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Ira GawlitzekView profile

Senior Lecturer

• Bilingualism
• Multilingualism
• Linguistics
• +3 more

Dr. Ira Gawlitzek is a Senior Lecturer with Tenure and Senior Academic Councillor at the University of Mannheim, affiliated with the Department of English (Anglistik I) within the School of Humanities. Her research focuses on bilingualism, multilingualism, and language acquisition, with specific expertise in corpus linguistics and child language development. She holds a fixed position at the L 10 building, room 219, and her contact includes phone number +49 621 181-2338 and email gawlitzek@uni-mannheim.de. Office hours are by appointment during the semester break and Mondays 2–3 PM during term time. Her research explores topics such as gender differences in language use, ethnic influences on language proficiency, and syntactic development in multilingual contexts. Key contributions include studies on bilingual bootstrapping mechanisms and the analysis of intensifiers in spoken corpora. Her work bridges theoretical linguistics with sociolinguistic applications, emphasizing empirical methods like corpus analysis. Publications span from foundational studies in bilingual acquisition (1990s) to recent investigations into corpus-based sociolinguistic patterns. No specific awards are listed, but her work demonstrates sustained academic impact through interdisciplinary approaches. While no advising records are provided, her teaching and research activities suggest involvement in guiding graduate students in linguistics and applied language studies. Labs or affiliated research groups are not explicitly mentioned, but her participation in collaborative projects like the Spoken BNC2014 study indicates engagement with large-scale linguistic datasets.

• Numerical Optimization
• Mixed-Integer Nonlinear Programming
• Global Optimization
• +14 more

Ruth Misener is a Professor in the Department of Computing at Imperial College London, where she leads the Computational Optimization Group and holds the BASF/RAEng Research Chair in Data-Driven Optimization (2022–2027). She is affiliated with the Faculty of Engineering and contributes to interdisciplinary research institutes including the Data Science Institute, the Institute for Molecular Science and Engineering, and the Sargent Centre for Process Systems Engineering. Her research lies at the intersection of numerical optimization, operations research, and machine learning, with applications in chemical engineering, bioprocess optimization, energy systems, and industrial scheduling. She develops global optimization algorithms for mixed-integer nonlinear programs (MINLP), focusing on real-world challenges such as heat recovery network design, petrochemical process optimization, and robust bioreactor operation. A key innovation is her work on optimizing over machine learning surrogates, including tree ensembles and neural networks, enabling data-driven decision-making under uncertainty. Her recent publications demonstrate a strong trend toward integrating Bayesian optimization with active learning, explainable AI, and industrial applications, particularly in collaboration with BASF, Royal Mail, and Eli Lilly. She develops and maintains open-source optimization tools such as ROmodel, OMLT, and ENTMOOT, which are publicly available on GitHub. STEM for Britain acceptance Runner-Up Presentation Award at PSE@ResearchDayUK Best Quality Poster to Simon Olofsson 1st Poster Prize at UK/Ireland Annual Meeting of the Society for Industrial & Applied Mathematics (2018) 2nd Poster Prize at Centre for Process Systems Engineering Industrial Consortium Meeting (2017) 1st Poster Prize at 2nd PSE@ResearchDayUK (2017) 2nd Presentation Prize at Department of Computing Research Associate Symposium (2017) Runner-Up for May Hicks Award (via student Natasha Page) Ruth supervises a dynamic research team and has examined and mentored numerous PhD students, including Jean Kossaifi, Robert Walecki, Alexander Thebelt, and Toby Boyne. She leads major research grants, including the BASF/RAEng Research Chair and the IConIC Prosperity Partnership, and collaborates with industry partners to advance continuous manufacturing and data-driven process optimization. Her team actively disseminates work through open-access publications, video presentations, and social media.

Stefan HerzogView profile

Researcher

• Decision-Making
• Artificial Intelligence
• Collective Intelligence
• +6 more

Stefan Herzog is a Senior Research Scientist and Head of the Research Area Boosting Decision-Making at the Max Planck Institute for Human Development in Berlin. He leads interdisciplinary projects integrating psychology, artificial intelligence, and computational social science to address global challenges like misinformation, climate change, and AI's societal impact. PhD in Psychology (2009, University of Basel) M.Sc. in Psychology (2005, University of Basel) B.Sc. in Psychology (2003, University of Basel) His research focuses on boosting human decision-making through: Hybrid human-AI collective intelligence Strengthening resilience against disinformation Behavioral interventions in digital environments Transparent, non-manipulative policy design Self-nudging strategies Methodological innovation in social science Recent publications emphasize AI ethics , digital sovereignty , and democratic resilience . He has secured significant funding from the EU Horizon program, DFG, and Volkswagen Stiftung. Scientific recognition includes the Hillel Einhorn New Investigator Award (2010).

