reduction strategies, and automated program repair. His approach often combines natural language processing with finite state machine generation to transform bug reports into actionable test models. Guizzo's publication record reveals a consistent trajectory of increasing impact in top-tier software engineering venues. His recent work demonstrates sophisticated integration of multi-objective evolutionary algorithms with practical software testing challenges, particularly in the areas of model inference from natural language bug reports and optimization of mutation testing processes. The evolution of his research shows progression from foundational work on design patterns in evolutionary algorithms toward more complex applications in automated software testing and repair. His achievements include: SSBSE 2021 Challenge Winner for innovative work on fitness functions in automated program repair Distinguished Artifact Award at ICSE 2021 recognizing reproducibility in genetic improvement research Microsoft Azure Research Award in 2017 supporting his work in cloud-based software engineering research Guizzo maintains active engagement with the research community through editorial roles for IET Software and Science of Computer Programming, membership on the SSBSE Steering Committee, and service on program committees for major conferences including ESEC/FSE, ASE, GECCO, and ICSE. His academic visits to University College London (3 months in 2017) and Queen Mary University (1 month in 2017) established lasting research collaborations with Dr. Jens Krinke, Dr. Federica Sarro, and Dr. John Drake that continue to produce high-impact publications. Through his interdisciplinary approach combining software engineering, evolutionary computation, and natural language processing, Guizzo has established himself as a significant contributor to the search-based software engineering community, with research that consistently addresses practical challenges while advancing theoretical foundations.

Vahid Alizadehمشاهده پروفایل

استادیار

• Empirical Software Engineering
• Software Quality
• Software Refactoring & Maintenance
• +۷ مورد دیگر

Vahid Alizadeh is an Assistant Professor in the College of Computing and Digital Media (CDM) at DePaul University in Chicago, USA, where he has been serving since 2020. His academic career focuses on bridging the gap between software quality research and industrial practice through empirical studies and intelligent tool development. Education: Ph.D. in Computer Science, University of Michigan (2015-2020) M.Sc. in Electrical Engineering, University of Tehran (2011-2013) B.Sc. in Electrical Engineering, Iran University of Science and Technology (2006-2011) Research Interests: Dr. Alizadeh's research spans empirical software engineering, software quality, refactoring & maintenance, intelligent software engineering, and AI-enabled systems. His work combines rigorous empirical methods with practical tool development to address real-world software engineering challenges. He has particular expertise in developing intelligent refactoring technologies that are currently deployed by organizations impacting thousands of programmers worldwide. Research Trends: His publication record shows a consistent focus on applying AI and machine learning techniques to software engineering problems, particularly in the areas of refactoring and quality assurance. Recent work demonstrates increasing integration of AI/ML approaches with traditional software engineering practices, reflecting the broader trend toward AI4SE (AI for Software Engineering). Awards & Recognition: Excellence in Teaching Award from DePaul University (2025) $67,000 DePaul-RFUMS Grant for AI-Powered Community Pharmacy Research (2024) ACM SIGSOFT Distinguished Paper Award at MODELS Conference (2020) Distinguished University of Michigan-Dearborn Honors Scholar (2020) Outstanding Graduate Research Assistant Award (2018/2019) Professional Activities: Dr. Alizadeh has served in various capacities at major software engineering conferences including ASE 2022 as Session Chair and Virtualization Co-Chair, and MODELS 2025 as Web Co-Chair. His work has resulted in one patent and multiple invention licenses through the University of Michigan Tech Transfer Office. He actively mentors graduate students interested in empirical software engineering, software quality, and intelligent refactoring technologies.

Einar Broch Johnsenمشاهده پروفایل

استاد

• Computer Science
• Formal Methods
• Distributed Systems
• +۷ مورد دیگر

Einar Broch Johnsen is a Professor at the Department of Informatics, University of Oslo, where he has established himself as a leading researcher in formal methods and their application to distributed systems, cloud computing, and digital twins. His work bridges theoretical computer science with practical engineering challenges in complex systems. His research interests span formal methods, distributed and concurrent systems, programming models, digital twins, and robotics. He has made significant contributions to the ABS modeling language for asynchronous distributed systems and the SMOL programming language for digital twins. His approach emphasizes lightweight analysis techniques, type systems, testing, and deductive verification to ensure system reliability. His recent publications reveal a strong focus on applying formal methods to digital twin technology, with particular emphasis on healthcare applications, pandemic modeling, and robotics. His work demonstrates how formal verification techniques can enhance the reliability of AI-driven systems, especially in critical domains like underwater robotics and pandemic response. Johnsen actively contributes to the academic community through leadership roles including co-Editor-in-Chief of Formal Aspects of Computing , membership in IFIP WG2.2, and service on numerous conference program committees. He has chaired major conferences including FM 2015 and DisCoTec 2008. He leads and participates in numerous research projects including Sirius (as strategy director), Envisage (as coordinator), HyVar (as scientific coordinator), and REMARO (as co-initiator). His current projects include DART: Digital Arctic Twins, A Digital Twin for Vaccination Strategies, A Digital Twin of the Oslo Fjord, and NebulOuS: A Meta Operating System for Cloud Computing Continuums. Johnsen teaches courses including IN2031 – Project in Programming, IN2080: Computability and Complexity, and IN5170: Models of Concurrency, mentoring the next generation of computer scientists in formal methods and systems engineering.

