جست‌وجوی استاد و پژوهشگر

Laura Kovacsمشاهده پروفایل

استاد

• Automated Reasoning
• Program Analysis
• Symbolic Summation
• +۵ مورد دیگر

Laura Kovacs is a full Professor at TU Wien's Faculty of Informatics, where she serves as head of the FORSYTE research unit focused on Automated Program Reasoning. She also holds a part-time associate professorship at Chalmers University of Technology in Sweden. As a leading researcher in automated reasoning, she was recently elected President and Chair of the ETAPS steering committee (2025) and has received prestigious awards including ERC Consolidator and Starting Grants. TU Wien, Faculty of Informatics (2016-present) Chalmers University of Technology, Sweden (part-time) Postdoctoral researcher at EPFL and ETH Zurich (2007-2010) FWF Hertha Firnberg Research Fellow (2010-2013) Her research spans automated theorem proving, program analysis, symbolic summation, and computer algebra, with a particular focus on developing theoretical foundations and practical tools for software verification. She is best known as co-developer of the Vampire theorem prover, which recently made history by winning all eight divisions at the CASC competition in 2025. Her recent publications demonstrate strong activity in first-order reasoning, quantifier handling, and security applications, with notable work including the Amazon-funded FOREST project (2020) and QuAT (2023). The 2025 CAV conference awarded her co-authored paper 'The Vampire Diary' a Distinguished Paper Award, highlighting continued leadership in the field. ERC Consolidator Grant 2020 for 'ARTIST: Automated Reasoning with Theories and Induction for Software Technology' Wallenberg Academy Fellowship (2014) ERC Starting Grant (2014) Amazon Research Awards (2020, 2023) Distinguished Paper Award at CAV 2025 Professor Kovacs actively supervises PhD students working on cutting-edge topics in automated reasoning, with recent successful defenses including Márton Hajdu's 'Redundancy, Rewriting, and Induction' (2025) and Sophie Rain's 'Automated Security Analysis of Blockchain Protocols' (2025). She leads the newly established Doctoral College on Automated Reasoning at TU Wien, which received FWF funding for 13 doctoral positions focusing on security and AI applications. As head of FORSYTE, she oversees research in automated program reasoning, working closely with colleagues on projects spanning software model checking, static analysis, and formal methods for distributed systems. Her group has established strong industry connections, particularly with Amazon through the Amazon Research Awards program.

Piotr Gmytrasiewiczمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Multiagent Systems
• Decision Theory
• +۷ مورد دیگر

Piotr Gmytrasiewicz is an Associate Professor at the Department of Computer Science, University of Illinois at Chicago (UIC). He leads the Multiagent Systems Group within the Artificial Intelligence Laboratory at UIC. His research focuses on rationality in artificial agents , particularly in environments with multiple interacting agents. Key areas include Interactive Decision-Making Bayesian Modeling for Agent Communication Recursive Belief Frameworks Time Pressure and Computational Trade-offs Evolution of Agent Communication Languages Dynamic Resource Allocation His recent work examines the rationality of insincere communication and methods to discount potentially insincere information. Past projects include modeling emotions in agent design and developing decision-theoretic approaches to game theory. He has secured funding from prestigious institutions such as the National Science Foundation (NSF) , Office of Naval Research (ONR) , and DARPA . Current and past projects emphasize Automated Linguistic Competence Evolution Emergent Communication Protocols Scalable Multiagent Learning Strategic Coordination under Uncertainty He earned his Ph.D. from the University of Michigan, Ann Arbor (1992) and has previously collaborated with the Department of Computer Science and Engineering (CSE) at the University of Texas at Arlington on DARPA-funded research.

