Sancho Salcedo Sanz is a Full Professor at the Universidad de Alcalá, affiliated with the Signal Theory and Communications Department and the GHEODE Research Group. His work focuses on applying machine learning and optimization techniques to energy systems, climate science, and environmental modeling. He holds PhDs from Universidad Complutense de Madrid (2019) and Universidad Carlos III de Madrid (2002). Key research interests include deep learning for energy price prediction, spatio-temporal climate analysis, and hybrid models for renewable energy forecasting. His GHEODE group develops optimization algorithms for network design and distributed systems. Recent publications highlight advancements in extreme weather prediction, smart grid optimization, and explainable AI for environmental monitoring. He has pioneered methodologies like Autoencoder-based flow analogues for heatwave reconstruction and multi-method ensembles for energy demand modeling. Labs/Teams: Leader of the GHEODE Group, specializing in modern heuristics and network design. Collaborates extensively on interdisciplinary projects combining AI with environmental and engineering applications.
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.
Professor Amelia Thorpe of the University of New South Wales School of Law specializes in planning, property and environmental law with a focus on mobility and urban governance. Her sociolegal approach integrates professional experience in public interest environmental law and planning, including acting as Commissioner in the Land and Environment Court of NSW and membership on the Independent Liquor and Gaming Authority. BEnvDes & BArch (Hons), University of Western Australia BPolSt (Hons), Murdoch University BA (Jurisprudence), Oxford LLM, Harvard Law School PhD, Australian National University Her research explores urban governance through projects like Owning the Street: The Everyday Life of Property (MIT Press, 2020) and current $2M+ in competitive funding including: Australian Research Council Linkage Project (2025-2028): Aboriginal-led pathways James Martin Institute Policy Challenge Grant (2023-2024): Data-driven mobility Reliable Affordable Clean Energy CRC (2020): EV infrastructure She has held visiting appointments at UC Berkeley, McGill, and Paris IAS. Her 12 PhD supervisees include: Matthew Idiculla (constitutional law) Amarnath Boopalam Manjunath (street vendors) Alice Palithorpe (climate displacement) Major awards include: Australian Legal Research Awards (2022) Legal Innovation Index winner (2016) Vice-Chancellor’s Teaching Excellence (2014)
Professor Patrick Manu is a faculty member at the University of the West of England (UWE Bristol), holding the position of Professor of Innovative Construction and Project Management within the School of Architecture and Environment. He specializes in construction management, project management, quantity surveying, and occupational safety and health. His research focuses on occupational health and safety, sustainable construction, digital construction technologies, and BIM integration. He has secured funding from EPSRC, DFID, and other institutions for projects like developing web-based safety tools and exploring immersive technologies for safety training. Patrick holds a PhD in Construction Project Management from the University of Wolverhampton, a BSc (First Class Honours) from Kwame Nkrumah University of Science and Technology, and a PGCert in Academic Practice from City University London. He is a Chartered Member of the Chartered Institute of Building and a Fellow of the UK Higher Education Academy. His research interests include BIM applications, Industry 4.0 technologies, circular economy in construction, and AI-driven safety solutions. He has published extensively on topics such as safety risk analysis, UAV applications, and pandemic-era construction safety. He serves as a reviewer for EPSRC, Newton Fund, and leading journals like Safety Science, and chairs committees for organizations like the International Construction Measurement Standards (ICMS). Patrick has held academic positions at institutions including The University of Manchester and KNUST, and his industry experience includes roles in quantity surveying and developing digital tools for construction cost estimation. He leads collaborative projects involving academia and industry partners, emphasizing practical solutions for construction challenges.
Yi Zhu is a Professor of Marketing and holder of the Margaret J. Holden and Dorothy A. Werlich Endowed Professor at the Carlson School of Management, University of Minnesota . His work bridges Industrial Organization , Quantitative Marketing , and Chinese Economy with a focus on digital advertising, platform economics, and consumer search behavior. Education PhD in Business Administration, University of Southern California (2013) MA in Economics, University of British Columbia (2004) MA in Management, Shanghai Academy of Social Sciences (2002) BE in Industry Engineering, Shanghai University of Electric Power (1998) His research applies Industrial Organization to Marketing , examining online auctions , advertising mechanisms , media slant , and Chinese economic dynamics . Recently, he has explored two-sided platforms and surge pricing effects on consumer complaints. Publications span Marketing Science , Management Science , and Journal of Marketing Research , with work highlighted in Harvard Business Review and Forbes . His advertising research includes auction design, TV-to-online search interactions, and budget-constrained advertiser behavior. Scientific Awards Winner of John D.C. Little Award (2015) Winner of Don Morrison Long Term Impact Award (2023) 3M Nontenured Faculty Grant (2013-2016) Marketing Science Institute (MSI) Scholar (2022, 2023) Holds the Carlson School Outstanding Teaching Award (2022) and serves as Associate Editor for Marketing Science . Teaching includes Marketing Analytics for MBAs and Marketing Strategy for undergraduates, with consistently high instructor ratings. Referees for top journals like Management Science and Information Systems Research .
