Lutz Schubert is a researcher at the Institute of Computer Science , University of Cologne. He focuses on efficient distributed and parallel execution environments for heterogeneous systems, notably the MyThOS operating system in collaboration with Brandenburg University of Technology, Cottbus-Senftenberg. His interdisciplinary work bridges computer science and digital archaeology , addressing modeling of non-deterministic events from sparse excavation data and exploring human behavior constraints in archaeological contexts. Research Interests Design of modular, scalable operating systems for distributed systems Optimization of execution environments for heterogeneous hardware Application of complex systems modeling to digital archaeology Statistical and probabilistic methods for archaeological interpretation Autonomic resource distribution and adaptation in computing Publication Trends : His work spans operating systems , parallel computing , and digital humanities , with recent emphasis on probabilistic reasoning in archaeology and adaptive OS design for multicore architectures. Labs & Collaborations : He collaborates with Brandenburg University of Technology on MyThOS and leads research in computational archaeology as chair of Computer Applications and Quantitative Methods in Archaeology (CAA) , Germany.
Isaac Osei-Tutu serves as a Research Fellow at the Bayreuth International Graduate School of African Studies (BIGSAS), University of Bayreuth, where his work bridges religious studies, business ethics, and African socio-economic contexts through interdisciplinary research. His research centers on Business and Corporate Ethics, Economics of Religion, Christianity in Africa, and Pentecostal/Charismatic movements, with a current focus on Ghanaian Neo-Pentecostal churches. He investigates the ethical frameworks within religious-economic enterprises like International Central Gospel Church and Lighthouse Chapel International, analyzing how prosperity gospel theology influences entrepreneurial structures and ethical conduct through mixed-methods approaches combining ethnography, interviews, and quantitative assessment of honesty, persistency, and consistency. Scientific Awards: No awards listed in provided source material Advising and Grants: No student advisement details or grant information specified
PD Dr. Christian Zillinger is a researcher at the Karlsruhe Institute of Technology (KIT), specifically within the Department of Mathematics. He leads the Junior Research Group "Stability and Instability in Fluids and Materials" (AP6) as part of the CRC 1173. His office is located at Kollegiengebäude Mathematik (20.30), room 2.024 in Karlsruhe, Germany. Dr. Zillinger obtained his PhD under the supervision of Herbert Koch at the University of Bonn. Following his doctorate, he served as an assistant professor (NTT) at the University of Southern California and was a postdoctoral fellow at BCAM (Basque Center for Applied Mathematics). He recently completed his habilitation thesis titled "On Mixing and Resonances in Fluid Systems" at KIT in 2023. Dr. Zillinger's research focuses on partial differential equations motivated by physical problems, particularly in fluid dynamics and material sciences. His work encompasses several key areas: Mixing as a (de)stabilizing mechanism in fluids and inviscid damping Cascades of resonances and instabilities in fluids and plasmas Convex integration and microstructures in materials, including rigidity and flexibility phenomena Magnetic fluids and magnetohydrodynamics Partial dissipation in the Boussinesq equations His recent publications demonstrate a strong focus on stability and instability phenomena in fluid systems, with particular attention to mathematical analysis of PDEs governing fluid behavior. He has made significant contributions to understanding echo chains, resonance phenomena, and damping mechanisms in various fluid models. His work bridges theoretical mathematics with applications in physics and materials science, often employing advanced analytical techniques to address challenging problems in nonlinear PDEs. Dr. Zillinger actively teaches courses at KIT, including "Klassische Methoden für partielle Differentialgleichungen" (Classical Methods for Partial Differential Equations), "Introduction to convex integration," "Introduction to Kinetic Equations," and seminars on microstructure in materials and fluid dynamics. He leads the Junior Research Group "Stability and Instability in Fluids and Materials" which is part of the Collaborative Research Centre (CRC) 1173 at KIT, focusing on wave phenomena. This research group investigates mathematical aspects of stability and instability in physical systems, with applications to fluid dynamics and material science.
Jan Jokisch is a Researcher and PhD student at the Max Planck Institute for Empirical Aesthetics in Frankfurt am Main, Germany, affiliated with the Heisenberg research group. His academic background includes a Master's in Comparative Literature from Johannes Gutenberg University Mainz and the University of Massachusetts Amherst, and a Bachelor's in Comparative Literature and Philosophy from Mainz. He has lectured in German language and literature at Argentine universities and served as a translator for the DEFA Film Library. His research focuses on drama history, quantitative and digital literary studies, and methodologies in the humanities, with current collaboration on the DFG-funded 'Forager Folklore Database (FFDB)' project. Education highlights include a thesis on 'Epistemological Horror in Literature' (2021) and a BA thesis reinterpreting Shklovsky's literary theory through Heidegger's phenomenology (2018). Jokisch has been recognized with DAAD scholarships (2019, 2021) and the Gutenberg Lehrkolleg Award (2018). He has authored and edited conference proceedings, including works on distant reading methodologies and interdisciplinary language studies. His academic work bridges computational analysis with traditional humanities, emphasizing the role of technology in literary research. Collaborations and editorial roles reflect his commitment to fostering international student scholarship and innovative research practices.
