Wolfgang Spohn is a Senior Professor at the University of Tübingen (since 2019) and Principal Investigator of the Cluster of Excellence 'Machine Learning: New Perspectives for Science' . He previously served as Professor (C4) at the University of Konstanz (1996-2018) and as a Senior Lecturer at the University of Bielefeld (1991-1996). His academic career spans multiple prestigious roles including Academia Europaea member (2015) Frege-Preis awardee (2015) Lakatos Award winner (2012) His research focuses on epistemology , philosophy of science , philosophical logic , ontology , and decision/game theory . He developed ranking theory as a foundational framework for belief dynamics and epistemic reasoning. His work bridges formal epistemology with practical applications in legal theory, economic rationality, and artificial intelligence. Recent publications highlight his contributions to Rationality frameworks for law and science Indexical utility theory and time preferences Ranking-theoretic approaches to conditionals and norms Epistemological foundations of induction Scientific honors include Lakatos Award (2012) Frege-Preis (2015) Heisenberg-Stipendium (1985) He has led major research initiatives such as the DFG Forschergruppe on counterfactuals (2011-2019) and the Reinhart-Koselleck project on reflexive decision theory (2020-present).
Christoph Dellago is a full Professor of Computational Physics at the Faculty of Physics of the University of Vienna, where he has been a faculty member since 2003. He currently serves as Director of the Erwin Schrödinger Institute for Mathematics and Physics, Head of the Computational and Soft Matter Physics Group, and Project lead of EuroCC Austria - National Competence Centre for Supercomputing. Previously, he served as Dean of the Faculty of Physics (2009-2012) and Coordinator of the Doctoral College Advanced Functional Materials (DCAFM). Full Professor, Faculty of Physics, University of Vienna (2003-present) Director, Erwin Schrödinger Institute for Mathematics and Physics (2017-present) Head, Computational Physics and Soft Matter Group (2024-present) Coordinator, Doctoral College Advanced Functional Materials (DCAFM) Austrian Representative, Council of CECAM Dellago received his PhD in Physics from the University of Vienna in 1996, followed by postdoctoral research at UC Berkeley as a Schrödinger Fellow of the Austrian Science Foundation. His research focuses on developing computational methods to study rare events in condensed matter systems, particularly transition path sampling methodology for simulating nucleation, chemical reactions, and biomolecular reorganizations. He has pioneered the application of machine learning to molecular structure recognition and potential energy surfaces. Recent work examines self-assembly of nanocrystals, biopolymer folding, aqueous interfaces, phase separation in alloys, thermo-polarization, cavitation, and freezing phenomena. Analysis of Dellago's recent publications (2023-2025) reveals a strong emphasis on machine learning applications in computational physics, particularly neural network potentials for simulating water interfaces, crystal defects, and phase transitions. His work bridges traditional statistical mechanics with modern computational techniques, creating powerful tools for studying complex dynamical processes that occur on timescales far beyond conventional molecular dynamics simulations. The publications demonstrate increasing integration of machine learning with rare event sampling methods, reflecting the cutting-edge direction of computational statistical mechanics. Förderpreis der Stiftung Futura zur Förderung junger Südtiroler im Ausland (1997) The Raymond and Beverly Sackler Prize in the Physical Sciences (2005) UNIVIE Teaching Award of the University of Vienna (2014) Dellago leads an active research group with multiple PhD students and postdocs, focusing on computational statistical mechanics. His group develops trajectory-based sampling methods and machine learning approaches for molecular simulation. He has secured significant funding through EuroCC Austria and various research platforms including the Research Platform Accelerating Photoreaction Discovery and the Research Platform Erwin Schrödinger International Institute for Mathematics and Physics. His research has been supported by numerous grants enabling advanced computational infrastructure for high-performance simulations. The Dellago Group operates within the Computational and Soft Matter Physics division at the University of Vienna, with strong connections to the Research Network Data Science. The group collaborates extensively with international research institutions and maintains close ties with the Erwin Schrödinger Institute, which Dellago directs. Their research environment combines theoretical physics, computational chemistry, and machine learning expertise to tackle fundamental questions in condensed matter physics and soft matter systems.
