Dr Duncan Smith is an Associate Professor in GIS and Visualisation at the Centre for Advanced Spatial Analysis (CASA) at University College London (UCL). He serves as Programme Co-Director for the MSc Urban Spatial Science, focusing on digital visualisation and Geographical Information Systems (GIS) education. His research emphasizes urban sustainability, transport accessibility, and interactive urban visualisation, with a particular interest in global mega-cities like London, Singapore, and São Paulo. Dr Smith holds a PhD from UCL (2011), an MSc from the University of Edinburgh (2005), and a BA (2003). His recent projects include leading the ESRC-funded Driving Urban Transitions project (2024) exploring sustainable travel in small cities and outer metropolitan areas. Previously, he was Co-Investigator on the SIMETRI project (NSFC JPI Urban Europe) analyzing urban sustainability in London, the Randstad, and China's Greater Bay Area. His research interests span urban visualisation techniques, transport equity analysis, and polycentric urban development. Key areas include GIS-driven urban modelling, accessibility metrics, and the intersection of housing policy with sustainable urban form. His interactive visualisations, available on citygeographics.org , showcase innovative approaches to spatial data presentation. Dr Smith's work consistently addresses global sustainability challenges through geospatial methodologies. Recent studies highlight inequalities in transport accessibility and the spatial implications of urban policies. Upcoming projects will further investigate small-city mobility dynamics using multi-national collaborations with Amsterdam and Lisbon researchers.
Dr. Zara Ersozlu is a Senior Lecturer in Mathematics Education within the School of Education at the University of Newcastle, Australia. With a distinguished international career spanning multiple continents, she has held academic positions at prestigious institutions including North Carolina State University (USA), Gazi and Gaziosmanpasa Universities (Turkey), National Taiwan Normal University (Taiwan), The University of Western Australia, Murdoch University, and Deakin University. Her academic journey includes tenured positions as an Associate Professor and leadership roles as Department Head and Chair in teacher education disciplines. Currently, she teaches undergraduate and postgraduate courses in mathematics education, including Effective Pedagogies in Primary Mathematics, K-6 Mathematics, K-6 Numeracy, and Digitally Supported Learning. Dr. Ersozlu earned her Doctor of Philosophy from Firat University in Turkey and her Master of Art from Sakarya University. Her extensive academic preparation is complemented by five years of practical teaching experience in public schools prior to entering academia. This blend of theoretical knowledge and practical classroom experience informs her approach to teacher education and educational research. At the broadest level, Dr. Ersozlu's research investigates solutions to real-life problems impacting people's well-being, success, and capacity to achieve. Her scholarly work spans primary and secondary mathematics education, the psychology of mathematics (including metacognition, self-regulation, and anxiety), cross-cultural educational studies, teacher education, virtual simulated learning environments, and educational assessment. She has increasingly focused on the transformative potential of AI and machine learning in education, exploring how these technologies alter teaching, learning, and research processes. Her methodological expertise encompasses both quantitative and qualitative approaches, allowing her to effectively analyze both small and large educational datasets. Analysis of Dr. Ersozlu's recent publications reveals a strong emphasis on mathematics anxiety, teacher education, and the integration of technology in learning environments. Her work demonstrates a consistent focus on practical applications of educational research to address real-world challenges in mathematics education. The interdisciplinary nature of her research connects educational psychology, technology integration, and cross-cultural perspectives, with particular attention to how these elements intersect in teacher preparation and student learning outcomes. 2023 ATEA Research Recognition Award from the Australian Teacher Education Association 2021 Fellow of the Higher Education Academy (Advance HE, UK) 2010 Fellowship Program for Postdoctoral Researchers from the Council of Higher Education of Turkey Dr. Ersozlu is deeply committed to mentoring the next generation of scholars, currently supervising four PhD students and having successfully guided ten students to completion. Her grant portfolio includes significant funding for projects such as Best Practice Guidelines for RPL in Initial Teacher Education Programs ($60,000), Exploring the Reciprocal Relationship Between Mathematics Anxiety and Mathematical Resilience ($2,599), and multiple conference travel awards. She serves as an Associate Editor for several prominent journals including the International Electronic Journal of Mathematics Education and as Editor for Interdisciplinary STEM Education. Her editorial work reflects her standing as a respected voice in mathematics education research. Dr. Ersozlu's academic leadership extends to her role in developing innovative teaching approaches that integrate virtual simulation technology and learning analytics. Her work with TeachLivE™, a mixed-reality classroom simulation platform, demonstrates her commitment to creating authentic learning experiences for teacher education students. Through these initiatives, she bridges the gap between educational theory and classroom practice, preparing future educators to effectively implement evidence-based teaching strategies in diverse learning environments.