• Autism Spectrum Disorders
• Developmental Disabilities
• Augmentative and Alternative Communication
• +۵ مورد دیگر

Professor Jeff Sigafoos is a distinguished academic in the School of Education at Victoria University of Wellington. He received his PhD in educational psychology from the University of Minnesota in 1990 and has held academic appointments at the University of Queensland, University of Sydney, and The University of Texas at Austin prior to his current position. His work focuses on educational and behavioral interventions for individuals with developmental and physical disabilities, with over 789 publications to his name. Dr. Sigafoos's educational background includes PhD, MA, and BA degrees from the University of Minnesota, Minneapolis. His research has been consistently funded by major organizations including the Royal Society of New Zealand, Health Research Council of New Zealand, Australian Research Council, and National Health and Medical Research Council. PhD, Educational Psychology, University of Minnesota MA, University of Minnesota BA, University of Minnesota Professor Sigafoos's research interests center on the education of children with developmental and physical disabilities, including autism spectrum disorders, communication assessment and intervention for individuals requiring augmentative and alternative communication, the use of assistive technology to teach adaptive skills, and the assessment and treatment of severe behavior problems in individuals with developmental disabilities. His recent work has increasingly focused on technology-aided interventions for people with intellectual and multiple disabilities. Analysis of his recent publications reveals a strong emphasis on developing technology solutions to support individuals with severe disabilities. His work spans autism intervention, communication strategies, behavioral flexibility assessment, and culturally appropriate assessment tools. A significant portion of his research employs single-case research methodology to evaluate the effectiveness of various interventions. Professor Sigafoos serves on the editorial boards of numerous prestigious journals in his field, demonstrating his standing as a leading scholar. His editorial roles include Clinical Archives of Communication Disorders, Current Developmental Disorders Reports, Teaching Exceptional Children, and several others. Editor, Clinical Archives of Communication Disorders Editor, Current Developmental Disorders Reports Editor, Teaching Exceptional Children Editor, Technologies: Assistive Technology Section Editor, Advances in Neurodevelopmental Disorders Member of International Society for Augmentative and Alternative Communication (ISAAC) In terms of academic mentoring, Professor Sigafoos actively supervises doctoral students, with current projects focusing on adapting early supports for autistic children in Azerbaijan and developing antecedent interventions for challenging behavior in adults with intellectual disability. His teaching portfolio includes courses on Applied Behaviour Analysis for Educators, Psychological Aspects of Neurodevelopmental Disorders, Evidence-Based Practice in Education, and Educating Students with Developmental Disabilities.

Abby Marshمشاهده پروفایل

دانشیار

• Usable Privacy and Security
• Digital Privacy
• Human-Computer Interaction
• +۳ مورد دیگر

Abby Marsh is an Associate Professor in the Department of Mathematics, Statistics, and Computer Science at Macalester College, currently on sabbatical during the 2025-2026 academic year. Her research centers on making online privacy usable and accessible, with a focus on marginalized populations including families with teenagers and online fandom communities. Education: Ph.D. in Societal Computing, Carnegie Mellon University, 2018 B.A. in Computer Science and Mathematics (double major), Oberlin College, 2013 Professor Marsh's work in usable privacy investigates how privacy tools can accommodate under-studied groups through empirical user studies and theoretical frameworks. She pioneers research on digital privacy norms within transformative fandom communities and develops inclusive security solutions for educational settings. Her approach emphasizes learning from existing practices of online groups with complex privacy behaviors, challenging traditional assumptions in the field. Analysis of her 2023-2024 publications reveals a concentrated shift toward boundary management in online communities, particularly fandom spaces, while expanding into assistive technology privacy in education. This builds upon her foundational work on family privacy dynamics, demonstrating consistent focus on real-world privacy challenges faced by vulnerable populations. Scientific Awards: No awards listed in the provided information Advising and Academic Service: Marsh actively mentors undergraduate researchers including Dan Bially Levy, Kien Nguyen, and Aron Smith-Donovan. She teaches core courses such as Object-Oriented Programming (COMP 127), Computer Systems (COMP 240), and Computer Security and Privacy (COMP 487), while maintaining comprehensive student resources for MSCS majors. She also coordinates Macalester's fiber artists community group, demonstrating interdisciplinary engagement beyond traditional CS boundaries. Research Context: During her doctoral work at Carnegie Mellon, Marsh was affiliated with the CUPS Lab within CyLab. Her current research continues this collaborative tradition, focusing on community-driven privacy solutions while leveraging her background in both technical systems and social computing.