Larissa Schlegel-Pape serves as a Scientific Associate at the Department for Ornamental and Pedigree Poultry within the Farm Animal Clinic of Freie Universität Berlin's Faculty of Veterinary Medicine. Her work focuses on developing innovative methods for assessing chicken welfare through the creation of the "Stressed Chicken Scale," which aims to systematically identify stress indicators in poultry. Her research interests center on animal welfare science, specifically stress assessment in chickens using both behavioral observation and computer vision technology. She investigates how body posture, movement patterns, and other visual indicators can reliably signal discomfort or stress in poultry, with the goal of creating practical assessment tools for veterinarians and poultry farmers. Her work bridges veterinary medicine, ethology, and technological innovation, contributing to refinement research (one of the 3Rs principles) in animal husbandry. Analysis of her publications reveals a strong focus on developing and validating the Stressed Chicken Scale across multiple contexts. Her work spans methodological development, practical implementation studies, and technological integration with computer vision systems. The research demonstrates progression from conceptual framework to validation studies and practical application, with increasing sophistication in assessment techniques and broader implications for animal welfare standards in poultry farming. Schlegel-Pape actively collaborates with the Federal Institute for Risk Assessment (BfR) and participates in interdisciplinary projects involving artificial intelligence applications in agriculture. She presents her findings regularly at major German veterinary conferences including the DVG (Deutsche Veterinärmedizinische Gesellschaft) events, DACh Epidemiology conferences, and specialized poultry medicine gatherings. Her work contributes significantly to advancing animal welfare assessment methodologies and promoting refinement in poultry husbandry practices.
Professor Matthias Mann is a world-leading scientist serving as Director of the Proteomics and Signal Transduction department at the Max Planck Institute of Biochemistry in Martinsried, Germany, and Director of the Proteomics department at the Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Denmark. With an h-index exceeding 277 and over 350,000 citations, he is recognized as the highest cited German researcher and one of the most influential scientists globally in proteomics. His educational background includes: Ph.D. in Chemical Engineering from Yale University (1988) Master's Degree in Physics from Georg August University Göttingen (1984) Bachelor's of Arts in Mathematics from Georg August University Göttingen (1982) Professor Mann's research focuses on advancing mass spectrometry-based proteomics to understand biological systems at the protein level. His work spans technological developments in mass spectrometry, bioinformatics and computational analysis, signal transduction and posttranslational modifications, and clinical proteomics applications for disease diagnosis and treatment. The Mann lab has pioneered groundbreaking methods like SILAC for quantitative proteomics and MaxQuant for proteome data analysis. Their vision is to translate proteomics knowledge into clinical practice for predictive, diagnostic, and preventive medicine, with recent work focusing on AI-guided platforms for analyzing proteomes from minimal tissue samples. Analysis of Professor Mann's recent publications reveals a strong trend toward clinical applications of proteomics, particularly in cancer research, metabolic diseases, and neurodegenerative disorders. His work increasingly integrates spatial proteomics, single-cell resolution techniques, and artificial intelligence approaches to uncover disease mechanisms and identify potential biomarkers, with a clear shift from basic technology development toward direct clinical applications and personalized medicine. Professor Mann has received numerous prestigious awards throughout his career: 2025: Elected member of the American National Academy of Sciences 2024: Dr. H.P. Heineken Award for Biochemistry and Biophysics 2023: Otto Warburg Medal 2019: Nominated member of the Bavarian Academy of Sciences 2013: Elected member of Leopoldina German National Academy of Sciences 2012: Körber European Science Award, Louis-Jeantet Foundation Prize for Medicine, Ernst Schering Prize, and Leibniz Prize Professor Mann leads a highly collaborative research team involved in multiple international networks including the Bill & Melinda Gates Foundation, Michael J. Fox Foundation for Parkinson's Research, CLINSPECT-M, and Munich Heart Alliance. His lab has mentored numerous successful researchers, with several former postdocs receiving prestigious ERC Starting Grants. The Mann group has developed innovative clinical proteomics pipelines for analyzing archived tissue specimens and body fluids, aiming to identify protein markers for early detection of diseases such as diabetes and cancer. The Mann lab operates across two major research centers with state-of-the-art mass spectrometry facilities. Their Clinical Knowledge Graph platform integrates multi-omics data with extensive metadata, creating an ecosystem for machine learning applications in proteomics. Current research focuses on developing highly sensitive methods that can profile thousands of proteins from minimal cell samples, enabling the identification of critical disease-related proteins and supporting the development of individualized therapies.