Sourav Medyaمشاهده پروفایل

استادیار

• Machine Learning
• Graph Mining
• Data Science
• +۳ مورد دیگر

Sourav Medya is an Assistant Professor in the Department of Computer Science at the University of Illinois at Chicago (UIC). Prior to joining UIC, he was a research assistant professor at the Kellogg School of Management and the Northwestern Institute on Complex Systems (NICO) at Northwestern University. He earned his Ph.D. in Computer Science from the University of California, Santa Barbara (2019) and a Master of Engineering in Computer Science and Automation from the Indian Institute of Science, Bangalore, India. Ph.D., University of California, Santa Barbara, 2019 M.Eng., Indian Institute of Science, Bangalore, India His research lies at the intersection of graphs, machine learning, and data science, with a focus on bias, fairness, and interpretability in AI. He also develops machine learning techniques with applications in healthcare, infrastructure, and computational social science. His recent publications address topics such as global counterfactual explainers for GNNs, game-theoretic node selection, and interpretable logical rule extraction from graph models. Medya has advised students in areas like multimodal learning, graph neural networks, explainable AI, and efficient AI. His scientific awards include the UIC Outstanding MS Thesis Award (2024) and Best Paper Award at the Machine Learning on Graphs (MLoG) Workshop at WSDM'23. He has reviewed for top conferences including NeurIPS, ICML, KDD, and AAAI, and recently taught courses on Machine Learning on Graphs (CS 519) and Introduction to Data Science (CS 418) at UIC.

• Economics of Scholarly Communication
• Open Access Publishing
• Academic Journal Pricing
• +۳ مورد دیگر

Mark McCabe is a Full Professor at SKEMA Business School, holding a dual affiliation with the Research Group in Law, Economics, and Management (GREDEG)—a joint unit of Université Côte d'Azur, CNRS, and SKEMA. As a teacher-researcher in the Pole Growth, Industry, and Markets (PCIM), he contributes to the BUDYMAC research team (Business Dynamism and Macroeconomic Challenges) with primary focus on Innovation studies. His academic leadership spans theoretical and empirical investigations into scholarly communication systems. His research program critically examines the economic foundations of academic publishing, specializing in open access dynamics, citation behavior, and market competition. Key contributions include: Econometric analysis of open access effects on citation counts across journal quality tiers Structural modeling of two-sided markets in scholarly journal pricing Empirical assessment of data disclosure policies using natural experiments Welfare analysis of publisher mergers and bundling strategies Development of sustainable funding models for gold open access Analysis of his 15 most recent publications (2006-2024) reveals consistent focus on open science economics, with methodological emphasis on natural experiments, panel data analysis, and industrial organization frameworks. His work bridges theoretical economic modeling with real-world policy implications for libraries, publishers, and research institutions. Within SKEMA's research ecosystem, Professor McCabe actively shapes discourse through the PCIM pole and BUDYMAC team, where he investigates macroeconomic dimensions of business innovation and market evolution.

Bhaswar B. Bhattacharyaمشاهده پروفایل

دانشیار

• nonparametric statistics
• distribution-free inference
• networks analysis
• +۴ مورد دیگر

Bhaswar B. Bhattacharya is an Associate Professor of Statistics and Data Science at The Wharton School of the University of Pennsylvania, with a secondary appointment in the Department of Mathematics. His research spans several interconnected areas at the intersection of statistics, probability, and computational geometry. Dr. Bhattacharya received his Ph.D. in Statistics from Stanford University in 2016 under the supervision of Persi Diaconis. Prior to that, he earned both his Bachelor of Statistics (2009) and Master of Statistics (2011) from the Indian Statistical Institute in Kolkata. His research interests focus on three main pillars: nonparametric statistics (including distribution-free inference, nearest-neighbor methods, and inference on networks), combinatorial probability (covering counting problems in random graphs, random colorings, and graph limit theories), and discrete and computational geometry (including facility location problems, Voronoi games, and geometric Ramsey problems). His work often bridges theoretical developments with practical applications in network analysis, statistical learning, and geometric optimization. Recent publications demonstrate a strong trajectory in developing distribution-free methods for network analysis, with significant contributions to understanding fluctuations in graphon-based random graphs and developing optimal tests for inhomogeneous random graph models. His work also shows increasing focus on higher-order network structures through hypergraph models and applications to real-world problems like vaccination site optimization. NSF Career Award (2021-2026) Alfred P. Sloan Research Fellowship (2021) Probability Dissertation Award, Stanford University (2016) Sabyasachi Roy Memorial Gold Medal for best master's thesis, Indian Statistical Institute (2009-2011) Dr. Bhattacharya teaches advanced courses in mathematical statistics at both undergraduate and graduate levels at Wharton. His research program involves collaborations across multiple institutions and disciplines, with recent work applying statistical methods to public health challenges such as optimizing vaccination site locations. He maintains active research collaborations with colleagues in statistics, computer science, and applied mathematics departments.