Francisco José Cuesta ValeroView profile

Researcher

• Climate Change
• Earth's Energy Imbalance
• Remote Sensing
• +3 more

Francisco José Cuesta Valero is a researcher at the Helmholtz Centre for Environmental Research - UFZ in the Department of Remote Sensing . His work focuses on climate change, Earth's energy imbalance, and subsurface thermal dynamics using remote sensing and climate models. Education: Ph.D. in Environmental Sciences, Memorial University of Newfoundland (2020) Master in Earth Sciences, St. Francis Xavier University (2016) BSc in Physics, University of Murcia (2013) Research Interests include: Earth's heat inventory quantification Satellite-based ground heat flux estimation Permafrost and climate feedbacks Borehole climatology methods Thermodynamic modeling of soil-bedrock systems Scientific Contributions reveal trends in climate modeling, heat storage metric development, and land-air temperature coupling analysis. His publications span 2016-2024 with 20+ peer-reviewed works. Awards: Alexander von Humboldt Research Fellowship (2021) He contributes to major projects like G-Flux (global ground heat flux from satellite data) and AI4GHEObs (machine learning for heat flux estimation). Collaborates with institutions including Memorial University, St. Francis Xavier University, and international climate research centers.

Henryk ZähleView profile

Professor

• Stochastics
• Quantitative Risk Management
• Statistical Robustness
• +4 more

Henryk Zähle is a Full Professor of Stochastics at Saarland University's Department of Mathematics, where he has held a W3 position since 2014. He previously served as a W2 Professor (2013-2014) and W1 Junior Professor (2010-2012) at Saarland, and earlier at TU Dortmund University (2007-2010). He earned his Ph.D. in Mathematics from Technical University Berlin (2004) and a Diploma in Mathematics from University of Göttingen (2000). His research focuses on statistical robustness of risk measures asymptotic theory for empirical processes quantitative risk management Markov decision models insurance and financial mathematics with methodological contributions to bootstrapping, quasi-Hadamard differentiability, and sensitivity analysis. Article trends show sustained engagement with stochastic process theory nonparametric estimation robust statistical functionals applications to insurance and finance asymptotic error distributions time series analysis spanning both theoretical and applied domains. Scientific awards include Marie Curie Fellowship (University of Warwick, 2001) DFG Fellowship (2000-2003) He has supervised numerous Ph.D., Master's, and Bachelor's theses on topics like risk measure asymptotics empirical process convergence copula robustness Markov decision sensitivity nonparametric risk estimation statistical bootstrap methods and serves as Associate Editor for Metrika .

Jörg BreitungView profile

Professor

• Econometrics
• Statistics
• Panel Data Analysis
• +3 more

Jörg Breitung is a Professor of Econometrics and Statistics at the Institute of Econometrics and Statistics within the Faculty of Management, Economics and Social Sciences (WiSo Faculty) at the University of Cologne since 2014. He also serves as a Research Professor of the German Bundesbank in Frankfurt since 2002. Research Focus: Panel Data Analysis Time Series Analysis Forecasting Financial Econometrics Scientific Contributions: Developed advanced GMM estimators for spatial regression models Innovative approaches for assessing causality in frequency domains Created robust tests for slope homogeneity in panel data Pioneered methods for serial correlation testing in fixed effects models Contributed to nonlinear panel data modeling and bootstrap techniques Honors and Editorial Roles: Associate Editor of International Journal of Forecasting (2019-) Associate Editor of Journal of Business and Economic Statistics (2017-) Associate Editor of Econometric Reviews (2014-) Contributed to leading journals like Econometrica and Journal of Econometrics

• Statistical Network Analysis
• Non-parametric Statistics
• Causal Inference
• +7 more

Dr. Alexander Fuchs-Kreiß is a Junior Professor for Statistics at the Institute of Mathematics, Faculty of Mathematics and Computer Science at Leipzig University. He joined the university in April 2022 as a member of the Stochastics research group. He is also a scientific member of the International Max Planck Research School for Mathematics in the Sciences and affiliated with the HKMetrics Network. His research focuses on the statistical analysis of network data, particularly semi- and non-parametric methods for dynamic interaction networks. He has developed methodologies for relational event models using counting processes like Hawkes processes, and has contributed to causal inference, high-dimensional statistics, and quantile regression. His work often bridges multiple statistical areas, creating innovative approaches to complex data structures. His recent publications show a strong trend toward developing statistical methods for network data with applications in economics, epidemiology, and social sciences. His research combines theoretical developments with practical implementations, as evidenced by the R packages accompanying his publications. As an educator, he teaches Mathematical Statistics, Statistical Network Analysis, and Causal Inference at Leipzig University. He supervises PhD students working on network models and advises diploma theses in mathematics and business mathematics. Dr. Fuchs-Kreiß maintains active research collaborations with institutions including Heidelberg University, UC Davis, KU Leuven, and LSE. He co-organizes academic seminars and participates in international conferences on statistical learning and probability.