Laura Kolbe is a Professor of European History at the University of Helsinki, affiliated with the Department of Philosophy, History and Art Studies within the Faculty of Arts. She is also associated with the Helsinki Institute of Urban and Regional Studies (Urbaria) and the Helsinki Institute of Sustainability Science. As a supervisor for the Doctoral Programme in History and Cultural Heritage, Professor Kolbe plays a significant role in guiding the next generation of historians and cultural scholars. Professor Kolbe's research interests span a wide range of historical and urban studies topics. Her work focuses on European history, particularly Finnish urban history, with special attention to Helsinki's development as a capital city. She has made significant contributions to the understanding of urban diplomacy, municipal cooperation, historical urban development, and the social history of Finnish cities. Her interdisciplinary approach bridges history, urban studies, and cultural heritage, examining how cities evolve through political, social, and cultural transformations. Over her extensive career spanning from 1988 to present, Professor Kolbe has published numerous scholarly works that trace urban development patterns across centuries. Her research reveals consistent themes of internationalization, municipal cooperation, and the evolving relationship between cities and national politics. She has particularly examined how Helsinki has transformed through key historical periods, including the pre-Winter War era, post-war reconstruction, and contemporary urban challenges. Her work often explores the intersections of class, gender, and urban space in shaping Finnish society. Eteläsuomalainen osakunta kunniamerkki (2002) Helsingin yliopiston ylioppilaskunta (2017) Helsingin Yliopiston Ylioppilaskunta kunniamerkki (1997) Kutsuttu Akademiska Sångföreningenin jäseneksi (2013) Kutsuttu Suomen Tiedeseuran jäseneksi (2005) Professor Kolbe actively supervises doctoral students through the Doctoral Programme in History and Cultural Heritage and has led multiple significant research projects. Current projects include 'Tiedeseura - Valta, kunta ja kansalainen' (2024-2025), 'Suurkaupungin kerrostumat - humanistinen kaupunkitutkimus' (since 2015), and 'Grand Hotels at the Fin de Siècle' (since 2012). Her research has been supported by various foundations and has resulted in extensive scholarly output spanning decades. As a key member of the Helsinki Institute of Urban and Regional Studies (Urbaria), Professor Kolbe contributes to interdisciplinary urban research that bridges historical perspectives with contemporary urban challenges. Her work connects with broader European urban scholarship through international collaborations and comparative studies of capital cities.
Mara Ferreri is a Fixed-term Assistant Professor at the Interuniversity Department of Territorial Sciences, Planning and Policies (DIST) at Politecnico di Torino, where she teaches Global Urban Geographies. She is also affiliated with multiple prestigious institutions including the Royal Geographical Society with the Institute of British Geographers (2022-present) and the London School of Economics, Department of Geography and the Environment (2022-present). Her academic career spans multiple European institutions, with previous appointments at Northumbria University (2019-2022), Universitat Autònoma de Barcelona (2016-2019), Durham University, and the London School of Economics. Ferreri's research focuses on housing precarity, temporary and platform urbanism, and struggles for housing alternatives. She employs qualitative methods to investigate the precarization of urban space and living, collective resistance, and self-organization. Her interdisciplinary work bridges urban and cultural geography, spatial planning, visual culture, and housing studies. She is particularly known for her monograph The Permanence of Temporary Urbanism: Normalising Precarity in Austerity London (Amsterdam University Press, 2021), which examines the normalization of precarious living conditions in London. Her recent publications reveal a consistent focus on urban commons, housing movements, platform economies, and the politics of care in urban contexts. Ferreri's work increasingly examines the intersections between digital platforms and housing precarity, feminist approaches to housing commons, and transnational solidarity in housing struggles. Her research demonstrates a methodological commitment to collaborative and militant research approaches that prioritize community knowledge and activism. Queen Mary PhD Studentship (2009) Urban Geography Research Group Event Fund (2012) Antipode Foundation Scholar-Activist Project Award (2012) Arts and Humanities Research Council - Creativeworks London (2014) Marie Curie Fellowship (2016) Antipode International Workshop Award (2019) British Academy Virtual Sandpit Follow-on Funding (2021) Accademia Nazionale dei Lincei and British Academy Knowledge Frontiers Symposium (2022) Ferreri supervises PhD students Matteo Beltramo and Tommaso Cosentino in the Urban and Regional Development program. She leads the ERC-funded EnactDECOM project (2025-2030) on decommodified housing in Southern Europe. As an active member of the European Network for Housing Research (2020-present), she serves on editorial boards for PLATFORMS & SOCIETY (2024-present), HOUSING AND SOCIETY SERIES (2023-present), and RADICAL HOUSING JOURNAL (2019-present), demonstrating her significant contribution to shaping housing research discourse.