Dennis Kundischمشاهده پروفایل

استاد

• Digital Markets
• Platform Economy
• Business Model Innovation
• +۴ مورد دیگر

Prof. Dr. Dennis Kundisch is Chair of Digital Markets at the Faculty of Economics (Department 3: Business Information Systems) , University of Paderborn. His research explores behavior of human and machine actors in digital markets through economic lenses, focusing on platform economy, business model innovation, and interdisciplinary methods like online experiments. Research Pillars: Platform governance, gamification, observational data analysis, business model taxonomies, and digital transformation in cultural/industrial sectors Recent publications analyze Cultural Data Ecosystems , Platform Launch Strategies , and Asymmetric Review Dynamics , showcasing his team's engagement with both theoretical frameworks and practical case studies. Collaborations include the Software Innovation Campus Paderborn (SICP) and industry partnerships. Awards: Best Paper Award Nominee (HICSS), Dean's Young Scholar (University of Paderborn), Best Reviewer Award (ICIS)

François Pottierمشاهده پروفایل

پژوهشگر

• programming languages
• functional programming
• type systems
• +۵ مورد دیگر

François Pottier is a senior researcher at Inria in Paris, France, where he leads the Cambium research team. He is affiliated with the Gallium research group and has maintained an active research profile spanning several decades in programming languages and formal methods. His research focuses on programming languages , particularly functional programming and OCaml, type systems design and implementation, program verification using separation logic, and compiler construction . His work bridges theoretical foundations with practical implementation, evidenced by numerous open-source software tools he has developed. Pottier's publication record shows consistent contributions to top programming languages conferences (POPL, ICFP, ESOP) with recent work emphasizing separation logic frameworks, resource analysis, and formal verification of OCaml systems. His research demonstrates a clear trajectory from foundational type theory toward practical verification techniques for real-world programming languages. He has advised numerous PhD students including Remy Seassau, Tiago Soares, Clément Allain, and Alexandre Moine, among others, many of whom have gone on to research positions at institutions like New York University, Imperial College London, and Inria itself. Pottier maintains active service roles in the programming languages community as a member of IFIP Working Group 2.8 on Functional Programming and IFIP Working Group 2.16 on Language Design, and serves on program committees for major conferences including upcoming roles for JFLA 2026 and ITP 2026. He leads the Cambium research team at Inria, which focuses on programming language theory and implementation, particularly around OCaml and formal verification. The team develops both theoretical frameworks and practical tools that have influenced the broader programming languages ecosystem.

Rupert Gehrleinمشاهده پروفایل

پژوهشگر

• Computer Science Education
• Didactics of Computer Science
• Computer Science Unplugged
• +۳ مورد دیگر

Rupert Gehrlein is a Researcher at Goethe University Frankfurt's Faculty of Computer Science and Mathematics, working within the IDMI institute as part of the Computer Science Didactics Secondary Schools team. His role focuses on developing and researching innovative teaching methodologies for computer science education in secondary schools, particularly through the "Computer Science Unplugged" project which implements computational thinking concepts without digital devices. Education: General higher education entrance qualification, Leibnizschule, Offenbach am Main (2010) Completed training as biology laboratory technician, Sanofi Deutschland GmbH, Frankfurt am Main (2013) First state examination for teaching qualification in computer science and biology, Goethe University Frankfurt (2022) Research Focus: Gehrlein specializes in accessible computer science pedagogy, emphasizing unplugged methods to demystify complex concepts like blockchain and NFTs through physical tools and games. His work bridges theoretical computer science with classroom-ready implementations, targeting secondary education curricula while addressing ecological and economic dimensions of emerging technologies. Publication Trends: His 2022-2023 publications reveal a concentrated effort in adapting cutting-edge AI tools like ChatGPT for educational diagnostics, creating tangible learning aids for abstract concepts (e.g., NFT board games), and redesigning teacher training environments. These works collectively advance the field toward experiential, device-independent computer science instruction. Scientific Awards: No awards documented in available sources. Teaching & Advising: Gehrlein conducts seminars including "Computer Science Unplugged," "Didactics of the Digital World," and project-based coursework across multiple semesters (2022-2025). While actively shaping future educators' pedagogical approaches, no graduate student advisement or grant management is indicated in current records. Team Integration: As core member of the Computer Science Didactics Secondary Schools unit under Prof. Dr. Andreas Dengel, he collaborates with Linda Rustemeier, Daniel Unro, Jonas Maurer, and Sebastian Görlich to develop localized teaching resources and implement research findings in Frankfurt-area schools.

