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Emanuele MacrìView profile

Professor

• Algebraic Geometry
• Derived Categories
• Moduli Spaces
• +3 more

Emanuele Macrì is a Professor at the Laboratoire de mathématiques d'Orsay, Université Paris-Saclay, specializing in algebraic geometry with a focus on derived categories, stability conditions, and moduli spaces. He holds editorial roles at Mathematische Zeitschrift, International Mathematics Research Notices, and Selecta Mathematica. His research explores hyperkähler manifolds, Fano varieties, and wall-crossing phenomena, contributing to foundational advancements in geometric stability theory. Education & Positions Current roles include: Professor, Université Paris-Saclay (since 2024) Member of the Orsay Mathematics Laboratory (LMO) Research Interests Key areas of study encompass: Derived categories of coherent sheaves and their stability conditions Moduli spaces of sheaves on K3 surfaces and hyperkähler varieties Applications of wall-crossing techniques to classical algebraic geometry problems Geometry of Fano varieties and hyperkähler manifolds Publications & Trends Recent work emphasizes: Advances in understanding hyperkähler manifolds via stability conditions (e.g., Mukai models of Fano varieties ) Classification of hyperkähler fourfolds using Riemann-Roch polynomials Investigations into antisymplectic involutions and their geometric implications Development of stability frameworks for Kuznetsov components in derived categories Awards & Recognition Plenary speaker at the 2025 Summer Research Institute in Algebraic Geometry Member of the Accademia dei Lincei (2024) Medaglia dei XL per la matematica (2023) Invited speaker at the International Congress of Mathematicians 2022 Advising & Grants Macrì has advised numerous PhD students and postdocs, including: Current students: Matteo Verni, Vanja Zuliani Notable past students: Luigi Martinelli, Benjamin Schmidt He leads the ERC Synergy Grant HyperK (2020–2026), exploring hyperkähler manifolds and related geometries. Labs & Collaborations Active in organizing workshops and seminars, including: HyperK workshop series (2020–2025) Reading seminars on hyperkähler geometry and moduli spaces Working groups on P=W conjecture and D-modules

• Distributed Systems
• Cryptography
• Electronic Voting
• +3 more

Michael J. Fischer is a Professor of Computer Science at Yale University, renowned for foundational contributions to distributed systems theory, cryptography, and parallel algorithms. His work includes the seminal impossibility result for distributed consensus with faulty processes and the development of the parallel prefix algorithm fundamental to modern parallel computing. His educational background: B.S. in Mathematics, University of Michigan (1963) M.A. in Applied Mathematics, Harvard University (1965) Ph.D. in Applied Mathematics, Harvard University (1968) Fischer's research spans theoretical and applied computer science with emphasis on distributed systems (consensus protocols, fault tolerance), cryptography (information-theoretic security, card-based protocols), and electronic voting systems . His work bridges abstract theory with practical security applications, particularly in trust modeling for e-commerce. Current investigations focus on algorithmic approaches to establishing trust relationships in distributed environments. His publication trajectory reveals evolving expertise from early parallel algorithms (1970-80s) to distributed consensus breakthroughs (mid-1980s), then cryptographic protocols and secure e-voting systems (1985-2000s), with recent work synthesizing these domains through trust frameworks. Key thematic threads include fault tolerance in unreliable networks and verifiable security mechanisms. Scientific recognition: ACM Fellow Fischer has held significant leadership roles including Editor-in-Chief of the Journal of the ACM , chair of the Max-Planck-Institute for Computer Science International Scientific Advisory Board, and founding member of the Computing Research Association's subcommittee on Women in Computer Science. His advisory work extends to the National Science Foundation and Wuhan University's State Key Laboratory on Software Engineering. Outside academia, he actively participates in the Yale Figure Skating Club, having served multiple terms as president. He maintains international collaborations as Guest Professor at Wuhan University and through editorial roles including Acta Informatica , while continuing to teach core computer science courses from data structures to cryptography at Yale.