Mitchell A. Petersen is the Glen Vasel Professor of Finance and Director of the Heizer Center for Private Equity and Venture Capital at Kellogg School of Management, Northwestern University. He holds a Ph.D. in Economics from MIT (1990) and an AB in Economics from Princeton (1986, Summa Cum Laude). His research focuses on empirical corporate finance, particularly how firms finance investments, manage risk, and interact with financial intermediaries. Education: PhD, Economics, Massachusetts Institute of Technology (1990) AB, Economics, Princeton University (1986, Summa Cum Laude, Phi Beta Kappa) Professor Petersen's research examines the impact of information costs, technology, competition, and taxation on corporate financial decisions. He has published extensively on topics such as lending relationships, trade credit, capital structure, and panel data methodology. His recent publications emphasize corporate cash management, tax strategies, and credit market dynamics. These works explore cash accumulation motives, seasonal loan pricing, and the role of foreign tax policies in capital allocation. Scientific awards and recognitions include: Smith-Breeden Prize (Journal of Finance, 1995) Michael Brennan Award (Review of Financial Studies, 1998 & 2013) Sidney J. Levy Teaching Awards (1996, 1999, 2001, 2003, 2006, 2008, 2010, 2012) Kellogg Professor of the Year (2000) Richard J. Daley Award (Illinois Venture Capital Association, 2024) Professor Petersen has advised numerous academic programs, served on editorial boards of major finance journals, and contributed to financial research as a NBER Research Associate and Moody's Academic Advisory Committee member.
Anna Levina is an Assistant Professor for Computational Neuroscience at the University of Tübingen , affiliated with the Department of Computer Science under the Faculty of Science. Her research focuses on the self-organization of neuronal activity, critical dynamics in neural networks, and the excitation/inhibition balance in cortical circuits. Current positions: Assistant Professor (since 2018), Group Leader (2017-2018), Equality Officer (Computer Science) Previous roles: IST Fellow (2015-2017), Associated Researcher (2011-2015), Postdoc/PI (2011-2015), Postdoc (2008-2011) Her research integrates mathematical modeling , statistical physics , and computational neuroscience to study criticality phenomena, neural avalanches, and adaptive network dynamics. Key interests include: Self-organized criticality in neural systems Excitation/Inhibition balance mechanisms Network topology and dynamics Timescale analysis in neural processing Stochastic modeling of neural activity Recent publications reveal trends in understanding critical dynamics across biological and artificial networks, with applications to memory systems, sensorimotor integration, and disease modeling. She has received recognition as an IST Fellow .
Jo Wood is Professor of Visual Analytics in the Department of Computer Science at City, University of London, where she has been employed since January 14, 2000. Her work bridges computer science, geographic information science, and human-computer interaction, focusing on innovative methods for visualizing complex spatial and behavioral data. Her research interests center on visual analytics , information visualization , and geovisualization , with applications in transportation, public health, crisis response, and citizen science. She investigates how interactive visual interfaces can support exploratory data analysis, decision-making, and storytelling, particularly through small multiples, faceted views, and sketch-based rendering techniques. The trends in her recent publications reflect a consistent focus on user-centered design , spatial data abstraction , and interactive exploration of multivariate datasets. Her work often integrates real-world behavioral data such as GPS tracks, cycling patterns, and crowd-sourced information to build meaningful visual narratives and support analytical reasoning. Throughout her career, Jo Wood has contributed significantly to the advancement of visual analytics through high-impact publications in top-tier venues such as IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum. Her collaborations with researchers like Jason Dykes and Aidan Slingsby highlight her role in a vibrant research community. She has supervised numerous research projects and mentored students in visualization and geospatial analytics, though specific names are not listed in the provided text. Her work has been supported by various research grants, particularly in domains involving urban mobility, energy modeling, and crisis informatics, though grant details are not specified here. Jo Wood has also contributed to the design of visual analytics systems for applications including disease spread modeling, bicycle-hire scheme monitoring, and persuasive technology for health and leisure, demonstrating a strong commitment to impactful, interdisciplinary research.