Dan Steinberg is a senior research scientist and team leader of the Decisions & Statistical Learning team at CSIRO Data61 in Canberra, Australia. His expertise lies in probabilistic machine learning, variational inference, Bayesian deep learning, causal inference, and their application to domains spanning synthetic biology, geospatial analytics, and algorithmic fairness. Education PhD in Computer Vision / Machine Learning (2013) – University of Sydney, Australian Centre for Field Robotics Bachelor of Engineering (Mechatronics, First-Class Honours) – University of Sydney (2008) Bachelor of Commerce (Finance) – University of Sydney (2008) Research Interests Steinberg’s core research agenda revolves around building scalable probabilistic models that can learn efficiently from limited or noisy data and provide principled uncertainty estimates. Key themes include: Variational Inference & Bayesian Deep Learning: developing lightweight yet powerful algorithms for approximate posterior inference in complex models (e.g., Aboleth, Revrand). Active Learning & Experimental Design: creating methods that decide which experiments or measurements will maximise information gain, with recent focus on in-silico protein engineering via Variational Search Distributions (VSD). Causal Inference: leveraging machine-learning tools to perform robust observational causal studies for evidence-based policy, including work on youth well-being and academic outcomes. Algorithmic Fairness: translating normative notions of equity into quantifiable objectives for regression-based decision systems. Large-scale Spatial Analytics: Landshark—an open-source TensorFlow toolkit for supervised learning on massive geospatial raster datasets. Notable Software & Tools Aboleth: A minimal-overhead TensorFlow framework for Bayesian deep learning. Landshark: Command-line tools for large-scale spatial inference. Revrand: Scalable Bayesian generalised linear models with non-conjugate likelihoods. libcluster: Extensible C++ library for hierarchical Bayesian clustering. Scientific Awards Oral Presentation Award – ICML 2025 Workshop on Scaling up Intervention Models (SIMS) Oral Presentation Award – NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty (BDU) Oral Presentation Award – NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning Spotlight Paper Award – NeurIPS 2014 (Extended and Unscented Gaussian Processes) Research Team & Collaborations As Team Leader – Decisions & Statistical Learning at CSIRO Data61, Steinberg directs a multi-disciplinary group that partners with government agencies (e.g., Jobs and Skills Australia, Australian Institute of Health and Welfare) and industry to deploy machine-learning solutions at scale. He has previously held roles as Principal Researcher at Gradient Institute (2019-2023), Senior Research Engineer at CSIRO Data61 (2016-2019), Researcher at NICTA (2013-2016), and Research Associate at the University of Sydney (2012-2013).
Dr. BARANYA Sándor is an Associate Professor and Head of the Department of Hydraulic and Water Resources Engineering at the Budapest University of Technology and Economics, Faculty of Civil Engineering. He holds key administrative roles, including Faculty Council Representative, Chairman of the Economic Committee, and Erasmus Committee Member. His office is located in Building K, Room MF 19, and he can be contacted via email or phone. His research spans sediment transport , river morphology , microplastic pollution , and computational fluid dynamics (CFD) . He employs innovative methods such as acoustic mapping, machine learning, remote sensing (Sentinel-2, Landsat), and numerical modeling to study large river systems, particularly the Danube. His work addresses ecological impacts, including thermal pollution from power plants and microplastic distribution. Recent publications (2023–2025) focus on: Sediment-microplastic dynamics using integrated field-data and AI Historical river regulation impacts CFD-based restoration strategies Advanced monitoring techniques (e.g., acoustic velocimetry, deep learning for riverbed analysis) He teaches courses including Hydraulics , Hydromorphology , and Water Utilisation & Damage Prevention , and mentors students in TDK (Research Society) projects on sediment transport, river habitats, and microplastics. He participates in EU initiatives like DanubeSediment for transnational sediment management.