David BourgetView profile

Associate Professor

• Philosophy of Mind
• Philosophy of Language
• Metaphilosophy
• +3 more

David Bourget is an Associate Professor in the Department of Philosophy at Western University and serves as the Director of the Centre for Digital Philosophy . He holds a PhD from the Australian National University (2010) and a BSc in Computer Science from L'Université Laval (2002). His research focuses on consciousness, intentionality, and digital philosophy , with a special emphasis on the intersection of AI and philosophical inquiry through projects like PhilPapers.org. Education: PhD, Australian National University (2010) BSc, L'Université Laval (2002) Key Research Areas: Philosophy of Mind Philosophy of Language Digital Philosophy Infrastructure Metaphilosophy His recent publications explore topics such as phenomenal intentionality, representationalism, and debunking theories . The Centre for Digital Philosophy , which he leads, maintains major resources like PhilPapers, PhilPeople, and PhilEvents, supported by CFI and ORF grants . He actively collaborates with philosophers like Angela Mendelovici on intentionality and representational theories.

Fabrizio RiguzziView profile

Professor

• Logic Programming
• Statistical Relational Artificial Intelligence
• Probabilistic Logic Programming
• +3 more

Fabrizio Riguzzi is a Full Professor at the Department of Mathematics and Computer Science of the University of Ferrara, Italy. His academic career spans over two decades at the same institution, having served as Associate Professor (2014-2020) and Assistant Professor/Ricercatore (1999-2014). He is an active researcher in the fields of Logic Programming and Statistical Relational Artificial Intelligence with numerous publications and leadership roles in international conferences. His educational background includes: PhD in Electronic and Computer Engineering from the University of Bologna (1999) Laurea in Computer Engineering from the University of Bologna (1995) Riguzzi's research focuses on probabilistic approaches to artificial intelligence, particularly probabilistic logic programming and statistical relational AI. His work bridges symbolic reasoning with probabilistic methods, developing frameworks for uncertain knowledge representation and reasoning. He has made significant contributions to probabilistic answer set programming, neuro-symbolic integration, and applications in areas like network intrusion detection and knowledge graph completion. His research demonstrates how logical formalisms can be enhanced with probabilistic reasoning to tackle real-world problems with uncertainty. An analysis of his recent publications reveals a strong trend toward integrating neural and symbolic approaches in AI, with significant work on probabilistic answer set programming frameworks. His research spans theoretical foundations of probabilistic logic programming, practical implementations, and applications in cybersecurity, knowledge graphs, and decision-making under uncertainty. The interdisciplinary nature of his work connects computer science theory with practical AI applications. His notable awards include: Alain Colmerauer 10-Year Test-of-Time Award at ICLP 2021 Best Paper Award for "BUNDLE: A Reasoner for Probabilistic Ontologies" at RR-2013 Highly Commended Paper Award for "Probabilistic declarative process mining" at KSEM 2010 Riguzzi has supervised several PhD students to completion, including Elena Bellodi, Riccardo Zese, and Giuseppe Cota, who have gone on to win prestigious awards for their theses. He has served in numerous editorial roles, including Associate Editor of the Journal of Artificial Intelligence Research and Editor in Chief of Intelligenza Artificiale. His leadership extends to organizing major conferences like ILP 2018 and serving on program committees for top AI venues including IJCAI, AAAI, and ECAI. He is a member of the ML@unife research group and has developed several online systems including cplint, TRILL, and an Online AUC calculator. His work has fostered collaborations across the AI research community, particularly in the areas of probabilistic logic programming and neuro-symbolic AI.

• Healthcare Education
• Vocational Pedagogy
• Learning Effectiveness
• +3 more

Prof. Dr. Bettina Glunde is a faculty member at the Frankfurt University of Applied Sciences , Department 4: Social Work & Health. She specializes in healthcare education, vocational pedagogy, and aging-related care innovations. Her work emphasizes interdisciplinary collaboration, qualitative research, and technology integration in nursing education. Current research focuses on interdisciplinary housing counseling (ProWoB project) and robot-assisted elder care (Pepper robot study). She leads international educational initiatives like the Erasmus Winterschool and Summerschool programs. Her publications span topics including project management in PhD research , interprofessional curricula , and media competency for migrants . She is affiliated with academic organizations such as the German Society for Nursing Science and the German Society for Pedagogy .