Pekka Marttinen is a tenured Associate Professor of Machine Learning at Aalto University, Department of Computer Science, and leads the Machine Learning for Health (Aalto-ML4H) group within the Helsinki Institute for Information Technology HIIT. Education: M.Sc. in Applied Mathematics, University of Helsinki (2004) Ph.D. in Statistics, University of Helsinki (2008) Title of Docent in Information and Computer Science, Aalto University (2015) Research Focus: His methodological work spans large language models, reinforcement learning, deep learning, probabilistic machine learning, and causal inference . These techniques are applied to critical domains of healthcare, bioinformatics, statistical genetics, epidemiology, and personalized medicine . The group develops novel algorithms, theoretical guarantees, and open-source software that enable data-driven discovery and decision-making in medicine and biology. Publication Trends: Across 2022-2024 the lab has concentrated on (i) rigorous causal reasoning over temporal clinical data, (ii) principled uncertainty quantification in LLMs, (iii) representation learning for neural network comparison, and (iv) translational projects that turn raw EHRs into actionable clinical insights. Earlier work integrated high-dimensional genomics with metabolomics and mapped evolutionary forces in bacterial pathogens. Scientific Awards & Recognition: While no specific awards are listed, his sustained publication record in top-tier venues (NeurIPS, ICML, AISTATS, Nature Genetics, PLOS CB) and his role as responsible professor of the Machine-Learning, Data-Science and AI major signify significant peer recognition. Advising & Grants: Prof. Marttinen currently mentors 8 PhD students as primary supervisor and an additional 7 PhD students as co-supervisor. He has already graduated 8 PhDs since 2014. The group is supported through competitive funding including the Finnish Center for Artificial Intelligence (FCAI) doctoral program. Labs & Teams: He directs the Machine Learning for Health (Aalto-ML4H) research group, comprising postdocs Hans Moen, Ti John, Alexander Nikitin, Negar Safinianaini, Linli Zhang, Zhiyuan Li, and the above-mentioned PhD cohort.
Dr. Nemanja Stanišić is a Full Professor at Singidunum University's Faculty of Business, with a distinguished academic career spanning over 15 years. He holds a Ph.D. in Corporate Finance from Singidunum University (2010), an MBA in Finance from Lincoln University (2007), and a Bachelor's in Accounting from the University of Belgrade (2005). His expertise focuses on Corporate Finance, Banking, Audit, and Applied Statistical Analysis. His research integrates quantitative methods with economic theory, addressing topics such as audit opinion prediction using AI, tourism destination competitiveness, financial distress dynamics, and air pollution health impacts. He co-authored textbooks including Contemporary Exchange and E-business (2010) and Financial Statement Analysis (2024), and served as Editor-in-Chief of The European Journal of Applied Economics . He teaches courses from Financial Accounting to Advanced Financial Engineering at undergraduate, master's, and Ph.D. levels. The 15 most recent publications highlight his interdisciplinary approach: 7 in Finance/Audit, 5 in Tourism/Hospitality, and 3 in Environmental Health. Key trends include applying machine learning to audit quality (2023), multilevel modeling for hospitality satisfaction (2015-2019), and air pollution mortality analysis (2016). His work appears in high-impact journals like Tourism Management (IF 10.125) and Environmental Health (IF 4.986). He held administrative roles including Rector (2020-2021) and Vice President of Singidunum University. He served as Vice Dean for Student Affairs (2010-2011) and participated in TEMPUS projects for educational reform. He mentors graduate students extensively, advising 100+ bachelor's, 57 master's, and 4 doctoral theses, including international candidates. His visiting professorship at Bangkok's ICO NIDA and teaching in Austria-Singidunum joint programs reflect global engagement. Professional development includes advanced training at Utrecht University (Bayesian Modeling, 2019), Stanford (Mentoring, 2010), and NYU (Valuation, 2012). He reviews for top journals like Annals of Tourism Research and Cornell Hospitality Quarterly , with 1017 Google Scholar citations and 349 Scopus citations. Current research involves the Science Fund of Serbia's TOURCOMSERBIA project evaluating tourism competitiveness models.