Jaan Masso is an Associate Professor at the University of Tartu, Estonia, where he has been affiliated with the Faculty of Economics and Business Administration since at least 2001. He currently serves as Chair of the department, Head of the Chair of Economic Modelling, and Programme Manager of the Master's programme in Quantitative Economics. His research focuses on applied econometrics, economic development, foreign direct investment, and labor economics, with particular emphasis on Estonia and the Baltic region as catching-up economies. He has published 146 scholarly works with over 23,000 reads and 1,745 citations, demonstrating significant scholarly impact in his field. Masso's research interests span multiple interconnected areas including foreign direct investment effects , productivity analysis , gender wage gap studies , innovation economics , and labor market dynamics . His work often employs rigorous econometric methods to analyze firm-level and regional economic data, particularly from Estonia and other Baltic states. His recent publications (2023-2025) show consistent scholarly productivity across multiple journals, with particular focus on foreign ownership effects, gender pay gaps in academia, FinTech sector development, and innovative methods for measuring firm innovativeness through web data analysis. His scientific contributions demonstrate expertise in analyzing economic transitions in small open economies, with methodological strengths in econometric analysis of firm-level data and innovative approaches to measuring economic phenomena.
Professor Oliver Razum at Bielefeld University's Faculty of Health Sciences leads Working Group 3 in Epidemiology & International Public Health. He serves on multiple commissions including the Faculty Conference and Teaching Commission, and contributes to the Center for Statistics and Bielefeld Center for Data Science. His work focuses on Epidemiology of migration and health Refugee health inequalities Medical rehabilitation equity Othering processes in public health Gender-sensitive health research Recent articles explore 2026 medical rehabilitation for people with disabilities, 2025 refugee mental health frameworks, and 2024 pandemic equity research. Key scientific contributions include the 2025 Georg Forster Fellowship and leadership in diversity-sensitive healthcare initiatives. His research spans urban neighborhood health effects , digital rehabilitation , and structural racism in healthcare . Current projects address intersectional inequalities , post-migration stress , and gender as social determinant . Professor Razum maintains active collaborations with institutions like the German Research Foundation and DRV Westphalia.
Omer Bayraktar is a Group Leader at the Wellcome Sanger Institute , leading research in the Cellular Genomics Programme. His work focuses on decoding human brain cellular diversity using spatial transcriptomics , imaging , and functional screening to study neural complexity in health and disease. Bayraktar's educational background includes a PhD from HHMI under Chris Doe, investigating neural diversity development in Drosophila , followed by postdoctoral work at University of California, San Francisco and University of Cambridge as a Life Sciences Research Foundation Fellow. He developed a spatial transcriptomic pipeline during his postdoc to analyze astrocyte heterogeneity in the cerebral cortex. His research explores neural cell type mapping , glial-neuronal interactions , and cellular pathways in neurodevelopmental disorders . Recent publications emphasize 3D tissue mapping , multi-omic integration , and computational tools like Cell2fate and WebAtlas. His work bridges neurogenetics and computational biology to advance understanding of human tissue ecosystems. Bayraktar's lab collaborates with the Human Cell Atlas initiative and develops technologies such as automated histology pipelines and highly-multiplexed smFISH for molecular cell typing. His team also investigates glia-based therapies and astrocyte functional heterogeneity in neurodevelopmental contexts. Key scientific contributions include: Discovering astrocyte layer patterns independent of neuronal laminae Developing cell2location for spatial cell mapping Characterizing Drosophila neural stem cell models with human relevance Notable awards include the Life Sciences Research Foundation Fellowship during his postdoctoral training. His current group includes a PhD student , Senior Data Scientists , and Bioinformaticians .