• Statistics
• Stochastic Processes
• Experimental Design
• +6 more

Professor Holger Dette holds the Chair of Stochastics, especially Statistics at the Faculty of Mathematics, Ruhr University Bochum. His research program is centrally focused on advancing statistical theory and methodology through sustained DFG funding. His primary research interests include: Optimal experimental design (both classical and space-time variants) High-dimensional data analysis with bootstrap and sublinear methods Spatial statistics and random field modeling Random matrix theory applications in statistics Covariance structure inference Current research demonstrates strong trends toward computationally efficient methods for complex data structures, particularly in spatial and high-dimensional domains. His work maintains theoretical rigor while addressing interdisciplinary applications in genetics, finance, and material science. Professor Dette actively supervises within major research frameworks: Principal investigator for two Research Groups and multiple In-kind grants Sub-project manager in Collaborative Research Centers (SFB/Transregio) Participating scientist in Cluster of Excellence CASA Former involvement in Graduate School GRK 2131 His research group operates through the Chair of Stochastics, especially Statistics, which serves as the organizational hub for his DFG-funded projects and methodological development.

• Mathematical Statistics
• High-Dimensional Statistics
• Statistical Learning
• +4 more

Professor Angelika Rohde is a faculty member at the University of Freiburg, holding a professorship in the Department of Mathematical Stochastics within the Mathematical Institute. She actively leads multiple German Research Foundation (DFG) projects including Research Group FOR 5381 and Collaborative Research Center sub-projects. Her research specializes in mathematical statistics for high-dimensional data environments, with core expertise in: Computationally feasible bootstrap methodologies Structural inference for covariance matrices under sparsity Discriminant analysis and classification frameworks Statistical inference under randomization constraints Clinical predictive modeling applications Forensic genetics classification systems Current DFG funding supports her leadership in: FOR 5381: Mathematical Statistics in the Information Age (as spokesperson) Integration of multi-site data for clinical predictive models (sub-project manager) Uncertainty quantification in forensic classification (sub-project manager) Prior projects include high-dimensional stochastic differential equations (Priority Program), covariance matrix inference (Research Group), and Graduate School GRK 2131 on high-dimensional stochastics phenomena. She directs the "Mathematical Statistics in the Information Age" research group, fostering interdisciplinary methodological development for modern statistical challenges.

Johannes KrebsView profile

Professor

• Topological Data Analysis
• Persistent Homology
• Spatial Statistics
• +3 more

Prof. Dr. Johannes Krebs holds the Chair of Mathematics - Statistics at the Faculty of Mathematics and Geography, Catholic University of Eichstätt-Ingolstadt since 2021. His academic service includes membership on the editorial board of Statistics , the tenure track board, examination committees for B.Sc. Mathematics and Data Science programs, and the faculty council. His research focuses on topological data analysis, persistent homology, and spatial statistics with applications in stochastic geometry. Funded by Deutsche Forschungsgemeinschaft (KR 4977/2-1 and KR 4977/1-1), his work bridges theoretical statistics with computational topology to develop novel methods for analyzing complex data structures. His methodological contributions span wavelet analysis, functional data, and bootstrap techniques for dependent data. Analysis of his recent publications reveals strong emphasis on topological inference (persistent homology, Betti numbers), spatial statistics, and wavelet methods across multiple high-impact journals including Bernoulli , Annals of Statistics , and Stochastic Processes and their Applications . His work demonstrates consistent innovation in applying topological concepts to statistical problems with theoretical guarantees. Academic service highlights include: Editorial Board Member, Statistics journal Member of Tenure Track Board Examination Committee for B.Sc. Mathematics & Data Science Faculty Council Member His research program is supported by significant DFG funding for projects on Topological Data Analysis (2021-2023) and Dynamic Objects on Random Fields (2017-2020), reflecting sustained contribution to advancing statistical methodology through topological frameworks. He maintains active collaborations with researchers at UC Davis, KU Leuven, and Heidelberg University.