جست‌وجوی استاد و پژوهشگر

Lisa Oswaldمشاهده پروفایل

پژوهشگر

• Political Communication
• Public Discourse in Digital Space
• Political Polarization
• +۹ مورد دیگر

Lisa Oswald is a Postdoctoral Researcher at the Max Planck Institute for Human Development in Berlin, working within the Center for Adaptive Rationality's Cognition in Online Environments research group. She holds a PhD in Political Science from the Hertie School in Berlin, an MSc in Social Data Science from the University of Oxford, and MSc and BSc degrees in Psychology from the University of Kassel. Her research focuses on public discourse in online environments and the role of digital media for democratic politics. Integrating psychological and political science perspectives, she employs computational social science methods including digital trace data analysis and online experiments. Her work examines critical contemporary issues including political polarization, online hate speech, climate change skepticism, and the relationship between digital platforms and democratic processes. Oswald's recent publications demonstrate her leadership in examining how digital environments shape political participation and public trust. Her work combines rigorous methodological approaches with pressing real-world questions about the digital transformation of democratic societies. She has developed expertise in analyzing political discussions on platforms like Reddit and examining how platform design affects user participation. Scientific Awards: Doctoral Scholarship, German Academic National Foundation (2021-2023) Best poster award 2022, PolMeth Europe Highly commended thesis 2020, Oxford Internet Institute Carl-Friedrich Graumann Award, German Psychological Society (2018) Scholarship, German Academic National Foundation (2016-2020) Oswald has served as a teaching assistant for courses including 'Introduction to Data Science' and 'Statistical Modeling & Causal Inference' at the Hertie School. Her research collaborations span multiple institutions, including work with Philipp Lorenz-Spreen, Ralph Hertwig, and other leading scholars in computational social science. She actively engages with policy-relevant research questions, particularly regarding the Digital Services Act and platform regulation.

• Computational modeling of cognition
• Attention processes of decision-making
• Decisions under risk and uncertainty
• +۵ مورد دیگر

Veronika Zilker is a visiting researcher at the Max Planck Institute for Human Development (MPIB Berlin), specializing in computational cognitive science and decision-making processes. She holds a Dr. rer. nat. (2020, summa cum laude) and M.Sc. in Mind and Brain (2016) from Freie Universität Berlin, along with a B.Sc. in Psychology (2013) from the same institution. Education: Dr. rer. nat. (2020, summa cum laude), Freie Universität Berlin M.Sc. Mind and Brain (2016), Berlin School of Mind and Brain, Humboldt University Berlin B.Sc. Psychology (2013), Freie Universität Berlin Research stay (2014), Wellcome Trust Centre for Neuroimaging, University College London Research Focus: Computational modeling of cognition Attention processes in decision-making Decisions under risk and uncertainty Stochastic decision process modeling Honors: Heinz Heckhausen Prize (2022) - German Psychological Society (DGPs) Gender Research Prize (2021) - Free University of Berlin She contributes to the Adaptive Rationality research team and employs interdisciplinary methods spanning experimental psychology, statistics, and computational modeling.

Emilia Ndilokelwa Weyuluمشاهده پروفایل

پژوهشگر

• Congestion Control
• Internet Traffic Analysis
• Transport Protocols
• +۳ مورد دیگر

