Dr. Peter Arcese is the FRBC Chair of Applied Conservation Biology and co-Director of the Centre for Applied Conservation Research in the Faculty of Forestry at the University of British Columbia. His research focuses on ecology and evolution of small populations, conservation biology, and human impacts on ecosystems. He has led long-term studies on song sparrows and other species, emphasizing population genetics, inbreeding effects, and invasive species management. With over 100 publications and 28 graduate students, his work bridges theoretical and applied conservation, addressing biodiversity loss and reserve design. Education: PhD in Zoology (UBC), postdoctoral work in Tanzania. Awards include NSF Young Investigator Award and Fellowship in the American Ornithologists Union. Active in global conservation initiatives, including Andean bear conservation and Garry Oak ecosystem restoration. His lab develops tools like the prioritizr R package for conservation prioritization. Key contributions include documenting human-driven ecosystem changes, designing nature reserves, and guiding policy through empirical research. Collaborations span institutions like The Nature Trust of BC and international conservation groups. Current projects address climate adaptation, genetic rescue in small populations, and urban biodiversity challenges.
Prof. Dr. rer. nat. Matthias S. Müller is a Universitätsprofessor and Director of the IT Center at RWTH Aachen University. His research focuses on High-Performance Computing (HPC), parallel programming models, correctness verification, energy-aware computing, and tools for distributed systems. He leads the High-Performance Computing group, contributing to advancements in HPC resource management, runtime systems, and sustainable computing practices. Key areas of expertise include MPI and OpenMP correctness checking, static and dynamic analysis techniques, performance optimization for heterogeneous architectures, and energy footprint modeling. Müller has extensively collaborated on projects like MUST (MPI correctness tool), OMPT tools, and frameworks for analyzing hybrid parallel applications. His work bridges theoretical computer science with practical implementation challenges in large-scale computing environments. Notable contributions include developing methods for data race detection in Remote Memory Access (RMA) programs, latency-aware power management models, and educational frameworks for HPC lab courses. His research often emphasizes tool development, runtime systems, and interdisciplinary applications of HPC across engineering domains. Müller's lab is part of RWTH Aachen's IT Center, which provides infrastructure and expertise for computational research. He actively publishes in top-tier conferences and journals, addressing challenges in parallel programming, energy efficiency, and distributed computing systems.
Dr. Tiago A. Marques is a Senior Research Fellow at the School of Mathematics and Statistics, University of St Andrews, UK, and an invited professor at DEIO (Universidade de Lisboa, Portugal). He specializes in Ecological Statistics , focusing on population density estimation using passive acoustic data and distance sampling methods. His work spans marine mammals (cetaceans, polar bears), fish, birds, and other wildlife. Key projects include DECAF (cetacean abundance via passive acoustics) and LATTE (cetacean behavior and human noise impact analysis). Education: Biologist by training, with an MSc and PhD in Statistics. Research Interests: Ecological statistics, acoustic monitoring, conservation biology, and statistical methodology dissemination. Key Contributions: Developed distance sampling software tools, pioneered methods for integrating acoustic data into ecological surveys, and led polar bear population studies in the Arctic. Collaborates globally on wildlife conservation and statistical ecology. Labs/Teams: CREEM (Centre for Research into Ecological & Environmental Modelling) at St Andrews. Active in open-source tool development, including R packages and GitHub repositories like DeepDiverCueRates .
Dr. Kerry Nice is a Research Fellow at the Melbourne School of Design (The University of Melbourne), specializing in urban climate modeling, artificial intelligence, and sustainable urban development. His work integrates software engineering expertise with environmental science to address urban challenges such as heat mitigation, active transport, and public health. He holds a PhD from Monash University, focusing on urban microclimate modeling (VTUF-3D) and the impact of vegetation/water-sensitive design on human thermal comfort. Research interests include: Urban modeling using artificial neural networks and deep learning Climate adaptation strategies for green/blue infrastructure Analysis of urban mobility patterns and bicycle infrastructure equity Impact assessment of irrigation and water management on urban cooling His publications (2020–2025) explore topics such as: System dynamics modeling for urban resilience Machine learning applications in thermal perception prediction Global pandemic mobility shifts and heat mitigation techniques He collaborates with the Transport, Health and Urban Design (THUD) research hub and maintains affiliations with the International Association for Urban Climate (IAUC) and Australian Meteorological & Oceanographic Society (AMOS).