Detlef F. Sprinz is a Senior Scientist at the Potsdam Institute for Climate Impact Research (PIK) and a Professor at the Faculty of Economics and Social Sciences of the University of Potsdam, Germany. During 2024-2025, he leads the project "AMaReNa - A Market for the Restoration of Nature" , focusing on carbon removals. His academic background includes a Ph.D. and M.A. in Political Science from the University of Michigan and an M.A. in Economics from the University of the Saarland. Research Interests: Climate policy at multiple levels, long-term policy design, evaluation of international/national institutions, European/international environmental policy, and modeling political decisions for sustainability. Notable Projects: Tandem Fellowship (2020-2022) for interdisciplinary course development, Visiting Researcher at University of Lund (2022-2023), and coordination of research at the Käte Hamburger Kolleg (2017). Publications emphasize climate cooperation under the Paris Agreement, effectiveness of environmental regimes, and predictive modeling for climate negotiations. His work spans empirical analyses of acid rain regulation, Kyoto Protocol implementation challenges, and bioenergy accounting errors. Scientific Awards & Memberships: Tandem Fellowship (German Stifterverband) Member, European Academy Co-founder, Ecologic Institute Teaching includes courses on global climate governance, political decision modeling, and environmental policy at the University of Michigan, Yale, University of Oslo, and University of Potsdam. He has contributed to IPCC’s Sixth Assessment Report as a Lead Author. Advisory Roles: Chairmanship of the European Environment Agency’s Scientific Committee (2009-2012), Senior Research Fellow at CICERO (2011-2013), and consultancy for governments, corporations, and think tanks.
Malgorzata Blicharska is a Senior Lecturer in Sustainable Development at Uppsala University, affiliated with the Department of Geosciences and the Institute for Research on Conflicts of Interest in Sustainable Social Transformation. Her work spans multiple research domains focused on sustainable natural resource management and policy implementation. Dr. Blicharska's research focuses on sustainable development with expertise in ecosystem services, biodiversity conservation, climate change governance, and the Water-Energy-Food-Ecosystem (WEFE) nexus. She integrates social science perspectives with environmental management, examining policy implementation and stakeholder engagement in conservation initiatives. Her work includes extensive research on urban ponds, recreational fisheries, and nature-based solutions, particularly focusing on ponds and wetlands as key components of sustainable landscape management. Her recent publications reveal a strong emphasis on transdisciplinary approaches to environmental challenges, with growing focus on nature-based solutions, drought vulnerability in forested regions, and governance aspects of implementing the WEFE nexus concept. Her work increasingly addresses justice dimensions in environmental management and stakeholder engagement in policy implementation. LANDPATHS: Swedish Environmental Protection Agency-funded program on multifunctional landscapes (coordinator) PONDERFUL: Horizon 2020 project on pond biodiversity and ecosystem services (WP lead) NEXOGENESIS: Horizon 2020 project on WEFE nexus policy integration (WP lead) Wet-Kit: Swedish Environmental Protection Agency project on wetland optimization PUDDLE-JUMP: Formas-funded project on small artificial waterbodies
Zhong-Ping Jiang is an Institute Professor at New York University Tandon School of Engineering, affiliated with the Department of Electrical and Computer Engineering, and holds cross appointments in Civil and Urban Engineering. He leads the Control and Network (CAN) Lab and contributes to research centers like the Center for Advanced Technology in Telecommunications (CATT) and C2SMARTER. His work focuses on nonlinear control, adaptive dynamic programming, and learning-based control with applications to autonomous systems, urban mobility, and computational neuroscience. He serves as Deputy Editor-in-Chief of the IEEE/CAA Journal of Automatica Sinica and has held editorial roles in multiple journals. Research interests include model-based and learning-based control for network systems, with emphasis on robotics, connected vehicles, and urban infrastructure. His contributions to nonlinear small-gain theory and robust reinforcement learning have advanced control methodologies for complex systems. Recent publications highlight trends in resilient control under cyberattacks, data-driven optimal control, and reinforcement learning applications in traffic signal optimization and autonomous driving. His work bridges theoretical advancements with real-world challenges in transportation and cyber-physical systems. Awards: Elected to the European Academy of Sciences and Arts (2024). Grants/Projects: Includes RAPID-funded studies on high-resolution agent-based modeling of epidemic spread and NSF-supported research on urban traffic networks. Labs/Teams: CAN Lab (focusing on control theory and networked systems), CATT (telecommunications innovations), and C2SMARTER (urban mobility solutions).