Emilia Ndilokelwa Weyulu is a Ph.D. student and researcher in the Internet Architecture department at the Max Planck Institute for Informatics, Saarbrücken, Germany, with concurrent enrollment in Computer Science at Universität des Saarlandes. Her work focuses on internet congestion control mechanisms and transport protocol analysis within the Saarland Informatics Campus ecosystem. Her academic journey includes: Ph.D. in Computer Science (2019–present) at Universität des Saarlandes and Max Planck Institute for Informatics Master of Informatics (2016–2018) at Tokyo University of Information Sciences, thesis: Asymmetric RTS/CTS for Exposed Node Reduction Master of Computer Science (2014–2017) at Namibia University of Science and Technology, thesis: A Rate Adaptive and Forward Error Correction Scheme for Video Streaming in 802.11b WLANs Bachelor of Science in Computer Science and Statistics (2006–2011) at University of Namibia Weyulu's research centers on congestion control heterogeneity in internet infrastructure, with emphasis on BBRv3 protocol evaluation, in-band service routing, and network-assisted congestion feedback. Her work bridges theoretical protocol design with empirical measurement in public internet environments, extending to wireless networking challenges including ad hoc WLAN optimization and video streaming reliability. She employs cross-layer approaches to address exposed node problems and throughput limitations in wireless networks. Analysis of her 2024 publications reveals a concentrated focus on next-generation congestion control evaluation, particularly BBRv3's real-world performance across diverse network conditions. Her research combines protocol design with large-scale internet measurement, addressing both wired infrastructure challenges and wireless network constraints through innovative routing and feedback mechanisms. Weyulu has served as tutor for Data Networks courses during Winter 2018 and 2020 terms, and for the Hot Topics in Data Networks Seminar in Summer 2020 at Universität des Saarlandes. She also acted as student scribe for the CoNEXT 2020 TPC meeting, demonstrating active engagement in academic community service. As a core member of the Internet Architecture research group at Max Planck Institute for Informatics, she contributes to projects analyzing internet traffic patterns, transport protocol evolution, and network measurement methodologies within the institute's collaborative research environment on the Saarland Informatics Campus.

Mareike Dresslerمشاهده پروفایل

مدرس ارشد

• Real Algebraic Geometry
• Computational Algebraic Geometry
• Polynomial Optimization
• +۶ مورد دیگر

Mareike Dressler is a Senior Lecturer (A/Professor, tenured) and ARC Discovery Early Career Research Fellow at the School of Mathematics and Statistics, University of New South Wales (UNSW Sydney). She joined UNSW in February 2022 as a Lecturer (Assistant Professor, tenure-track) and was promoted to Senior Lecturer with tenure in July 2024. Her educational background includes: PhD in Mathematics from Goethe-Universität Frankfurt/Main (2018), supervised by Thorsten Theobald M.Sc. in Mathematics from Goethe-Universität Frankfurt/Main (2013) B.Sc. in Mathematics from Goethe-Universität Frankfurt/Main (2010) Mareike's research focuses on real and computational algebraic geometry and polynomial and convex optimization. She also works on problems intersecting with convex geometry, matrix and tensor computation, applied algebraic geometry, algebraic and geometric combinatorics, and real analysis. Her work particularly involves nonnegativity of polynomials, optimization methods, and ranks of matrices and tensors, with a special interest in sums of nonnegative circuits (SONCs) for sparse polynomials. Her research has strong applications in data science and machine learning. Mareike has received several prestigious awards including the ARC Discovery Project 2025 grant for "Quantifying Uncertainty of Risk-Aware Optimization for Safe Decision-Making," the J G Russell Award from the Australian Academy of Science, and the Early Career Impact Award from UNSW Science. She actively supervises research students, including PhD student Hongzhi Liao, Master's student Qi Wang, and recently supervised Moritz Schick to completion of his PhD in 2025. Mareike has secured significant research funding, including an ARC Discovery Early Career Researcher Award (DECRA) for 2024-2026. Mareike is an active member of the academic community, regularly organizing workshops and conferences such as "Optimization Days" at UNSW and minisymposia at major conferences like SIAM Conference on Applied Algebraic Geometry.

• Algebraic Geometry
• Computational Algebraic Geometry
• Integrable Systems
• +۶ مورد دیگر

Türkü Özlüm Çelik is a research group leader at the Max Planck Institute of Molecular Cell Biology and Genetics and the Center for Systems Biology Dresden . Her research bridges abstract algebraic geometry with computational methods and applications in natural sciences. Education : PhD in Mathematics at Institut de recherche mathématique de Rennes (defended in 2018). Her research focuses on algebraic curves, theta functions, and abelian varieties, with applications in integrable systems, biological classification, and optimization. She employs numerical algebraic geometry and computer algebra to extract mathematical structures from scientific data. Notable projects include studies on space sextics, tritangents, and the KP equation. Her group explores bidirectional interactions between mathematics and natural phenomena, emphasizing continuous-discrete duality. Recent collaborations address computational challenges in algebraic geometry, such as Wasserstein distance optimization and eigenpoint analysis of cubic surfaces. In 2024, she received the TUD Young Investigator status and co-organized workshops on computational algebraic geometry and women in mathematics. Her group actively participates in the Elbe Program for postdoctoral opportunities.