Dr. Ahmad Abdel Latif is an Assistant Professor in the Department of Electrical and Software Engineering at the University of Calgary. Previously, he served as a postdoctoral researcher at DASLab, Concordia University, and earned his Ph.D. in Software Engineering from Concordia under Dr. Emad Shihab. His master’s degree was obtained from King Fahd University of Petroleum and Minerals (KFUPM). His research focuses on software engineering advancements in artificial intelligence, including chatbots, software quality, and mining software repositories. Notable projects include analyzing dependency ecosystems (e.g., NPM, Maven) for security risks, developing AI-driven chatbots for code repositories, and exploring machine learning model management challenges. He also investigates ethical implications of AI-generated code and open-source collaboration dynamics. Dr. Latif teaches ENSF 381: Full Stack Web Development and actively publishes on topics such as vulnerability mitigation, LLM-based chatbots, and software bot detection. His work bridges technical innovation with practical applications in cybersecurity, open-source ecosystems, and AI integration.
Steven Gray is a full professor in the Department of Community Sustainability at Michigan State University (MSU). He holds additional appointments at the National Institute of Standards and Technology and is a fellow at the Collective Intelligence Unit at the IT University of Copenhagen. His research focuses on socio-environmental modeling, knowledge diversity, and collective intelligence for sustainability, with over 100 peer-reviewed publications and a leading role in editing Environmental Modeling with Stakeholders: Methods, Theories and Applications . Gray’s work is supported by grants from the National Science Foundation, NOAA, USDA, and international bodies like the Belmont Forum. His lab develops the Mental Modeler software, applied globally in environmental planning contexts such as marine spatial planning, citizen science projects, coastal hazard mitigation, and agricultural conservation. Key projects include Collaborative Modeling of Mangroves and Seawalls (NOAA, 2023–2025) and Integrating Perspective-taking and Systems Thinking (NSF, 2021–2024). Research interests emphasize participatory modeling, systems thinking, and leveraging stakeholder knowledge for environmental decision-making. Notable contributions include advancing frameworks for assessing cognitive diversity in stakeholder groups and analyzing the role of collective intelligence in conservation. Gray’s lab also addresses urban food systems, disaster resilience, and climate-smart agriculture through interdisciplinary collaborations. Academic achievements include being named a fellow at the Collective Intelligence Unit and leading MSU’s Human-Environment Interactions Lab. Current projects focus on coastal resilience, fisheries management, and participatory approaches to complex environmental challenges.
Lluís Vicent Safont is a Senior Lecturer and Director of the Postgraduate Program in Data Management at the UPF Barcelona School of Management. He has held prominent roles such as Rector of Universitat Oberta La Salle (2008–2012) and academic leadership positions at institutions like Universitat Ramon Llull and Universidad La Salle. His research focuses on data science, education technology, and innovative teaching methodologies, with over 70 publications and 50 projects as Principal Investigator. He specializes in curriculum design, educational assessment, and the integration of technology in higher education, including hybrid learning systems and adaptive learning tools. Education background includes a Doctorate in Engineering and Architecture, alongside master’s and technical engineering qualifications. His work emphasizes bridging education and technology, addressing challenges like early school leaving and digital education readiness. He has contributed to international conferences (IEEE, Erasmus+) and authored books on topics like fuzzy logic in assessment and multimedia in education. As a leader, he has directed postgraduate programs, research groups, and institutional initiatives, focusing on innovation, internationalization, and educational policy. His projects often involve collaboration across universities and institutions to enhance educational quality and accessibility. Recent work includes the H2O Learn project on hybrid education analytics and initiatives reinforcing engineering leadership in societal contexts.