Gudrun HillerView profile

Professor

• Particle Physics
• Flavor Physics
• Beyond the Standard Model (BSM)
• +12 more

Prof. Dr. Gudrun Hiller is a faculty member in the Department of Physics at the Technical University of Dortmund, where she conducts research in theoretical particle physics. She is affiliated with the HEP theory group and actively involved in the IMAPP international master program in particle physics. Her research spans flavor physics, rare decays of beauty and charm quarks, physics beyond the Standard Model, asymptotic safety, and SMEFT. University: Technical University of Dortmund School: Faculty of Physics Department: Department of Physics Office: Room P1-04-307 Email: gudrun.hiller@tu-dortmund.de Phone: +49 (0)231 755-3580 Her research focuses on flavor physics, emphasizing rare semileptonic and radiative decays of beauty and charm quarks, precision tests with top quark observables, and the development of novel particle physics models with controlled high-energy behavior (asymptotic safety). She leads the BSM seminar, covering topics such as flavor, Higgs, dark matter, quantum gravity, and asymptotic safety. The recent publications and workshop activities indicate a strong focus on rare charm decays, CP violation, flavor anomalies, leptoquarks, dark matter models, and the interplay between flavor physics and collider phenomenology. Her group actively participates in international collaborations and workshops, including those at CERN, DESY, and Aspen Center for Physics. DFG Research Unit: Theoretical Flavor Physics Dortmund/Siegen BMBF Theorieverbund (2012-2015) Particle Theory Group at Dortmund: R&D on EOS Member of the HEP theory group at Dortmund Organizer of workshops on asymptotic safety and flavor physics Prof. Hiller supervises students and postdoctoral researchers, with recent seminar topics indicating active advising in areas like flavored dark matter, leptoquarks, proton decay, and flavor anomalies. She has taught courses including Introduction to Elementary Particle Theory, Theoretical Physics II, and General Relativity, demonstrating a strong commitment to education and mentorship.

Jianbing (Jason) LiView profile

Professor

• Environmental pollution control
• Petroleum waste management
• Soil and groundwater remediation
• +3 more

Dr. Jianbing Li is a Professor and Professional Engineer (P.Eng.) in the Environmental Engineering Program at the University of Northern British Columbia (UNBC), holding prestigious fellowships from CSCE, CSSE, EIC, and Engineers Canada. His research program addresses critical environmental challenges with significant real-world impact, particularly in northern and remote communities of British Columbia. Education: PhD in Environmental Systems Engineering, University of Regina Research Focus: Dr. Li's work centers on environmental pollution control , petroleum waste management , soil and groundwater remediation , environmental modeling , risk assessment , and oil spill response . His innovative approaches integrate machine learning, advanced materials, and sustainable engineering principles to develop practical solutions for complex environmental problems, with particular emphasis on resource recovery from waste streams. Publication Trends: Analysis of his 15 most recent publications (2023-2025) reveals a strategic focus on oil spill response technologies, wastewater treatment innovations, and waste valorization. Key advancements include nano/micro bubble flotation systems, chitosan-based adsorbents, and machine learning models for pyrolysis optimization, demonstrating his leadership in translating laboratory research to field applications. Scientific Recognition: 2024 Fellow of Engineers Canada and Engineering Institute of Canada 2023 CSCE Dr. Albert E. Berry Medal (Canada's top environmental engineering award) Multiple UNBC Research Excellence Awards (2010, 2014, 2019, 2023) 2013 Northern BC Business and Technology Award with Husky Energy Best paper awards from International Academy of Science and Environmental Geotechnology Society Research Leadership: Dr. Li has secured over $800,000 in 2023 and $1.9 million in 2020 for oil spill response research through NSERC, DFO, and NRCan. His current portfolio includes groundwater protection for Indigenous communities, next-generation decanting technologies, and water security for remote regions. He actively mentors PhD, MSc, and MASc students while serving on NSERC evaluation committees and co-directing the UNBC/UBC environmental engineering program (2013-2017). Collaborative Networks: Dr. Li leads multi-institutional partnerships with UBC, government agencies, industry (including Husky Energy), and Indigenous communities like Lheidli T'enneh First Nation. His work through the Multi-Partner Research Initiative addresses practical challenges in rural British Columbia while advancing fundamental knowledge in environmental systems engineering.