Günter Lastمشاهده پروفایل

استاد

• Stochastic Processes
• Stochastic Geometry
• Poisson Processes
• +۶ مورد دیگر

Prof. Dr. Günter Last is a Professor at the Institute of Stochastics within the Faculty of Mathematics at the Karlsruhe Institute of Technology (KIT) . He has held this position since 2000 (C4/W3 Professorship). Last's research focuses on stochastic processes , stochastic geometry , and their applications in mathematics, physics, and finance. Education: Diploma in Mathematics, Humboldt University Berlin (1984) PhD in Mathematics, Humboldt University Berlin (1987) Dr. Sc. in Mathematics, Technical University Braunschweig (1995) Research Interests: Last leads research in Poisson processes, Boolean models, Gibbs processes, and spatial random systems. His work explores Palm calculus, hyperuniformity, normal approximation, and percolation phenomena. He co-authored the textbook Lectures on the Poisson Process with Mathew Penrose. Publications & Trends: His recent work includes Normal approximation of Kabanov-Skorohod integrals , Hyperuniform stable matchings , and Poisson hulls , reflecting a focus on stochastic analysis and geometric probability. His research bridges theoretical insights with applications in digital microstructures and wireless network modeling. Scientific Leadership: Co-Editor for Electronic Journal of Probability (2018-2023) Speaker of DFG Research Unit Geometry and Physics of Spatial Random Systems (2011-2018) Associate Editor for Applied Probability Journals (2005-2019) Advising: Last has supervised 15 doctoral theses and numerous diploma/master's theses, including topics on neural networks, random tessellations, and stochastic financial models.

Abdulraheem Arome Musaمشاهده پروفایل

پژوهشگر

• Genomic Selection
• Statistical Genetics
• Animal Breeding
• +۶ مورد دیگر

Dr. Abdulraheem Arome Musa is a Postdoctoral Researcher in the Domestic Animal Genetics Group at the Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany. He holds a Dr. sc. agr. in Statistical Genetics from FBN and the University of Kiel, and his work focuses on genomic selection, genetic diversity conservation, and breeding program optimization in livestock. B.Sc. Agriculture, Ahmadu Bello University, Nigeria (2005–2010) M.Sc. Animal Science, Ahmadu Bello University, Nigeria (2012–2014) Professional Diploma in Education, Federal College of Education, Nigeria (2012–2015) Dr. sc. agr., FBN Dummerstorf & University of Kiel, Germany (2017–2021) His research centers on genomic prediction , statistical modeling for genetic diversity , and design of sustainable breeding programs . He develops and applies similarity matrices and Mendelian sampling models to preserve haplotype diversity while maintaining genetic gain. His work bridges theoretical genetics with practical applications in farm animal improvement. The most recent articles demonstrate a consistent focus on genomic selection methodologies , genetic diversity metrics , and statistical innovations in animal breeding . His publications span from poultry genetics in Nigeria to advanced genomic modeling in cattle and breeding theory, showing both regional relevance and global scientific impact. Topics include neural networks in agriculture, diallel analysis, and hematological markers, reflecting a broad quantitative and applied approach. Dr. Musa has not been listed with any formal scientific awards in the provided text. He has not been explicitly mentioned as advising any students. There is no information about grants he may have led or participated in. His research is conducted within the Domestic Animal Genetics Group at FBN, which likely involves collaborative work with statisticians, geneticists, and animal scientists focused on sustainable livestock improvement.

Macartan Humphreysمشاهده پروفایل

استاد

• Political Economy of Development
• Governance
• Political Violence
• +۷ مورد دیگر

Macartan Humphreys is the Director of the Research Department Institutions and Political Inequality at the WZB Berlin Social Science Center and holds honorary professorships in social sciences at Humboldt University Berlin and Trinity College Dublin . His work integrates experimental approaches , survey research , and formal theory to address questions in the political economy of development , governance , and political violence . Education: B.A. in history and political science from Trinity College Dublin (1994), M.Phil. in economics from Oxford (2000), Ph.D. in government from Harvard (2003). His research spans causal inference , experimental design , and methodological innovation , with notable contributions to frameworks like MIDA for research design and CausalQueries for Bayesian causal modeling. Recent publications address global vaccine equity , endogenous growth under conflict , and democratic accountability through both quantitative and qualitative lenses . Scientific roles and leadership include membership on the editorial boards of American Political Science Review , Journal of Conflict Resolution , and PSRM , as well as being a founding member of the Evidence in Governance and Politics (EGAP) network and former President of the APSA Experiments section . His field experiments in post-conflict regions like Liberia, Congo, and Aceh have reshaped understanding of aid effectiveness , reintegration programs , and democratic institution-building .