João Pedro Machado Vitorino is a part-time lecturer and researcher at the Polytechnic Institute of Porto's School of Engineering, affiliated with GECAD. He is pursuing a Ph.D. in Informatics Engineering (Artificial Intelligence) at the University of Porto and holds an MSc in Artificial Intelligence Engineering. Education : Ph.D. (in progress), MSc, and BSc in Informatics/Artificial Intelligence Engineering Research : Focuses on machine learning robustness, explainability, and adversarial attack simulation for cybersecurity applications Projects : Involved in 7 EU/National R&D initiatives (2021-2025), including BEHAVIOR (2024-2025) and CYDERCO (2023-2025) His recent publications (2023-2025) span cybersecurity datasets , adversarial learning , malware detection , LLM security , and energy-efficient AI . He co-organized the 36th European Simulation & Modelling Conference (2022) and peer-reviewed for Pattern Recognition and Computers & Security . Awards : IEEE Outstanding MSc Thesis (2023), Engineers Association Innovation Award (2024), multiple merit certificates Skills : Machine Learning, AI Security, Network Analysis, and 3 professional certifications (Cisco, Microsoft, Airbus)
Christoph Hönnige is Professor and Chair for Comparative and German Politics at the Institute of Political Science, Faculty of Philosophy, Leibniz University Hannover. He also holds leadership roles including Chair of the Joint Examination Committee for Political Science degree programmes, Deputy Director and Deputy Managing Director of the Institute, and represents professors on several faculty bodies. He is additionally affiliated with the Leibniz Center for Science and Society (LCSS) and the Center for Inclusive Citizenship (CINC). Education PhD, University of Potsdam (supervisors: Herbert Döring & André Kaiser) Graduate studies, University of Konstanz Research Focus Hönnige’s scholarship centres on three interconnected areas: Judicial Politics (comparative analysis and the German Federal Constitutional Court), Legislative Politics (expert consultation and decision-making under institutional constraints), and Higher Education (ethics, administration, and student behaviour). Across these fields he investigates how formal and informal institutional rules shape individual and collective behaviour, and how citizens’ trust in institutions and decision-making procedures is formed and maintained. Recent Publication Trends Since 2020 his peer-reviewed output has addressed four principal themes: (1) governance and organisational diversity in German universities, (2) temporal strategies in bicameral legislatures, (3) legitimacy and public perceptions of constitutional courts, and (4) integrity and assessment practices in digital higher-education settings. Methodologically, the work blends large-N quantitative analysis, survey experiments, and text mining, often with cross-national comparative designs. Scientific Awards & Recognitions While no standalone prizes or medals are explicitly listed, Hönnige’s continuous funding by the German Research Foundation (DFG)—including co-leadership of the project "The Federal Constitutional Court as a Veto Player" —testifies to peer recognition of his research excellence. Advising & Grants As principal investigator on the DFG-funded project on the Federal Constitutional Court he supervises doctoral and post-doctoral researchers. He also mentors BA and MA thesis students through weekly colloquia and is responsible for curricular design within the Politics programmes at Hannover. Labs & Research Groups He leads the Comparative and German Politics research group housed in the Institute of Political Science, coordinates the Constitutional Court Database (CCDB) project, and collaborates closely with interdisciplinary teams at LCSS and CINC that focus on science-society relations and inclusive citizenship respectively.
Chen Pan is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio's Klesse College of Engineering and Integrated Design. His research focuses on energy-harvesting embedded systems, low-power computing, and IoT network optimization through machine learning techniques. Ph.D. from University of Pittsburgh Specializes in transient computing for batteryless devices Develops reinforcement learning solutions for UAV-assisted IoT systems Chen's recent publications emphasize energy-aware scheduling, non-volatile memory optimization, and sustainable communication protocols. His work intersects spatiotemporal modeling, fault tolerance, and resource-constrained AI execution across heterogeneous architectures.