Carlee A. BishopView profile

Professor

• Systems Engineering
• Experiential Learning
• Problem-Based Learning
• +7 more

Carlee A. Bishop is a Professor of Physics at Agnes Scott College, located in the Department of Physics within the College of Arts and Sciences. She holds a PhD in Electrical Engineering from Auburn University, an MS from Georgia Institute of Technology, and a BS from the U.S. Air Force Academy. Her academic and professional work bridges physics, engineering, and systems thinking. Her educational background includes: BS in Electrical Engineering, U.S. Air Force Academy MS in Electrical Engineering, Georgia Institute of Technology PhD in Electrical Engineering, Auburn University Dr. Bishop's research and teaching focus on experiential learning in STEM, employing case studies, problem-based learning, and experimentation platforms. Her interests include systems thinking, ethical use of technology and data, and managing emerging technologies. She emphasizes decision-making and problem-solving skills in engineering education. The recent publications reflect a strong trend in systems engineering applied to defense, disaster response, and acquisition systems. Her work integrates modeling, simulation, and lifecycle management, with applications in military robotics, humanitarian logistics, and procurement optimization. The interdisciplinary nature of her scholarship connects engineering, ethics, and real-world operational challenges. Her professional affiliations include: INCOSE (International Council on Systems Engineering) Member Certified Systems Engineering Professional (CSEP) IEEE (Institute of Electrical and Electronics Engineers) Member Dr. Bishop has contributed to significant tutorials and workshops at INCOSE symposia and military capstone events. She has advised on systems engineering best practices, autonomy in defense robotics, and disaster response logistics. While no formal list of advisees is provided, her leadership in capstone projects and professional tutorials indicates active mentorship and educational outreach. She has not received any explicitly mentioned scientific awards. She is involved in academic and professional teams related to systems engineering, particularly through INCOSE and IEEE. Her work with military and disaster response systems suggests collaboration with interdisciplinary teams focused on national security and humanitarian applications.

Theodore KypraiosView profile

Professor

• Bayesian Inference
• Statistical Methodology
• Infectious Disease Modeling
• +5 more

Theodore Kypraios is a Professor of Statistics at the School of Mathematical Sciences, University of Nottingham, United Kingdom. He serves as Course Director for the MSc in Statistics and MSc in Statistics with Machine Learning programmes, and as Head of the Statistics and Probability Section. Kypraios joined the University of Nottingham in September 2006 as a Research Fellow and was appointed as Lecturer in 2008. His research focuses on developing novel statistical methodology for Bayesian inference and model selection for high-dimensional complex data, with particular emphasis on stochastic epidemic models and infectious disease outbreak data. Kypraios has made significant contributions to Bayesian nonparametric methods, as evidenced by his PNAS publication on heterogeneously mixing infectious disease models which enables more data-driven approaches to understanding transmission mechanisms without strict parametric assumptions. Kypraios has been actively involved with the Royal Statistical Society, serving as Chair of the Computational Statistics and Machine Learning Section until December 2020, and currently sits on the Academic Advisory Group committee. He has presented his work at major conferences including the International Symposium for Bayesian Analysis and the Bayesian Inference for Stochastic Processes Workshop. As an educator, Kypraios has taught Statistical Inference and Data Analysis and Modelling modules at Nottingham, and has been an instructor for the 'MCMC II for Infectious Diseases' module at the Summer Institute in Statistics and Modeling in Infectious Diseases since 2010. His teaching emphasizes both classical and Bayesian approaches to statistical inference with applications to real-world problems. He has supervised PhD students including Dr. Rowland Seymour, whose thesis work formed the basis of the PNAS publication. His research has practical implications for understanding disease transmission mechanisms, as demonstrated by his analysis of the 2001 UK foot and mouth disease outbreak, and contributes to the development of more effective disease control strategies.