Guoqiang Yu is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. He holds a joint appointment at the Virginia Tech Research Center - Arlington. His research focuses on integrating machine learning, signal processing, and statistical methods to develop computational tools for analyzing multiplatform biomedical data. Key areas include neuroinformatics, bioinformatics, and systems biology, with applications in understanding human diseases through genomic, proteomic, and imaging data integration. Education: Ph.D. in Electrical Engineering, Virginia Tech (2011) Postdoctoral Fellowship at Stanford University (2012) M.S. Tsinghua University (2004) B.S. Shandong University (2001) Research Interests: Machine learning methodologies for biomedical data analysis, pattern recognition in complex datasets, optimization algorithms for high-dimensional data, stochastic signal processing, and their applications in neurodegenerative diseases (e.g., ALS, Alzheimer's), glial cell biology, and precision medicine. His work emphasizes developing open-source tools like ABDS, CAM3.0, and SynQuant for data normalization, deconvolution, and quantitative imaging analysis. Awards & Service: NSF Career Award (2018) Dean's Award for Excellence in Research (2022) Member of NIH BRAIN Initiative Consortium (2021–present) Associate Editor for BMC Bioinformatics (2017–present) Labs & Teams: Leads the Yu Lab at Virginia Tech, collaborating with multidisciplinary teams in neuroscience, bioengineering, and computational biology. Active in NIH-funded consortia focused on brain data science and large-scale neuroimaging initiatives.
Prof. Sander M. Bohte holds a part-time appointment as a Professor of Computational Neuroscience at the Swammerdam Institute for Life Sciences (SILS), University of Amsterdam, and is a researcher at the CWI Machine Learning group. His research focuses on computational models of neural information processing, emphasizing spiking neural networks, predictive coding, and reinforcement learning. He bridges computational neuroscience and machine learning, exploring how biological insights can improve neural network designs and vice versa. Key collaborations include work with Cyriel Pennartz (UvA), Pieter Roelfsema (NIN), and Steven Scholte (B&C). His applied research spans scientific machine learning applications in finance and genomics. He actively supervises MSc thesis students, prioritizing those from UvA, with projects ranging from biologically inspired neural architectures to efficient spiking network simulations. Research highlights include developing biologically plausible learning rules for deep networks, predictive coding models for sensory data, and spiking network models for working memory tasks. His work also addresses challenges in temporal dynamics and scalable neural computation, leveraging both theoretical and applied perspectives.
Marion K. Matters-Kammerer is a Full Professor of Electrical Engineering at Eindhoven University of Technology, leading research in terahertz (THz) and millimeter-wave systems. She holds positions in the Center for Wireless Technology, THz Electronics and Integration Lab, and RF Sensing & Communication Lab. Her expertise includes integrated circuits, antenna design, and power amplifier systems. She has led EU projects like 3DmicroTune and ULTRA, and co-authored over 70 journal/conference papers with 13 US patents. Education: MSc in Physics from École Normale Supérieure (Paris) and TU Berlin (1999), PhD in Physics from RWTH Aachen (2007). Past roles include Senior Scientist at Philips Research (1999–2011) and Guest Professor at RWTH Aachen (2009–2010). Research focuses on THz spectroscopy, mm-wave integrated circuits, and energy-efficient wireless systems. Key projects involve THz biosensing, 60 GHz sensor networks, and co-integration of photonics and electronics. Her work addresses UN SDGs like affordable and clean energy, and industry-academia collaboration via NXP Smart Mobility projects. Recent articles highlight advancements in mm-wave power amplifiers, waveguide integration, and radar signal processing. Grants include €2.5M for TeraIBs (2025–2028) and €1.8M for Future Wireless Interfaces (2024–2029). Labs include THz Electronics Lab and RF Sensing Team, advancing sensor and communication technologies.
Hannah Scheithauer is a DPhil (Doctor of Philosophy) student at the University of Oxford, affiliated with Jesus College, The Queen’s College, and currently serving as a College Lecturer in Modern French and Francophone Literature at St. John's College. Her research focuses on transnational forms of memory in contemporary French and German literatures, supported by the Clarendon Fund and Queen’s College Graduate Scholarship. She co-convened the Oxford French Graduate Seminar (2022-2023) and was a guest doctoral researcher at Friedrich-Schlegel-Graduiertenschule, Freie Universität Berlin (2023-2024). Education: B.A. in French and German (2016-2020), M.St. in Comparative Literature and Critical Translation (2020-2021), with additional studies at Georg-August-Universität Göttingen and École Normale Supérieure Paris. Research interests include multidirectional memory, postcolonial and Holocaust narratives, gendered identities in literature, and comparative approaches to French and German texts. Her work bridges cultural studies, literary analysis, and transnational frameworks. Publications and presentations span academic conferences and blogs, addressing topics such as Odile Kennel’s poetics, Anouar Benmalek’s spectral time, and Jérôme Ferrari’s fictionalized ethics. Awards include the 2023 R. Gapper Postgraduate Essay Prize and runner-up for the 2024 Women+ in German Studies Essay Prize. Teaching experience includes courses in French and German literature, with a focus on fostering critical engagement with textual and translational challenges. Grants include the Clarendon Fund and Queen’s College scholarships.