Professor Vasilis Katos is a Professor in Cyber Security at Bournemouth University, specializing in digital forensics, incident response, and intellectual property security. With over 160 publications and extensive industry experience as an Information Security Consultant, he serves as an expert witness in criminal courts in both the UK and Greece. His research has significant impact in digital forensics for intellectual property infringement investigations through collaborations with the EU Intellectual Property Office (EUIPO) and UNICRI. Professor Katos holds a Diploma in Electrical Engineering from Democritus University of Thrace, an MBA from Keele University, and a PhD in Computer Science (network security and cryptography) from Aston University. He is a certified Computer Hacking Forensic Investigator (CHFI) with extensive practical experience in cybersecurity. His research primarily focuses on digital forensics and incident response, with recent emphasis on intellectual property infringement investigations, IoT security, blockchain applications, and traffic prediction systems. His work bridges academic research with practical security applications, particularly in intellectual property protection and smart city security frameworks. Professor Katos has coordinated significant research projects including Illegal IPTV in the European Union and IP Infringement on online trading platforms, funded by the EUIPO Observatory. His extensive publication record shows strong trends in digital forensics, cybersecurity for intellectual property protection, IoT security, and increasingly in smart city security frameworks. The research demonstrates a progression from foundational cybersecurity work to specialized applications in intellectual property protection and circular economy security models, with recent incorporation of AI and machine learning techniques for threat intelligence and traffic prediction. Certified Computer Hacking Forensic Investigator (CHFI) Editorial Board Member of Computers & Security Journal Professor Katos has successfully supervised multiple PhD students including Amalia Damianou (Digital Forensics in Smart, Circular Cities), Christos Iliou (Machine Learning Based Detection and Evasion Techniques for Advanced Web Bots), and Mohammed Al Qurashi (Intrusion Detection for IoT). He has secured significant research funding including the ECHO project (European network of Cybersecurity centres), IDEAL-CITIES, and multiple EUIPO-funded initiatives focusing on intellectual property protection. His work connects with the Centre for Intellectual Property Policy & Management (CIPPM) at Bournemouth University, where he contributes to research on intellectual property in emerging technologies. Professor Katos maintains active collaborations with international organizations including UNICRI and the EU Intellectual Property Office, focusing on practical applications of digital forensics in intellectual property protection.
Steven L. Johnson serves as Associate Professor of Commerce and Area Coordinator for Information Technology & Innovation at the University of Virginia School of Commerce. He also holds significant leadership positions as Faculty Lead of the Digital Technology for Democracy Lab at the University of Virginia Karsh Institute of Democracy and Faculty Affiliate for the Thriving Youth in a Digital Environment research initiative. His academic journey includes a Ph.D. in Information Systems from the University of Maryland, an MBA from The College of William & Mary, and a B.S. in Computer Science from the same institution. Ph.D., Information Systems, University of Maryland M.B.A., The College of William & Mary B.S., Computer Science, The College of William & Mary Professor Johnson's research adopts a sociotechnical systems perspective examining how digital technology intersects with people, processes, and data to impact individuals, organizations, and society. His work spans online communities, social media, open innovation, and the application of social network analysis and computational linguistics to study team dynamics. He investigates critical societal issues including content moderation, algorithmic bias, echo chambers, filter bubbles, and the ethical implications of AI. His ongoing collaborations explore how digital technology supports democracy through information distribution and discovery, its role in healthy youth development, and methods to minimize bias while promoting fairness in AI deployments. His research has appeared in top journals including MIS Quarterly, Organization Science, Information Systems Research, Information, Communication & Society, and Information & Organization. Analysis of his publication trends reveals a consistent focus on the societal implications of digital technology, with increasing attention to AI ethics, content moderation, and democratic processes in recent years. His methodological approach combines computational social science with network analysis to examine large-scale digital interactions. Professor Johnson has received numerous prestigious awards recognizing his scholarly contributions: Association for Information Systems Distinguished Member, Cum Laude (2021) University of Virginia Research Achievement Award (2021, 2022) MISQ Best Paper Award (2020) AOM OCIS Division Best Conference Paper Award (2018) Prix académique de la recherche en management (2015) As an educator, Johnson has taught numerous undergraduate and graduate courses covering systems and strategy, business analytics, information technology management, and specialized topics including Managerial View of AI and Race in Commerce. He has provided significant service to the academic community as Associate Editor at Information Systems Research, previously at MIS Quarterly, and as Senior Editor at Information & Organization. He serves on the executive committee of the Communication, Digital Technology, and Organizations division of the Academy of Management and was Program-Chair Elect for the 2025 Annual Meeting. His community engagement extends beyond academia through roles as Commissioner on the Charlottesville Economic Development Authority and involvement with local organizations including the Fifeville Neighborhood Art Gallery. Professor Johnson leads the Digital Technology for Democracy Lab at the Karsh Institute of Democracy, which examines how digital technology supports democratic processes through information distribution and discovery. He is also affiliated with the Thriving Youth in a Digital Environment research initiative, investigating how youth benefit from or are harmed by digital environments. His technical infrastructure contributions include operating the cville.online Mastodon server and managing the Fifeville air quality monitor.
Associate Professor Mehmet Kizil is the Mining Engineering Program Leader at the School of Mechanical and Mining Engineering, The University of Queensland. With a career spanning 25+ years, he holds a Bachelor of Mining Engineering (1986) from Dokuz Eylul University (Turkey) and PhD (1993) from the University of Nottingham (UK). His affiliations include being an affiliate of Future Autonomous Systems and Technologies and active participation in Mining Education Australia. School of Mechanical and Mining Engineering Australian Research Council (ACARP, CRCTiME, MRIWA, SIMTARS, industry partners) Research interests focus on mine planning/design, production optimization, computer/virtual reality applications, and mine ventilation systems. His 2025-2024 publications highlight innovations in FMIPCC systems, methane dispersion modeling, digital twins for mineral processing, and sustainable underground mining. Notable scientific achievements include being recognized as Higher Education Academy Senior Fellow (2018) and receiving national teaching awards. His work with industry partners (Newcrest, Rio Tinto, BHP, Xstrata, Anglo American, Origin Energy, Iluka Resources) has secured over $3M in research funding.