Stavros DemetriadisView profile

Professor

• Learning Technologies
• Educational Technology
• ICT in Education
• +7 more

Stavros Demetriadis is a Full Professor at the School of Informatics, Aristotle University of Thessaloniki, Greece. His research focuses on Learning Technologies, including Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning (CSCL), Computational Thinking, and Massive Open Online Courses (MOOCs). He has led EU-funded projects like colMOOC and developed educational tools such as 'pytolearn' for Python instruction and 'Cubes Coding' (winner of Open Education Challenge 2014 and NUMA Competition 2014). He has supervised 5 completed PhD theses, 4 ongoing PhDs, and over 60 Master’s theses. Academic Appointments: Full Professor (2020–present), Associate Professor (2015–2020), Assistant Professor (2012–2015), Lecturer (2002–2008), Informatics Teacher (1989–2002) Education: PhD in Multimedia Technology in Education (2000), MSc in Electronic Physics (1986), BSc in Physics (1983) His work bridges AI and education, with over 161 publications and an h-index of 27. Recent research explores ChatGPT integration, ethics in Learning Analytics, and AI-driven assessment tools. He has delivered invited talks at institutions like the University of Valladolid (2024) and coordinates the 'Teachers' Fast-paced Distance Training on Tele-education' project. Awards include three international best paper awards and recognition for his 'Cubes Coding' project. Key Research Contributions: Developed frameworks for Conversational Agents in CSCL Innovated Computational Thinking pedagogy through robotics Explored ethics and culture in Learning Analytics adoption Created Python-based MOOCs for non-programmers He has taught courses like Human-Computer Interaction and Learning Analytics, and led short programs on Conversational AI. His collaborations span institutions in Spain, Denmark, and Greece. ORCID: 0000-0002-1561-6372; Google Scholar, Semantic Scholar, and Scopus profiles list his extensive output.

Boris KausView profile

Professor

• Geodynamics
• Lithospheric Deformation
• Numerical Modeling
• +5 more

Boris Kaus is a Full Professor and Chair of Geophysics and Geodynamics at the Institute of Geosciences, Johannes Gutenberg University Mainz, Germany. His research focuses on understanding geological processes from grain scale to planetary scale using mathematical and numerical models. Funded by the German Research Foundation, European Research Council, and BMBF, his work spans lithospheric deformation, melt migration, fold-and-thrust belts, and high-performance computing applications in geosciences. His research interests center on geodynamic modeling of lithospheric processes, including subduction zones, mantle convection, and crustal deformation. Kaus develops novel numerical approaches to simulate complex geological phenomena, with emphasis on coupling between erosion, lithosphere dynamics, and mantle flow. His group creates specialized software for high-performance computing systems to tackle multi-scale geophysical problems. His scientific awards include the Paul Niggli Medal, EGU Arne Richter Award, multiple ERC grants (Starting, Proof-of-Concept, Consolidator), and the Carl Friedrich Gauss Lecturer honor. He has received recognition for editorial contributions including G-Cubed's Excellence in Refereeing award. ERC Consolidator Grant MAGMA (2018-2023) ERC Proof of Concept Grant SALTED (2016-2017) ERC Starting Grant MODEL (2010-2015) John von Neumann Excellence Project for HPC ETH Medal for Ph.D. thesis Kaus actively supervises graduate students and leads research projects funded by major European and German agencies. His group develops open-source software like GeophysicalModelGenerator.jl and maintains strong collaborations with international institutions including ETH Zürich and USC. Current projects focus on magma dynamics, lithospheric shear localization, and the development of advanced numerical methods for geodynamic simulations. The research group operates within the Geodynamics & Geophysics team at JGU Mainz, utilizing high-performance computing resources and collaborating with multiple European research initiatives including IMPRS and FORTHEM networks. Their laboratory specializes in numerical modeling of Earth systems with applications to tectonics, volcanology, and crustal evolution.