Jin Zhu is a Researcher in the Department of Statistics at the London School of Economics and Political Science (LSE), working with Prof. Chengchun Shi on reinforcement learning and machine learning. His research focuses on developing algorithms with statistical and computational guarantees, alongside statistical software design to enhance algorithmic applications. Prior to LSE, he earned his PhD in Statistics at Sun Yat-Sen University under Dr. Xueqin Wang and Dr. Na You. Key expertise includes reinforcement learning, machine learning, and computational statistics. His work addresses challenges in off-policy evaluation, robustness in RL, and sparsity-constrained optimization. He has contributed to open-source tools like skscope and abess for efficient statistical computation. Research interests also span causal inference, high-dimensional data analysis, and algorithmic design for complex systems. Notable contributions include methodologies for genetic factor identification, spatial experimental design, and nonparametric statistical inference. Jin’s research bridges theoretical advancements with practical software implementations to address real-world computational and statistical challenges.
Mark Schankerman is a Professor of Economics at the London School of Economics (LSE), leading roles include directing the MSc in Economics and PhD Placement. He holds a PhD from Harvard University, with prior roles at the University of Arizona and the European Bank for Reconstruction and Development. His expertise spans innovation, patents, industrial economics, and law and economics. Education: PhD in Economics, Harvard University MA in Economics, Harvard University BA in Economics (Magna cum Laude, Phi Beta Kappa), Brandeis University Research Interests: Focuses on intellectual property rights, cumulative innovation, university technology transfer, and policy impacts on innovation ecosystems. His work bridges law, economics, and technology, addressing global challenges like drug accessibility and patent system reforms. Recent studies include patent screening mechanisms and global diffusion of pharmaceuticals. Professional Contributions: Editorial roles at Journal of Industrial Economics , Economics of Transition , and RAND Journal of Economics Consultant to USPTO, OECD, and UK Government on IP policy Visiting professorships at Tilburg University, Tel Aviv University, and Toulouse School of Economics Awards: Recipient of the Feldberg Prize for Best Student in Economics (Brandeis University). Grants & Leadership: Directed policy studies at the EBRD and led grant-funded research on patent systems Advisor to multilateral institutions like the World Bank and OECD Labs/Teams: Active in LSE’s STICERD Economics of Industry Programme, focusing on industrial economics and innovation policy.
John J Cannon is a Professor in the School of Mathematics and Statistics at the University of Sydney. He is a member of the Computational Algebra research group and maintains an office in Room 618 of the Carslaw Building. His work has significantly contributed to the field of computational group theory and algebraic computation. University: University of Sydney School: School of Mathematics and Statistics Department: Computational Algebra Position: Professor Professor Cannon's research primarily focuses on computational algebra, group theory, and finite groups. His work has been instrumental in developing algorithms for permutation groups, matrix groups, and computational representation theory. He has made substantial contributions to the understanding of subgroup structures, conjugacy classes, and modular representations in finite groups. His publications demonstrate a consistent trajectory from foundational work in the 1970s through to cutting-edge research in computational algebra up to 2020. The trend in his recent work shows a continued focus on structural computations in large finite groups, with increasing sophistication in handling modular representations and computational challenges in group theory. Professor Cannon is best known as one of the principal developers of the Magma computational algebra system, which has become a standard tool in computational algebra and number theory. His work on Magma has enabled researchers worldwide to perform complex algebraic computations that were previously infeasible. Throughout his career, Professor Cannon has maintained extensive collaborations with leading researchers in computational algebra including Derek Holt, William Unger, Allan Steel, and others. These collaborations have resulted in numerous influential publications that have shaped the field of computational group theory.