Professor Ying Xie is a leading academic at Cranfield University's School of Management, holding the position of Professor of Supply Chain Analytics. Her work bridges engineering, data science, and business management across diverse sectors including maritime logistics, healthcare, and disaster response. Her educational background includes a BEng, MSc, and PhD in Management Science from Coventry University. Key research interests focus on supply chain digitalization and decarbonization , renewable energy supply chain configuration , and AI applications in operational resilience . Her work consistently integrates machine learning with real-world business challenges, particularly in port management and sustainability. Recent publications reveal strong trends in maritime decarbonization (25%), AI-driven supply chain optimization (30%), and healthcare systems resilience (20%). Her research increasingly addresses climate adaptation through circular economy models and clean energy transitions. Principal Fellow of the Higher Education Academy (HEA) Expert reviewer for UKRI MRC, British Academy, and EU Horizon Professor Xie has supervised numerous PhD completions and secured two dedicated scholarships for port management and digital twin research. Her £20m+ grant portfolio includes major projects with EPSRC (£7.6m Net Zero Aviation CDT), Innovate UK (£174k Sustainability Platform), and EU Horizon (£5m MEDiate disaster management). She actively collaborates with the Port of Dover, Ocado Technology, and NHS England. She leads the Co-Innovation Group in the UK National Clean Maritime Research Hub and directs academic activities for the EPSRC Centre for Doctoral Training in Net Zero Aviation, shaping national maritime strategy through the Department for Transport's 'UK Ports the Future' report.
Sergio Baranzini is a Professor in the Department of Neurology at the University of California, San Francisco (UCSF) School of Medicine and a member of the UCSF Weill Institute for Neurosciences. With a distinguished career spanning over two decades at UCSF, Dr. Baranzini has established himself as a leading researcher in multiple sclerosis (MS) and neuroimmunology. Dr. Baranzini earned his BS/MS and PhD in Biochemistry/Biotechnology and Human Molecular Genetics from the University of Buenos Aires, Argentina, completing his PhD with honors in 1997. He then pursued postdoctoral training in neurogenetics at UCSF before joining the faculty in 2003. His research focuses on the genetic, genomic, and immunological aspects of multiple sclerosis, with particular emphasis on the gut-brain axis and microbiome's role in neuroinflammation. Dr. Baranzini's research employs a multidisciplinary approach integrating wet lab techniques (including DNA microarrays, proteomics, and laser capture microdissection) with dry lab analytical approaches (bioinformatics, complexity theory, and mathematical modeling). His work has revealed critical insights into MS pathogenesis, particularly how gut microbiota influences disease development and progression. Recent groundbreaking studies have demonstrated how specific gut bacteria from MS patients can trigger MS-like disease in animal models and how microbial metabolites affect remyelination processes. His laboratory has secured significant funding through multiple NIH grants, including as Principal Investigator on projects examining the genetic basis of MS progression and post-GWAS approaches to identify cell-specific genetic pathways underlying MS risk. As evidenced by his extensive publication record in top-tier journals including Science, Nature, and PNAS, Dr. Baranzini's work represents some of the most innovative research in neuroimmunology and MS pathogenesis. National Multiple Sclerosis Society (US) Advanced Postdoctoral Fellowship (2001) National Multiple Sclerosis Society (US) Harry Weaver Neuroscience Scholar Award (2009-2014) Department of Neurology UCSF Endowed Chair in Neurology (2010) National Multiple Sclerosis Society Stephen C. Reingold Award (2015) Department of Neurology UCSF Distinguished Professorship in Neurology I (2019) Department of Neurology UCSF Neurology Research Incentive Program 2 (N-RIP2) (2023) Barancik Prize for Innovation in Multiple Sclerosis Research (2024) Dr. Baranzini serves as an ad-hoc reviewer for numerous specialized journals and is an elected member of the American Neurological Association. His laboratory (iMSMS) actively collaborates with interdisciplinary teams worldwide to integrate knowledge across research domains through systems biology approaches. His current NIH-funded research explores automated evidential support from raw data for relay agents in biomedical knowledge graph queries and investigates the genetic basis of progression in multiple sclerosis.