PD Dr. Kaspar Riesen is the Head of the Pattern Recognition Group at the Institute of Computer Science, University of Bern. His research focuses on graph-based methods for pattern recognition, with applications in document analysis, environmental modeling, and healthcare. Key interests include graph matching, neural networks, and spatio-temporal modeling. His work spans structural pattern recognition, graph embeddings, and keyword spotting in historical documents. Recent projects involve river network analysis using graph regression and hypoglycemia prediction via LSTM-GNN hybrid models. Publications emphasize graph theory advancements, such as normalized graph compression and geometric similarity learning. Collaborations include developing specialized algorithms for automated error detection and improving decision-making in simulated sports. Labs/Teams: Pattern Recognition Group (PRG) at the University of Bern.
Dr. Kaidong Yu is a Researcher at the Management School, University of Sheffield, currently serving as a Research Associate on the ESRC-funded project investigating young workers' transitions in the UK labour market. Previously, he was a Module Convenor in the Sociology Department at the University of Manchester (2023-24) and completed his PhD there in 2023, focusing on working-class experiences of education and social mobility across generations. Education: PhD in Sociology, University of Manchester (2023) MA in Contemporary Sociology, University of Leicester BA in Sociology, Central China Normal University Research Focus: Dr. Yu’s work examines youth transitions, class/gender/ethnicity inequalities, social mobility, and life course methods. His recent publications explore how structural changes in educational and labor markets shape inequalities in access to higher education and career trajectories. He currently investigates barriers to labor market progression for younger workers, emphasizing gender, race, ethnicity, and disability disparities. Current Project: His ESRC-funded work analyzes the UK labor market’s ability to facilitate successful transitions for young workers, with a focus on career, earnings, health, and wellbeing outcomes. This project aims to enhance understanding of diversity in labor market experiences through comparative analysis. Affiliations: He is affiliated with the Centre for Decent Work at the Sheffield University Management School and actively contributes to research on decent work and social justice.
Daniele Lorenzini is an Associate Professor of Philosophy at the University of Pennsylvania and a Honorary Associate Professor at the University of Warwick. His work focuses on Post-Kantian European philosophy, social and political philosophy, and the history of philosophy. He holds a PhD from Paris XII University and Sapienza University of Rome, and undergraduate degrees from Scuola Normale Superiore and the University of Pisa. Research interests include Michel Foucault's genealogy, Nietzschean perfectionism, early analytic philosophy, and the philosophy of literature. Lorenzini’s 2023 book, The Force of Truth: Critique, Genealogy, and Truth-Telling in Michel Foucault , explores Foucault’s analysis of truth and its ethical dimensions. He has held postdoctoral roles at Columbia University and Sorbonne University, and was a Humboldt Research Fellow at Freie Universität Berlin (2023-2024). Awarded the Charles Ludwig Distinguished Teaching Award (2024), he also serves as Editor-in-Chief of Foucault Studies and co-editor of the Chicago Foucault Project . Upcoming talks include discussions on Frantz Fanon’s legacy and contemporary philosophical debates.
Dr. Ronald Stauber is an Associate Professor in the Research School of Economics at The Australian National University. His research focuses on game theory, economic theory, and decision-making under ambiguity. He has contributed to understanding Nash equilibria, Bayesian analysis in strategic settings, and correlated equilibrium dynamics. His work frequently explores how ambiguity and irrationality influence strategic interactions in extensive and normal-form games. Key research areas include ambiguity-averse player behavior, robustness of equilibria to higher-order beliefs, and applications of game theory to public insurance systems and dynamic agent models. Stauber's publications span journals like Games and Economic Behavior and Journal of Mathematical Economics , with notable contributions on strategic delegation, belief function products, and computational methods for solving dynamic public insurance games. His research has addressed topics such as Kuhn’s theorem extensions for ambiguity-averse players, trembles in extensive form games, and worker heterogeneity in limited-commitment frameworks. Stauber’s work often combines theoretical rigor with practical insights into economic policy and institutional design.