• Semiotics
• Cinema Studies
• Media Studies
• +۵ مورد دیگر

Nicola Maria Dusi is an Associate Professor in the Department of Communication and Economics at the University of Modena and Reggio Emilia (UNIMORE). She specializes in semiotics of cinema and media, with a focus on contemporary television series, intermediality, and transmedia storytelling. Her academic work bridges theoretical frameworks with practical analysis of audiovisual media products. Dr. Dusi's research interests encompass multiple dimensions of media studies. She investigates how contemporary television series construct narrative meaning through complex storytelling techniques, with particular attention to the interplay between fiction and documentary elements. Her work on intermediality explores how different media forms interact and transform content across platforms. She has conducted extensive research on the representation of historical events in television miniseries, notably analyzing the Chernobyl TV series as a case study of cultural memory construction. Her scholarly contributions also include studies on biopics, autism representation in media, and the semiotics of cinema archives. She approaches these topics through socio-semiotic frameworks that examine both textual structures and audience reception. Her recent publications reveal a consistent focus on contemporary media phenomena, particularly the evolution of television seriality in the streaming era. She examines how modern TV series negotiate between factual and fictional elements, creating complex narrative ecosystems that extend beyond the screen through paratexts and fan engagement. Her work on Chernobyl demonstrates how a TV miniseries functions as both historical representation and cultural commentary, blending documentary approaches with dramatic storytelling. She also explores more technical aspects of media representation, such as the aesthetics of blurred vision and data moshing in digital media, analyzing how these techniques affect meaning construction and viewer experience. Dr. Dusi is actively involved in teaching courses directly related to her research expertise. She teaches 'Semiotics of Cinema and Media' for Communication Sciences students, covering theoretical frameworks and analytical methods for examining audiovisual texts. Her course includes modules on basic semiotic theories, analysis of cinema and media, and specialized topics in contemporary media studies. She also teaches 'Intermediate Languages' for the Master's Degree in Advertising, Digital Communication, and Business Creativity. Her teaching emphasizes both theoretical knowledge and practical application, incorporating current media examples to illustrate concepts and encouraging students to develop critical analytical skills for understanding complex media phenomena.

• Science Education
• Didactics of Experimental Sciences
• Educational Neuroscience
• +۳ مورد دیگر

Maria Angeles de las Heras Perez serves as a University Professor in the Department of Integrated Didactics at the Faculty of Education, Psychology and Sports Sciences, University of Huelva. She maintains dual affiliations with the Research Center on Contemporary Thought and Innovation for Social Development and the RNM358 MARSHES AND BEACHES research group, focusing on environmental education contexts. Her academic foundation stems from a 2007 PhD at the University of Huelva, where her dissertation Study of flora and vegetation of the western Doñana area was supervised by Dr. Jesús Muñoz Álvarez and Dr. Pablo José Hidalgo Fernández. This ecological background informs her current interdisciplinary approach to science education. Her research program centers on the cognitive-emotional dynamics of science teaching, investigating how stress, cognitive load, and emotional recognition impact teachers' professional knowledge. She pioneers applications of educational neuroscience in teacher training, developing interventions that integrate EEG monitoring with didactic strategies. Her work extends to sustainable chemistry education, AI literacy in science curricula, and computational thinking through inquiry-based learning frameworks. Recent publications demonstrate consistent methodological innovation through bibliometric analyses, emotional climate observation tools, and technology-enhanced pedagogical models. Analysis of her 2023-2025 publications reveals three dominant trajectories: (1) measurement of emotional-cognitive interactions in science teachers using neuroscientific methods, (2) development of context-based didactic tools for environmental and chemistry education, and (3) integration of computational thinking through Micro:bit and game-based learning. Her research consistently bridges theoretical neuroscience with practical classroom applications, particularly in experimental sciences education. She actively contributes to educational innovation through the RNM358 research group, which leverages the Doñana natural ecosystem as a living laboratory for developing place-based science curricula. Her work on emotional climate observation tools (OCE) provides educators with practical frameworks for improving classroom dynamics in both university and secondary settings.