Professor Paul Marx is a faculty member at the University of Bonn, affiliated with the Faculty of Philosophy and the Institute of Political Science and Sociology. His research focuses on critical areas of political sociology and policy analysis, with particular emphasis on labor market dynamics and political participation. His research interests center on labor market policy , attitude research , policy analysis , politics and emotions , political socialization , tax and redistribution policy , and inequalities in political participation and representation . Professor Marx examines how economic conditions, particularly labor market experiences, shape political attitudes, behaviors, and representation. His work often employs mixed-methods approaches, combining quantitative analysis with qualitative insights from focus groups and elite interviews. Analysis of Professor Marx's recent publications reveals a consistent focus on the intersection of economic conditions and political behavior. His research demonstrates how labor market insecurity, income inequality, and welfare state policies influence political participation, voting behavior, and attitudes toward redistribution. A notable trend is his examination of political inequality, particularly how economic hardship in childhood affects later political engagement. His work also addresses contemporary political debates in Germany and Europe, including identity politics, gender-neutral language, and taxation policies. Professor Marx maintains an active research agenda with numerous publications in 2023-2025. His work appears to focus on German politics and comparative European welfare states, with some research extending to development contexts such as Bangladesh. His methodology frequently combines survey data with experimental and qualitative approaches to provide comprehensive insights into political behavior.
Thomas S. Lontzek is Professor of Economics at RWTH Aachen University, holding the Chair of Computational Economics within the School of Business and Economics since October 2016. His research develops numerical methods for economic decision-making with focus on climate change and environmental risks. His educational background includes economics studies at Maastricht University and UC San Diego (1999-2003), followed by PhD from University of Kiel (2009). Prior positions include Assistant/Senior Assistant at University of Zurich (2010-2016) and visiting scholar at Stanford's Hoover Institution (2012). Lontzek's research spans Economic Growth, Quantitative Macroeconomics, Resource and Energy Economics, Computational Economics, Climate Risk Management, and Decision Making under Uncertainty. His work emphasizes unconventional methods for analyzing economic processes through multidimensional, nonlinear stochastic optimization while incorporating ethical principles into economic analysis for sustainability challenges. His publication record reveals a consistent focus on climate economics, particularly the social cost of carbon, climate tipping points, and integrated assessment modeling. These works demonstrate how accounting for economic and climate risks, especially potential tipping points, necessitates more aggressive climate policies than traditional models suggest, often requiring sophisticated computational techniques to handle high-dimensional uncertainty. 2021 Erik Kempe Award for work on calculating an optimal CO2 tax Lontzek actively mentors students through research seminars and teaching, emphasizing methodological diversity and interdisciplinary approaches. He leads the Global Challenges Research Seminar through the Global Challenges Lab, providing students with opportunities to conduct innovative research using quantitative decision-making techniques for sustainable development challenges. His teaching portfolio for Summer Semester 2025 includes Quantitative Macroeconomics, Sustainable Finance, and specialized research seminars. He heads the Chair of Computational Economics, which includes scientific staff members Dr. Marco Thalhammer, Dr. Yifan Zhao, and Philipp Olivier, M.Sc., working collaboratively on climate economics and computational methods. The chair's research bridges theoretical economic modeling with practical policy applications, developing dynamic stochastic integrated assessment models capable of handling complex climate-economy interactions under uncertainty.
Prof. Dr. Johannes Sauer is a Professor at the Technical University of Munich (TUM), holding dual affiliations with the TUM School of Management and the TUM School of Life Sciences . His academic focus is on production and resource economics, with expertise in agricultural sustainability, policy evaluation, and circular economy strategies in Asia-Pacific and Latin America. Education: Bachelor’s/Master’s in Agricultural Economics from Universities of Tübingen, Hamburg, and Imperial College London. Doctorate (summa cum laude) in Agricultural Economics from the University of Bonn (2004). Research Interests: Prof. Sauer’s work spans productivity and resilience in agricultural systems, adoption of sustainable technologies, water resource valuation, and bioeconomic trends. He emphasizes smart technologies and circular economy applications in developing regions. His research employs econometric methods to analyze policy impacts and environmental-economic trade-offs. Key Trends in Publications: Recent articles highlight climate-smart agriculture, ICT adoption in rural China, and agroforestry’s role in reducing ecological-economic trade-offs. He explores behavioral drivers of policy participation and innovative tools like the IoFarm decision support system. Awards: 2021 Honorary Professorship at ANU OECD Fellow Awards (2010, 2016) Best Paper Awards (2008–2015) Consulting & Roles: OECD and Asian Development Bank consultant, ESRC Peer Review College member, and liaison lecturer for the German National Academic Foundation. He advises on agri-environmental policies and international development. Labs/Teams: Active in collaborative projects such as PONDERFUL Framework and IPM Popilia , focusing on nexus research and pest management strategies.