• Persian Language and Literature
• History of Iran
• Timurid Studies
• +۷ مورد دیگر

Michele Bernardini is a Full Professor of Persian Language and Literature at the University of Naples 'L'Orientale', specializing in Iranian studies, Timurid history, and Islamic culture. With a career spanning over three decades, he has established himself as a leading scholar in Persian studies and Central Asian history in the Italian academic landscape. His educational background includes a Degree in Literature from the University of Rome "La Sapienza" (1985, with honors) and a Doctorate in Iranian Studies from the Oriental University Institute of Naples (1991). His academic journey progressed from researcher (1992-2002) to Associate Professor (2002), and finally to Full Professor (2016), with national qualification as Full Professor obtained in 2014. Professor Bernardini's research focuses on Persian language and literature, the history of Iran (particularly medieval and modern periods), Timurid culture and history, Islamic art and architecture, and Ottoman studies. His work bridges historical, literary, and artistic approaches to understanding the Islamic world, with particular attention to cross-cultural interactions between East and West. His scholarship demonstrates how Persian literary traditions influenced broader Islamic civilization and how Timurid culture represented a crucial nexus of artistic and intellectual exchange across Eurasia. His extensive publication record shows consistent engagement with primary sources in Persian, Arabic, and Turkish, demonstrating expertise in manuscript studies and textual criticism. Bernardini's work reveals a particular interest in how historical narratives were constructed and transmitted across cultural boundaries, with significant contributions to understanding Timurid historiography and its reception in both Eastern and Western contexts. First Honorable Mention in The Saidi-Sirjani Book Award of the International Society for Iranian Studies (2010) Professor Bernardini has supervised numerous graduate students in Persian studies and Iranian history, though specific names are not provided in the available documentation. His editorial work, particularly as editor-in-chief of "Oriente Moderno," has provided critical support for emerging scholars in the field. He has participated in numerous international research projects, particularly those focused on Timurid history and Persian literary traditions, often collaborating with French, German, and Turkish academic institutions. As a member of the scientific committee for major international projects and libraries like BULAC (Bibliothèque Universitaire des Langues et Civilisations) in Paris, Bernardini contributes to shaping the institutional infrastructure for Oriental studies in Europe. His leadership roles in organizations like the International Committee for Turkish Art Congresses demonstrate his commitment to fostering international scholarly collaboration in the field of Islamic and Oriental studies.

Andreas Gromerمشاهده پروفایل

پژوهشگر

• Competency orientation in vocational and technical education
• Information strategies in vocational-technical competence development
• Didactic development of digital transformation (Industry 4.0)
• +۳ مورد دیگر

Andreas Gromer is a Researcher at the Chair of Technology Didactics within the School of Social Sciences and Technology at the Technical University of Munich (TUM). Seconded since 2019 (part-time until 2024, full-time from 2025), he concurrently taught metal and construction technology at Johann-Bierwirth-Schule in Memmingen until 2025 while contributing to TUM's teacher training professionalization and research initiatives. His educational foundation includes a vocational teaching degree from TUM (2006-2011) specializing in metal and construction technology, preceded by graduation from Vöhlin-Gymnasium Memmingen (2005) and practical training at Bavarian teacher colleges (2012-2014). Research centers on competency-oriented vocational education frameworks, knowledge-work-driven competence development strategies, Industry 4.0 didactic modeling, and hybrid-format digital pedagogy. His work systematically bridges theoretical vocational learning with practical industrial applications through technology integration. Publication analysis reveals a cohesive trajectory: recent works progressively detail Industry 4.0 implementation in vocational contexts, evolving from interdisciplinary competency frameworks (2023) to hybrid learning landscapes (2021), then to robotics (2020) and cyber-physical pneumatics (2018), demonstrating applied focus on industrial technologies within educational settings. No scientific awards were documented in source materials. As a TUM researcher, Gromer mentors teacher training students in technology didactics while contributing to institutional projects. His consultancy role in ALP Dillingen's Digital Transformation initiative extends his impact to robotics and sensor technology specialization groups. He operates within TUM's Technology Didactics ecosystem, collaborating on BBI@TUM and LPI projects while advancing vocational education through the TRIX platform and JOTED journal, with ongoing work targeting cyber-physical system integration in vocational curricula.

• Computational Mechanics
• Finite Element Methods
• Fluid Dynamics
• +۴ مورد دیگر

Ricardo Javier Principe Rubio is a Researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Barcelona East School of Engineering (EEBE) and the Department of Fluid Mechanics. He is a key member of the ANiComp (Numerical Analysis and Scientific Computing) and (MC)² (Computational Mechanics in Continuous Media) research groups. His work bridges high-performance computing, fluid dynamics, and numerical methods, with applications in fusion technology, environmental engineering, and nanomaterials. His research focuses on advanced computational techniques, including finite element methods, uncertainty quantification, and parallel algorithms for large-scale simulations. Recent projects involve anisotropic mesh adaptation, multilevel Monte Carlo methods, and stabilized formulations for multiphase flows. Principe actively contributes to UPC's scientific software ecosystem, notably through the FEMPAR framework for parallel finite element modeling. Awards include the Premi Extraordinari de doctorat 2010 for outstanding doctoral research. He leads/participates in competitive R&D projects funded by Catalan and EU programs, such as EXAscale Quantification of Uncertainties for Technology and Science Simulation (EXAQUAT). Collaborative networks span Barcelona Supercomputing Center and international consortia.