Richard E. Wendellمشاهده پروفایل

استاد

• Management Science
• Decision Analytics
• Data Envelopment Analysis (DEA)
• +۵ مورد دیگر

Richard E. Wendell is a Professor of Business Administration at the Joseph M. Katz Graduate School of Business, University of Pittsburgh. His academic focus spans Management Science , Decision Analytics , and Data Envelopment Analysis (DEA) , with expertise in Sensitivity Analysis , Facility Location , and Project Management . He has held faculty positions at Ohio State University, Carnegie-Mellon University, and Rensselaer Polytechnic Institute, alongside research fellowships at institutions like the Center for Operations Research and Econometrics in Belgium and Argonne National Laboratory. Education : PhD in Operations Research (Northwestern University, 1971), MS in Industrial Engineering (University of Pittsburgh, 1966), BS in Industrial Engineering (University of Pittsburgh, 1965) His research, supported by National Science Foundation grants, includes over 60 papers in journals such as Management Science , Operations Research , and Mathematical Programming . Key publication trends include DEA methodology , linear programming sensitivity , and global optimization techniques . Scientific Awards : Distinguished Professor award (Executive MBA), University of Pittsburgh Faculty Honor Roll, multiple Katz Excellence-in-Teaching awards Wendell has advised numerous academic and industry projects, with consulting engagements at companies like Johnson Matthey Inc., Promistar Financial Corporation, and Duquesne Light. His work bridges theoretical advancements in operations research with practical applications in business analytics and risk management. Outside academia, he enjoys traveling, making wine, working out, and dancing.

Paul Peter Hagerمشاهده پروفایل

استادیار

• Mathematical Finance
• Machine Learning
• Stochastic Control
• +۴ مورد دیگر

Paul Peter Hager serves as an Assistant Professor in the Department of Statistics and Operations Research at the University of Vienna, where he teaches courses including Linear Algebra and Applied Optimization. Previously, he held a junior research group leader position at Technische Universität Berlin. His research centers on: Mathematical Finance Machine Learning Stochastic Control Mean-Field Games Fractional Processes Gaussian Multiplicative Chaos Volatility Modeling Hager pioneers applications of rough path signatures in financial mathematics, developing novel frameworks for stochastic control and calibration problems. His work bridges theoretical probability with practical machine learning implementations, particularly in volatility modeling using fractional processes and log-correlated fields. Recent publications reveal a dominant trend in signature-based methods for optimal stopping and mean-field games, with significant contributions to fractional Brownian motion theory. His collaborative work with leading researchers like Peter Friz and Christian Bayer consistently targets high-impact journals in applied probability and financial mathematics. Dr. Hager maintains active research collaborations and has delivered invited talks at institutions including KAUST, focusing on computational implementations of signature methods in finance.

• Optimization under uncertainty
• Robust optimization
• Scenario generation
• +۸ مورد دیگر

Christina Busing is a Full Professor for Combinatorial Optimization at RWTH Aachen University, a position she has held since 2021. Previously, from 2016 to 2021, she served as a Junior Professor for Robust Planning in Medical Care at the same institution. She leads the Teaching and Research Group on Combinatorial Optimization, contributing significantly to the academic community through her research and teaching activities. Her educational background includes Mathematics studies at WWU Münster, Universidad Comlutense de Madrid, and the Technical University of Berlin. Her doctoral work was completed under the supervision of Prof. Möhring, focusing on Recoverable Robustness in Combinatorial Optimization. She has also held postdoctoral positions at institutions in Aachen, Lancaster, and Vienna. Professor Busing's research spans multiple areas of optimization theory and application. Her work focuses on optimization under uncertainty, robust optimization, scenario generation, combinatorial optimization, complexity theory, optimality criteria, and both exact and heuristic algorithms. She has made significant contributions to applying these theoretical frameworks to practical problems in healthcare, energy systems, and transportation networks. Her interdisciplinary approach bridges theoretical computer science with real-world operational challenges. Her extensive publication record demonstrates a consistent focus on robust combinatorial optimization, with recent work emphasizing applications in healthcare systems, particularly in patient-to-room assignment, primary care scheduling, and pharmacy services. She has developed novel methodologies for handling uncertainty in optimization problems, including recycling valid inequalities and designing consistent decision frameworks for two-stage optimization problems. RWTH Aachen Brigitte Gilles Award for contributions to the advancement of women in science (2022) RWTH Aachen FAMOS Award for excellent family-friendly leadership (2019) RWTH Aachen university-wide Best Teaching Award (2018) TU Berlin Best Diploma Excellence Award in Mathematics (2008) German National Scholarship (Cusanuswerk) (2003-2007) Professor Busing serves on multiple program committees including EURO (2019), INOC (2018), and ESA (2017). She is also involved with the UnRAVeL Graduate College since 2018. Her teaching portfolio includes courses on Graph and Network Optimization, Mathematical Heuristics for Discrete Optimization Problems, and Combinatorial Optimization. She has developed problem-based learning approaches for heuristic methods in decision problems across mathematics, computer science, and industrial engineering. Her research group actively collaborates on interdisciplinary projects addressing operational issues in healthcare, energy systems, and transportation networks, developing mathematically optimized solutions for complex real-world challenges.