Augusto Gerolin is an Assistant Professor jointly appointed in the Departments of Mathematics and Statistics and Chemistry and Biomolecular Sciences at the University of Ottawa. He holds a Tier II Canada Research Chair in Artificial Intelligence at the Interface of Chemistry and Mathematics. His research focuses on Optimal Transport Theory, Mathematical Physics, Theoretical and Computational Chemistry, and Machine Learning. Gerolin’s work bridges quantum chemistry, mathematical analysis, and computational methods, with applications in Density Functional Theory and quantum information science. He obtained his PhD from the University of Pisa and was a Marie Skłodowska-Curie fellow at Vrije Universiteit Amsterdam. He is a member of the European Laboratory for Learning and Intelligent Systems (ELLIS) and leads a research group exploring AI-driven solutions in chemistry and mathematics. His current projects include developing optimal transport frameworks for quantum systems, advancing machine learning algorithms in scientific computing, and fostering collaborations across disciplines through initiatives like the OQMG Network. Gerolin’s research has led to advancements in multi-marginal optimal transport, entropy-regularized methods, and the strong-interaction limit of density functional theory. His group actively collaborates with institutions worldwide, including the Fields Institute, IPAM, and the University of Genoa. He has supervised numerous PhD, Master’s, and undergraduate students, many of whom have contributed to cutting-edge studies in computational chemistry, quantum algorithms, and mathematical analysis. Key awards include the Canada Research Chair designation, and his work has been supported by grants from NSERC, MITACS, and the University of Ottawa. Gerolin is also committed to diversity in science, endorsing principles such as the Diversity Axioms, and advocates for academic solidarity with researchers affected by global conflicts.
Pablo Timoner is a Researcher at the Institute of Global Health, part of the Faculty of Medicine at the University of Geneva. He holds a PhD in Environmental Sciences (2021) and a Master’s in aquatic ecology (2017). His work focuses on climate change impacts on biodiversity, geospatial modeling for health accessibility, and river ecosystem dynamics. Currently, he collaborates with the WHO on geospatial models to enhance healthcare accessibility in emergencies and fragile contexts. Education : PhD in Environmental Sciences, University of Geneva (2021) Master’s thesis on aquatic macroinvertebrates in restored river channels, University of Geneva (2017) Research Interests : Climate change impacts on biodiversity, geospatial health service modeling, river ecosystem resilience, and freshwater invertebrate ecology. His work integrates GIS tools, biostatistical approaches, and environmental data to address global challenges in health and ecology. Articles Trends : Recent publications emphasize snow cover dynamics in Swiss alpine regions, healthcare accessibility modeling in Mali, and biodiversity shifts in freshwater ecosystems. Tools like the inAccessMod R package reflect his focus on open-source geospatial solutions. Scientific Awards : No awards explicitly listed. Advising & Grants : Collaborates on WHO-funded projects and contributes to initiatives like EUROPONDS. No formal advisees listed. Labs/Teams : Active member of the GeoHealth group, focusing on global health and environmental data integration.
Ruth Breu is a Full Professor and Dean of the Faculty of Mathematics, Computer Science and Physics at the Universität Innsbruck, where she also leads the Quality Engineering research group. She has been a key figure in the Department of Computer Science since 2002 and served as its Head from 2013 to 2024. Her academic journey began with a PhD summa cum laude from the University of Passau in 1991, followed by a habilitation at the Technical University of Munich in 1999. Her research interests include: Quality Engineering Model and Security Engineering Requirements and Software Development Processes Enterprise Architecture Management Threat Intelligence and Digital Twins Her recent publications reflect a strong focus on model-based systems, automated programming assessment, security engineering, and digital twins in construction and energy systems. She frequently collaborates with researchers such as Michael Felderer, Clemens Sauerwein, and Philipp Zech, contributing to advancements in software testing, threat intelligence sharing, and cyber-physical systems. Notable awards include her PhD awarded summa cum laude. She has also been actively involved in national research governance, serving on the board of the Austrian Science Fund (FWF) from 2011 to 2020. She co-founded Txture GmbH in 2017 and holds advisory roles at Universität Passau and FH OST. Ruth Breu advises several students and leads a vibrant research group. Her leadership extends to organizing workshops and contributing to major conferences in software engineering and enterprise modeling. She is deeply engaged in both academic and applied research, bridging theory and practice in IT quality and security.