Eduardo Eyras is a Professor at the Australian National University (ANU) and EMBL Australia Group Leader, leading research in computational RNA biology and cancer genomics. He directs the Centre for Computational Biomedical Sciences and is part of the Shine-Dalgarno Centre for RNA Innovation. His work focuses on transcriptome and epitranscriptome analysis using long-read sequencing, machine learning, and computational methods to study cancer mechanisms. Eyras holds a PhD in Mathematics from the University of Groningen (1999) and previously led research at the Sanger Institute and Pompeu Fabra University. Affiliations: Director, Centre for Computational Biomedical Sciences Researcher, Shine-Dalgarno Centre for RNA Innovation Member, Division of Genome Sciences and Cancer Leader, The Eyras Group - Computational RNA Biology Research Interests: Development of algorithms for long-read sequencing Machine learning applications in RNA biology Epitranscriptomic modifications and cancer Therapeutic mRNA platform steering Key Projects: Novel algorithms for transcriptome variation analysis Predictive models of RNA modifications in disease Ribosomal DNA variation analysis Advisees & Grants: Supervises PhD students (e.g., Favour Oyelami, Stefan Prodic) and leads ARC-funded projects on mRNA diagnostics and epitranscriptomic therapies. Collaborates with global teams on forensic genomics, cancer drug resistance, and AI-driven translational research. Labs/Teams: Leads the Eyras Group, collaborating with the Hannan Group (Cancer Therapeutics) and Shirokikh Group (Protein Biosynthesis).
Martin Fischer is a Professor at Ludwig Maximilian University of Munich (LMU), affiliated with the Faculty of Philosophy, Science Theory, and Religious Studies, and the Munich Center for Mathematical Philosophy. He holds the academic rank of Professor and has been a Privatdozent (PD) since 2019, leading a DFG-funded project on "Logics: From tolerance to pluralism." Prior roles include a visiting fellowship at MCMP, research at K.U. Leuven, and a stint at the Scuola Normale Superiore in Pisa. Educational Background: Fischer earned his Master's degree in 2003 and his Ph.D. in 2007 from LMU Munich. His studies included a DAAD-supported term at the University of Oxford in 2006. He has held research positions in Belgium, Germany, and Italy, contributing to projects like "Syntactical Treatments of Interacting Modalities" funded by the DFG. Research Interests: His work focuses on logic (axiomatic theories of truth, modal logics, interpretability), epistemology (realism/antirealism debate, Fitch paradox), and philosophy of language (Davidson, Quine, deflationism). He explores formal systems, non-classical logics, and the philosophical implications of truth theories. Publications: His recent works address sequent calculi for HYPE logic, nonclassical truth theories, and paradoxes. Key contributions include articles in Studia Logica , Review of Symbolic Logic , and Nous , advancing topics like truth's expressive power, iterated reflection principles, and the interplay between deflationism and instrumentalism. Grants & Projects: Fischer leads a DFG-funded project exploring logics' pluralism and has previously contributed to syntactical treatments of modalities research. His academic trajectory reflects a commitment to formal methods in philosophy. Labs & Affiliations: Affiliated with the Munich Center for Mathematical Philosophy, he collaborates on interdisciplinary projects bridging logic and epistemology.
Dr. Mao Lin is an Associate Professor of History at Georgia Southern University since 2014, affiliated with the Department of History in the College of Arts and Humanities. His research and teaching focus on American Foreign Relations, the U.S. Presidency, U.S.-China Relations, and Modern China. He holds degrees from Peking University (B.A. 1999, M.A. 2002) and the University of Georgia (M.A. 2004, Ph.D. 2010). Research interests include Cold War diplomacy, Sino-American rapprochement, and modernization narratives. His current book project examines U.S.-China relations and modernization diplomacy from 1966-1979. He directs the Study Abroad in China program, emphasizing experiential learning. Publications span journals like Journal of Cold War Studies and Chinese Historical Review , analyzing trade diplomacy, soft power, and cultural exchanges. His work bridges economic, political, and cultural dimensions of international relations. Teaching responsibilities include upper-division courses on U.S. Foreign Relations, Cold War history, and world history. Office: #3098 Interdisciplinary Academic Building, with contact via mlin@georgiasouthern.edu or 912-478-0243.