Franck Iutzelerمشاهده پروفایل

استاد

• Numerical optimization
• Statistical learning
• Stochastic programming
• +۵ مورد دیگر

Franck Iutzeler is a Professor of Applied Mathematics at Université de Toulouse, working within the Statistics & Optimization team of the Institut Mathématique de Toulouse and teaching in the Department of Mathematics. He previously served as an Assistant Professor at Université Grenoble Alpes from 2015 to 2023 and completed his Habilitation à Diriger des Recherches in 2021. His research focuses on the intersection of optimization, statistics, and optimal transport theory to develop robust data-driven models. Key areas include numerical optimization, statistical learning, stochastic programming, and optimal transport. He is particularly interested in distributionally robust optimization using Wasserstein metrics and has developed the skwdro Python library for implementing these methods. Iutzeler's recent publications demonstrate a strong focus on Wasserstein Distributionally Robust Optimization (WDRO), with multiple papers in top venues like NeurIPS and SIAM Journal on Optimization. His work bridges theoretical guarantees with practical implementation, particularly through the skwdro library which provides efficient code for WDRO in machine learning applications. ANR JCJC grant for project STROLL: Harnessing Structure in Optimization for Large-scale Learning Co-PI of ANITI chair on Trust and Responsibility in Artificial Intelligence led by JM. Loubes and J. Bolte Iutzeler actively supervises PhD students including Yu-Guan Hsieh (awarded Université Grenoble Alpes's PhD award), Gilles Bareilles, Waïss Azizian, and Victor Mercklé. He has secured research funding through the ANR (MAD project on Automatic Differentiation) and ANITI. His current research includes statistical fairness using optimal transport theory and automatic differentiation for stochastic optimization. He leads the development of the skwdro library for Wasserstein Distributionally Robust Optimization and is involved with ANITI (Toulouse's AI Cluster), where he also took responsibility for the 2nd year of the Master SID in Data Science & Engineering in September 2024.

Björn Fritzمشاهده پروفایل

مدرس

• Art History
• Visual Studies
• Digital Art
• +۷ مورد دیگر

Björn Fritz is a Lecturer in the Division of Art History and Visual Studies within the Department of Arts and Cultural Sciences at Lund University's Faculty of Humanities and Theology. He teaches across various courses focusing on art, architecture, and design from the 19th and 20th centuries, as well as theoretical aspects of art history. His research interests span two primary areas: art & technology (particularly computer-mediated visual environments and art), and body, sexuality & representations (with a focus on the male gay body in western culture). These interests extend to related fields including digital worlds, game environments, spatial design, aesthetics, and embodied experience. His work often engages with visual phenomena beyond traditional art historical domains. Dr. Fritz completed his doctoral thesis titled "Experiencing Gameworlds: Understanding Zelda and Mario Through the Lenses of Art History and Phenomenology" in 2025, which examines how video games like The Legend of Zelda: Breath of the Wild and Super Mario Odyssey can be understood through art historical and phenomenological perspectives. His publications also cover topics such as landscape representation, art and politics since 1950, and art education methods. Active researcher in the research node for aesthetic studies since 2018 Regular participant in the Higher Seminar in Art History and Visual Studies at Lund University Dr. Fritz is actively engaged in teaching courses including KOVA14 (Art History of the Western World) and KULB10 (Mediate and Write about Culture), where he brings his expertise in modern and contemporary art, architecture, and visual culture.