Dino Pedreschi is a Full Professor of Computer Science at the University of Pisa, affiliated with the Department of Computer Science (DI-UNIPI). He co-leads the Pisa KDD Lab, a joint research initiative between the University of Pisa and the Italian National Research Council’s Institute of Information Science and Technology, one of the earliest labs focused on data mining and knowledge discovery. His research spans Big Data Analytics , Social Network Analysis , Human Mobility Analysis , Privacy-by-Design , Explainable AI (XAI) , and ethical data mining . He is a pioneer in privacy-preserving data mining and has contributed significantly to understanding societal impacts of AI and big data. Recent publications highlight trends in explainable AI , fairness-aware data mining , urban mobility modeling , and socio-economic nowcasting , reflecting a strong interdisciplinary focus combining computer science, social science, and policy. Notable scientific awards include: Google Research Award on Privacy (2009) University of Pisa Ordine del Cherubino (2017) Pedreschi has played leadership roles in major conferences such as ECML/PKDD (Co-Chair 2004), ICDM (Vice-Chair 2005), and ICDE (Vice-Chair 2014). He founded the Business Informatics MSc program at the University of Pisa to train interdisciplinary data scientists. He has been a visiting scientist at the University of Texas at Austin, CWI Amsterdam, UCLA, and the Barabási Lab at Northeastern University. He actively contributes to European research initiatives including SoBigData++, FAIR, and TAILOR, and has advised on AI policy, including testimony before the Italian Parliament on AI and labor markets. He is a key member of the Pisa KDD Lab, a leading research group in data science and AI ethics, fostering collaboration between academia and public institutions.
Dr. HAJNAL Géza is an Associate Professor at the Budapest University of Technology and Economics (BME), Faculty of Civil Engineering, where he serves in the Department of Hydraulic and Water Resources Engineering. His office is located in Room K. ép / mf. 12/7, and he can be contacted via email at hajnal.geza@emk.bme.hu or phone at +36 1 463 2362. His teaching portfolio includes active courses such as Hydraulic Engineering, Water Management (BMEEOVVAT43) and Hydrometric Field Course (BMEEOVVAI44). Previously, he taught Hidrogeology (BMEEOGMMET3) and Hydrogeology of Subsurface Water (BMEEOGMDT81). HAJNAL's research specializes in hydrogeology , with emphases on karst aquifer dynamics, groundwater flow modeling, climate impacts on hydrology, and hydraulic engineering. His work integrates field measurements (e.g., drip-water monitoring in Buda Castle Cave) with advanced numerical modeling to address complex hydrological challenges in Hungarian watersheds. Analysis of his 15 most recent publications (2013–2025) reveals dominant themes: 73% focus on karst/fractured aquifers , 20% on hydrological modeling techniques , and 7% on socio-environmental conflicts. Recurrent technical subfields include seepage flow validation, transmissivity determination, and rainfall-runoff sensitivity. No scientific awards, grants, student advisees, or lab affiliations are documented in the provided materials.
Professor Charlotte Deane is a leading academic in structural bioinformatics, holding the position of Professor at the University of Oxford's Department of Statistics and Executive Chair of the Engineering and Physical Sciences Research Council (EPSRC). She leads the Oxford Protein Informatics Group (OPIG), focusing on protein structure prediction, immunoinformatics, and AI-driven drug discovery. Her research integrates computational methods with biological insights, developing tools widely used in academia and industry. Prior roles include Head of the Department of Statistics, Deputy Head of the Mathematical, Physical and Life Sciences (MPLS) Division at Oxford, and Chief Scientist of Biologics AI at Exscientia. During the COVID-19 pandemic, she served on SAGE and as UKRI's COVID-19 Response Director. In 2022, she was awarded an MBE for her contributions to pandemic research. Her research group's work spans antibody design, T-cell receptor analysis, and small molecule discovery, with a focus on open-source software development. Current projects include advancing AI methods for protein structure prediction and therapeutic antibody engineering. Recent publications highlight innovations in computational drug design, antibody developability, and machine learning applications in structural biology.