Anna Schnauber-StockmannView profile

Associate Professor

• Media Use and Effects
• Mobile Media and Communication
• Situational Media Research
• +4 more

PD Dr. habil. Anna Schnauber-Stockmann is a prominent researcher in media and communication science at Johannes Gutenberg University Mainz, where she has been a member of the Media Structure and Media Effects research group since 2010. She completed her habilitation in October 2024 with the thesis 'The Importance of the Situation in Media Use and Media Effects Research' and was awarded Venia Legendi in Communication Science. Previously, she served as an interim professor at IJK (HMTM Hannover) from April to September 2021. Her academic journey includes earning a Dr. phil. in Communication Research in May 2016 with a dissertation on 'Day-to-day Media Selection. The Role of Habits in the Selection Process' and completing her Master's degree at the University of Mainz in 2007. Dr. Schnauber-Stockmann's research focuses on media use and effects, particularly examining how situational factors influence media selection and consumption patterns. Her work explores media habits, mobile communication behaviors, self- and feedback-effects in media contexts, and the application of quantitative research methods, especially in situ methodologies. She investigates how daily routines shape media platform usage and how these patterns affect individual behavior and social interactions. Her research bridges theoretical frameworks with practical applications in digital media environments, with particular attention to how time, context, and personal characteristics interact in media consumption. Her recent publications reveal a strong emphasis on situational media research, with significant contributions to understanding phubbing behavior, mobile media habit formation, and the distinction between person-specific and situation-specific variations in media use. Through meta-analyses and longitudinal studies, she has advanced methodological approaches for measuring media habits and examining real-time media effects. Her work consistently applies sophisticated quantitative methods to capture the dynamic nature of contemporary media consumption. Top Faculty Paper 2023 of ICA's Mobile Communication Division Top Student-led Paper 2023 of ICA's Mobile Communication Division Best Proposal Award 2017 of the DGPuK division Methods Research grant from the 'Friends of the University of Mainz' for outstanding dissertation (2017) Award for best dissertation on media convergence, University of Mainz (2016) As an active member of the academic community, Dr. Schnauber-Stockmann serves as treasurer of the German Communication Association (DGPuK) since May 2020 and previously served as spokesperson for the Media Reception and Effects division (2019-2021). She is an editorial board member for 'Media Psychology' and 'Mobile Media & Communication' and regularly reviews for leading communication journals. Her work demonstrates significant influence through numerous invited presentations and collaborations with international researchers across multiple institutions.

Florian DiekertView profile

Professor

• Environmental Economics
• Resource Economics
• Socio-ecological Systems
• +7 more

Professor Florian Diekert is a Professor of Environmental Economics at the University of Augsburg's Faculty of Business and Economics and a member of the Centre for Climate Resilience. He leads the Environmental Economics Lab, which focuses on designing, analyzing and testing strategies for sustainable and resilient development, with particular emphasis on socio-ecological systems under pressure and group decisions under strategic and natural uncertainty. Professor Diekert received his education from the Technical University Dresden (International Relations) and the University of Oslo (MPhil in Economics, PhD in Economics in 2011). His research employs economic experiments, theoretical modeling, and statistical analysis, often in interdisciplinary collaborations with natural scientists. Prior to joining the University of Augsburg in 2023, he was a Junior Professor in Heidelberg and conducted research visits at Columbia University and UC Santa Barbara. His research spans Environmental Economics , Resource Economics , and Behavioral Economics , with specific focus on socio-ecological systems, group decision-making under uncertainty, lab-in-the-field experiments, social norms, and early warning systems for ecological tipping points. His work integrates theoretical insights with practical applications for sustainable development policy, often through interdisciplinary collaborations with natural scientists. Professor Diekert's publication record reveals a consistent trajectory of high-impact research on climate resilience, fisheries management, and collective action problems. His recent work increasingly incorporates experimental methods to investigate how environmental conditions shape economic behavior across different cultural contexts (Chile, Norway, Tanzania), and how policy interventions can improve sustainability outcomes through behavioral insights. ERC Starting Grant 'NATCOOP' for research on how nature shapes preferences and incentives of economic agents and how this affects common-pool resource management Professor Diekert advises multiple doctoral students and leads a vibrant research team including postdoctoral researchers and doctoral candidates. His Environmental Economics Lab actively participates in major international conferences such as the Global Tipping Points Conference, Nordic Annual Environmental and Resource Economics Workshop, and European Association of Environmental and Resource Economists conference, demonstrating strong international engagement in his field. The Environmental Economics Lab at the University of Augsburg brings together economists, natural scientists, and policy experts to address pressing sustainability challenges through interdisciplinary research. The lab conducts both theoretical and experimental work, with field studies in various international contexts including Chile and Tanzania, and maintains strong connections with other research institutions across Europe and beyond.