Linda Castañeda is a Professor of Educational Technology in the Department of Didactics and School Organization at the Faculty of Education, University of Murcia, Spain. Born in Bogotá, Colombia, and based in Murcia, she holds a PhD in Educational Technology from the University of the Balearic Islands. She is a leading figure in digital transformation in higher education, coordinating major European projects such as CUTIE and DALI, and directing strategic research contracts with the European Union's Joint Research Center. Her research focuses on educational technology, digital leadership, AI in education, and digital literacy. She has conducted international research stays at prestigious institutions including the Open University (UK), University of Oxford, UC Berkeley, and UJI. She is actively involved in editorial roles for top journals such as the European Journal of Educational Technology in Higher Education , Journal of New Approaches in Educational Research , and Educational Technology Research & Development . Linda leads the development of open educational resources, such as the course Strategic Leadership for Digital Transformation in Universities , adapted for the Spanish context. Her recent work emphasizes integrating AI into pedagogical practices, rethinking student roles, and fostering critical engagement with technology. She is deeply committed to ethical, people-centered, and pedagogically grounded digital transformation in education. She has contributed to national and European frameworks, including the University Digital Teaching Competence Framework (MCDDU) and the UNIDIGITAL accreditation project. Her publications reflect a strong focus on institutional change, teacher development, data literacy, and open, collaborative knowledge creation. Member, Editorial Board – European Journal of Educational Technology in Higher Education Member, Editorial Board – Journal of New Approaches in Educational Research Member, Development Editorial Committee – Educational Technology Research & Development (ETR&D) Member, GITE – Interuniversity Journal of Research in Educational Technology Linda mentors students through innovative teaching methods involving AI-enhanced reflection, role-based learning, and collaborative blogging. She emphasizes metacognition, feedback integration, and digital fluency. Her projects involve cross-institutional collaboration across 35 Spanish universities and European partners, demonstrating her leadership in shaping the future of digital education. She maintains an active blog, Educational Mushware , where she reflects on ideas over tools—'MUSHWARE' being the conceptual and creative layer beyond hardware and software. Her vision is for education to be transformed not by technology alone, but by thoughtful, human-centered innovation.
Mariana Gonzalez Boluda is a Lecturer in Spanish Language at the Department of Languages and Cultures, School of Literature and Languages, University of Reading, UK. She brings over two decades of international teaching experience from France, Jamaica, the USA, and the UK, and is actively engaged in pedagogical innovation and research in applied linguistics. Educational Background: PhD in Applied Linguistics, University of Las Palmas de Gran Canaria, Spain MEd in Open and Distance Education Learning, UNED, Spain DEA in Development of Multimedia and New Methodologies in Foreign Language Teaching, UNED, Spain BA in Hispanic Philology, University of Murcia, Spain Her research centers on enhancing language education through critical and multimodal approaches. She investigates how digital tools, film, and hybrid learning environments can develop intercultural competence, writing skills, and student autonomy. Her work emphasizes sustainability, inclusivity, and social justice in Spanish language teaching, particularly through decolonizing curricula and integrating gender-inclusive language. She actively promotes learner engagement via collaborative and project-based methods. Her recent publications and conference presentations reveal a strong thematic trend toward digital innovation, critical pedagogy, and social inclusion in language education. She frequently explores the use of blogs, wikis, social media, and virtual platforms to support language acquisition and autonomy, especially in multilingual and international contexts. Her scholarship bridges theory and practice, aiming to transform traditional language classrooms into dynamic, equitable, and socially aware learning spaces. Professional Affiliations and Networks: Member, ELE UK Member, ASELE Member, FILTA Special Interest Group (SIG) Member: SIG ELE UK on 'Decolonisation of Spanish Language Teaching' SIG AULC on 'Pedagogical Approaches to Language Variation' ReN Learner Autonomy, AILA DIM-EDU Pedagogies, Innovation y Multimedia Mariana Gonzalez Boluda is a Fellow of the Higher Education Academy, affirming her commitment to excellence in teaching. She teaches advanced Spanish language modules (SP2L3/4, SP3L3/4) and integrates her research directly into her pedagogy. She has no listed grants or advisees in the provided text, but her leadership in educational research networks and conference contributions highlights her active role in shaping contemporary language teaching practices. Labs and Teams: She contributes to collaborative academic initiatives through her involvement in international research networks and special interest groups focused on learner autonomy, multimedia pedagogy, and inclusive language teaching. These networks function as distributed research teams advancing innovation in language education across borders.