Prof. Dr. Rudi Zagst is a Professor of Mathematical Finance at the Technical University of Munich (TUM), where he serves as Head of the Department of Mathematical Finance within the TUM School of Computation, Information and Technology. He has held this position since 2001 and is actively involved in teaching, research, and academic leadership. In 2003, he was appointed as a second member of the Faculty of Economics, and since 2004, he has served as Deputy Chairman of the joint elite degree program 'Finance & Information Management' of the University of Augsburg and TUM. Prof. Zagst earned his doctorate in business mathematics from the University of Ulm, where he later completed his habilitation in 2000. His academic journey began with a professional career at HypoVereinsbank AG, where he served as Head of Product Development in Institutional Investment Management before becoming Managing Director of RiskLab GmbH in 1997. His research focuses primarily on financial engineering, risk management, and asset management, with particular emphasis on portfolio optimization, mathematical finance, and quantitative risk management. His work bridges theoretical finance with practical applications, often incorporating advanced mathematical techniques to solve complex financial problems. Recent publications demonstrate his continued interest in GARCH models, portfolio optimization under various constraints, and the application of machine learning techniques to financial problems. Analysis of his recent publications (2024-2025) reveals a strong focus on portfolio optimization under complex market conditions, particularly using GARCH models to capture volatility dynamics. His work increasingly incorporates machine learning techniques (as seen in the credit spread analysis paper) while maintaining rigorous mathematical foundations. Many papers explore the intersection of theoretical finance with practical investment strategies, reflecting his commitment to bridging academic research with real-world financial applications. Professor of the Year 2007 (awarded by Unicum Profession magazine) Prof. Zagst has supervised numerous bachelor's, master's, and doctoral theses through TUM's Finance and Actuarial Science research group. His collaborative work with industry partners through the TUM CAIR Labs and RiskFactory demonstrates strong connections between academic research and practical financial applications. He has received research funding through various industry partnerships with major financial institutions including Allianz, Munich Re, and ERGO Group AG. Prof. Zagst leads the Research Group Finance and Actuarial Science at TUM, which includes Professors Matthias Scherer, Aleksey Min, and Christoph Knochenhauer. The group maintains strong industry connections through the TUM CAIR Labs initiative, collaborating with over 25 financial institutions including Allianz, Munich Re, Deloitte, PwC, and KPMG. Their RiskFactory laboratory serves as a bridge between academic research and practical financial risk management applications in the industry.
Nasir M. Rajpoot is a Professor in the Department of Computer Science at the University of Warwick, UK. His research focuses on computational pathology, medical image analysis, and deep learning applications in histology. He leads interdisciplinary projects integrating artificial intelligence with healthcare, particularly in cancer diagnostics and pathology workflows. Rajpoot’s work emphasizes developing robust algorithms for histology image analysis, including nuclear segmentation, tumor classification, and domain generalization in computational pathology. His contributions include the TIAToolbox, an open-source framework for tissue image analytics, and the CoNIC Challenge to advance nuclear detection and counting in histology images. He collaborates with clinicians and biologists to translate AI models into clinical practice, addressing challenges like tumor heterogeneity and staining variability. Rajpoot’s research spans colorectal, lung, and oral cancers, with a focus on predicting clinical outcomes via histological features and genomic data integration. Notable projects include the development of Handcrafted Histological Transformer (H2T) for unsupervised representations of whole slide images and the SAFRON framework for histology image synthesis. His work addresses domain adaptation, robustness evaluation, and explainability in AI-driven pathology systems.
Steffi Haag is a Professor of Digital Innovation and Entrepreneurship at the Institute of Computer Science , Heinrich Heine University Düsseldorf (HHU) . She bridges the Faculty of Mathematics and Natural Sciences and Faculty of Business Administration and Economics , collaborating with the Center for Entrepreneurship Düsseldorf (CEDUS) to inspire tech startups. Her research focuses on sustainable information systems, digital experiences, and business models. Steffi Haag’s research integrates Shadow IT , Usable Cybersecurity , and Digital Idea Management . Her work emphasizes theoretical , quantitative , qualitative , and mixed-methods research , including experimental and survey methodologies. Steffi Haag’s publications (2018–2024) span Information Systems , Cybersecurity , Digital Twins , and Sustainable Design . Common themes include Shadow IT dynamics , user behavior in security , and innovation management . Hermann Gutmann Award for special scientific achievements (2023) Schöller Fellow (2020) HMD Best Paper Award (2018) Research Award in Data Protection and Data Security (2017) Dissertation Prize (2017) Steffi Haag has secured grants such as the TU Darmstadt Postdoctoral Fellowship for Female Researchers (2016–2018) and Deloitte Foundation Fellowship (2009–2011). She actively moderates conferences and serves as Associate Editor of Business & Information Systems Engineering .