Maja ElmgrenView profile

Senior Lecturer

• Chemistry Education Research
• Physics Education Research
• Higher Education
• +8 more

Maja Elmgren is a Senior Lecturer in Physical Chemistry and Educational Developer at Uppsala University's Department of Chemistry and Faculty of Science and Technology. Since 2009, she has directed the Council for Educational Development (TUR), focusing on academic leadership, chemistry education, and scholarly teaching. Her research spans physical chemistry, chemistry/physics education, and higher education development. Research Interests: Leadership in higher education and doctoral assessment Educational expertise in academia Student learning in thermodynamics and kinetics Chemistry education through international cooperation Quantum mechanics conceptualization Thermal phenomena visualization via infrared cameras Article Trends: Recent publications highlight interdisciplinary learning (chemistry-mathematics), assessment reform in doctoral education, student-centered pedagogy, and technological tools in science education. Subfields include mathematical modeling, entropy understanding, and VR-funded projects on science teacher roles. Scientific Awards: Medal for Merit from Uppsala Science and Technology Student Union (2011) Distinguished Teaching Award from Uppsala University (2001) Academic Roles: Director, Council for Educational Development (TUR) since 2009 Author of "Academic Teaching" (2018) and "Universitetspedagogik" (2016) International collaborations with IUPAC and VR-funded projects Specializes in entropy/thermodynamics education and infrared camera applications

• Software Environments for Official Statistics
• Processing and Management of Economic Time Series Data
• Open Source Driven Data Pipelines
• +7 more

Matthias Bannert is a Lecturer at the Department of Management, Technology, and Economics at ETH Zürich, where he works at the KOF Swiss Economic Institute (Konjunkturforschungsstelle). His work focuses on the intersection of economics, software development, and data management, with particular expertise in time series analysis and official statistics. Bannert designs solutions for state-of-the-art data processing, management, and publishing of economic data and research. Bannert completed his doctoral thesis titled "Survey Based Research in Economics - Essays on Methodology, Economic Applications and Long Term Processing of Economic Survey Data" at ETH Zürich in 2016. His academic journey began when he joined KOF in late 2008, initially working as a researcher for the Business Tendency Survey group before transitioning to the institute's IT department. Dr. Bannert's research interests span several interconnected domains at the nexus of economics and data science. He specializes in developing software environments for official statistics, with particular focus on processing and managing economic time series data through open-source driven data pipelines. His technical expertise includes R programming and PostgreSQL database systems, which he applies to create robust solutions for economic data analysis. Bannert is particularly interested in survey methodology, nowcasting techniques, and the development of reproducible research workflows. His work bridges the gap between theoretical economics and practical software implementation, ensuring that economic research can leverage state-of-the-art data processing techniques. Analysis of Bannert's publication record reveals a consistent focus on the application of data science techniques to economic research problems, particularly in the domain of official statistics and survey-based economics. His work demonstrates a progression from theoretical survey methodology to practical software implementation, with increasing emphasis on real-time economic forecasting and data management systems. A distinctive feature of his research is the development of open-source R packages that make advanced economic data analysis more accessible to researchers and practitioners. As an active contributor to the R language for Statistical computing and the open source community, Bannert has developed several notable software packages including timeseriesdb, tstools, and kofdata, which are available on CRAN. These tools reflect his commitment to creating reproducible, transparent, and efficient workflows for economic data analysis. Bannert serves as a data science supervisor for multiple KOF research projects and is a co-Principal Investigator in an SNF-funded Digital Lives project in collaboration with KOF's labor market expert group. His teaching activities include "Hacking for Sciences - An Applied Guide to Programming with Data" and involvement in the Nowcasting Lab, which provides live out-of-sample forecasting and model testing capabilities for economic researchers. Dr. Bannert is affiliated with the KOF Swiss Economic Institute, where he contributes to several research groups including the KOF Macroeconomic Forecasting group and the KOF Data Science and Macroeconomic Methods group. His work at KOF bridges the institute's traditional economic research with modern data science approaches, helping to position the institute at the forefront of data-driven economic analysis.