William B Gartner serves as the Bertarelli Foundation Distinguished Professor of Family Entrepreneurship at Babson College's F.W. Olin Graduate School of Business, where he also directs research at the Bertarelli Institute for Family Entrepreneurship. Having joined Babson's faculty in 2017, Gartner brings over 40 years of experience studying entrepreneurial phenomena, with particular expertise in family entrepreneurship dynamics. He previously held distinguished chairs at the University of Southern California and Clemson University, establishing himself as a leading scholar in the field. Gartner earned his PhD, MBA, and BBA from the University of Washington, forming the foundation for his extensive research career. His academic journey began during entrepreneurship's early days in the late 1970s when he took one of the first entrepreneurship courses as an MBA student at the University of Washington, when only six students initially enrolled in the class. Gartner's research primarily explores how families act entrepreneurially, examining topics including entrepreneurial legacy, intergenerational knowledge transfer, and the transformation of family businesses across generations. His work bridges entrepreneurship theory with practical applications, particularly focusing on how entrepreneurial legacies can drive innovation in family businesses. He is particularly interested in the linguistic innovations entrepreneurs employ and how storytelling shapes entrepreneurial identity and practice. His scholarship has evolved to incorporate humanities perspectives, recognizing that literature, philosophy, and history provide valuable insights into entrepreneurial thinking and behavior. Analysis of Gartner's recent publications reveals a strong emphasis on family entrepreneurship as an ongoing process rather than a static state, with increasing attention to methodological innovation in entrepreneurship research. His work demonstrates growing interest in the role of narrative, visual methods, and qualitative approaches to understand complex entrepreneurial phenomena. The research shows consistent focus on family business succession as transformation rather than simple transfer, with increasing attention to adolescent entrepreneurial development and the influence of parenting styles. 2025 — Top 1% of Scholars in all subjects, Stanford/Elsevier's Top 2% Scientist Rankings 2024 — The FamCap25 – The Top FamilyEnterprise Academics, FAMILY CAPITAL MAGAZINE 2022 — Justin G. Longnecker Fellow, United States Association of Small Business and Entrepreneurship 2016 — Dedication to Entrepreneurship Award, Entrepreneurship Division, Academy of Management 2013 — Foundational Paper Award, Entrepreneurship Division, Academy of Management 2005 — International Award for Entrepreneurship and Small Business Research Gartner actively mentors doctoral students and early-career researchers, frequently collaborating on publications addressing complex family business dynamics. His editorial roles as Special Issue Editor for Entrepreneurship and Regional Development and Academy of Management Perspectives demonstrate his influence in shaping research agendas. He has secured significant research funding supporting studies on entrepreneurial legacy, family business succession, and adolescent entrepreneurial development, though specific grant amounts aren't detailed in the available materials. As Director of Research at the Bertarelli Institute for Family Entrepreneurship, Gartner leads initiatives connecting academic research with practical applications for family businesses. His work emphasizes the transformative potential of entrepreneurship within family contexts, challenging traditional notions of family business succession as mere transfer of ownership. Through workshops and seminars, he helps families explore how entrepreneurial legacies can lead to new innovations while preserving core values across generations.
Marta Molinas is a Professor at the Department of Engineering Cybernetics within the Faculty of Information Technology and Electrical Engineering at the Norwegian University of Science and Technology (NTNU). Her research spans multiple interdisciplinary domains with a focus on EEG technology and brain-computer interfaces. She actively supervises numerous Master's projects and maintains extensive international collaborations with institutions including Kavli Institute for Systems Neuroscience, RIKEN Center for Brain Science, University of Tsukuba, Juntendo University, and several European universities. Professor Molinas' research interests center on developing innovative EEG technologies, particularly her FlexEEG concept for reduced-channel EEG systems with brain imaging capabilities. Her work integrates signal processing, artificial intelligence, and neuroscience to create practical applications in mental health, sleep research, neurorehabilitation, and human-computer interaction. She specializes in EEG source imaging, machine learning for brain signal analysis, and the development of brain-computer interfaces for various applications including locked-in syndrome communication, ADHD treatment, and driver monitoring systems. Her publication portfolio demonstrates strong trends in interdisciplinary research combining neuroscience with electrical engineering and artificial intelligence. The work shows particular emphasis on developing practical EEG-based systems that minimize invasiveness while maintaining analytical power, with applications spanning healthcare, rehabilitation, and human augmentation. Her research bridges theoretical signal processing with real-world implementations through numerous student projects and international collaborations. Professor Molinas actively supervises a large team of Master's and PhD students across multiple projects, with each project typically requiring two students working collaboratively. Her research is supported through numerous international collaborations with institutions in Japan, India, and Europe, indicating substantial research funding and project leadership. She has developed a pipeline of student projects that build upon previous work, creating a cumulative knowledge base within her research group. She leads the EEG ITK research team at NTNU, which focuses on developing the FlexEEG headset prototype featuring flexible, wireless, dry electrodes designed to move across the scalp. This team works at the intersection of neuroscience, electrical engineering, and computer science, developing applications for sleep research, mental health monitoring, neurorehabilitation, and brain-computer interfaces. The team collaborates extensively with international partners including the Kavli Institute for Systems Neuroscience, the International Institute of Integrative Sleep Medicine at University of Tsukuba, and several engineering departments across Europe and Asia.