Sarah Depaoliمشاهده پروفایل

دانشیار

• Bayesian Statistics
• Structural Equation Modeling
• Latent Variable Modeling
• +۵ مورد دیگر

Sarah Depaoli is Associate Professor of Quantitative Psychology at the University of California, Merced and Visiting Distinguished Professor at the Methods Center of the Eberhard Karls University of Tübingen . She specializes in Bayesian statistics, structural equation modeling, and mixture modeling with applications in psychological and health-related research. PhD in Quantitative Methods (minor in Mathematical Statistics), University of Wisconsin (2010) MA in Quantitative Psychology, California State University-Sacramento (2007) BA in Psychology, California State University-Sacramento (2003) Her research focuses on: Bayesian estimation of latent variable and growth models Prior distribution selection in small-sample research Measurement invariance testing across populations Development of guidelines for model transparency (WAMBS-checklist) Psychological and health outcome modeling with Bayesian methods The most recent articles demonstrate expertise in: Bayesian longitudinal analysis (CushingQoL interpretation differences) Latent class enumeration in growth mixture models ML vs Bayesian estimation comparisons Health psychological outcomes (PTSD, Quality of Life) Cross-cultural measurement invariance Statistical software implementation (JAGS, Mplus) Scientific awards include: 2015 Association for Psychological Science Rising Star 2013 Hellman Fellow 2011 APA Division 5 Distinguished Dissertation Multiple travel awards from Psychometric Society and SMEP She has advised numerous graduate students and served as Associate Editor for Psychological Methods , Multivariate Behavioral Research , and Journal of Royal Statistical Society, Series A .

Melanie Schirmerمشاهده پروفایل

استاد

• Host-microbial interactions
• Microbiome
• Multi-omics Data
• +۶ مورد دیگر

Melanie Schirmer is a Professor at the Technical University of Munich (TUM) within the TUM School of Life Sciences , specifically the Translational Microbiome Data Integration focus group. She earned her PhD in 2014 at the University of Glasgow and completed postdoctoral work at the Broad Institute of MIT and Harvard. Appointed : Rudolf Mößbauer Tenure Track Professor (2023) Grants : ERC Starting Grant (2022), Emmy Noether Award (2020) Her research spans host-microbial interactions , microbiome , and multi-omics data to understand diseases like inflammatory bowel disease and cirrhosis . She utilizes computational biology to link microbial genes to metabolites and immune responses. Her recent publications focus on diurnal microbiome patterns , sex-specific microbial modulation , and ulcerative colitis mechanisms . Trends include microbiome-disease associations , metabolomic profiling , and multi-omics integration . Scientific Awards : Highly Cited Researcher (2021-2023) ERC Starting Grant (2022) Life Sciences Bridge Award (2022) Emmy Noether Award (2020) Career Development Award (2018)

Felix Rempeمشاهده پروفایل

پژوهشگر

• Mobility Systems
• Machine Learning
• Data Exploration and Analyses Methods
• +۱ مورد دیگر

Felix Rempe is a Rudolf Diesel Industry Fellow at the Technical University of Munich Institute for Advanced Study (TUM-IAS) , affiliated with the BMW Group in the field of Autonomous Driving . He holds a PhD in Computational Science and Engineering from TU Munich, awarded summa cum laude in 2018, and an M.Sc. in Mechatronics from DHBW Stuttgart in 2014 with Honours. His research focuses on data-driven approaches to traffic engineering and control , leveraging machine learning and sensor data from vehicles for real-time traffic state estimation and prediction. His work explores the intersection of mobility systems and artificial intelligence , particularly in the domains of traffic flow theory and digital twin development for transportation infrastructure. Felix’s publications highlight advancements in data fusion techniques , deep learning architectures , and statistical modeling applied to autonomous driving and urban mobility challenges. 2018: PhD thesis awarded summa cum laude 2014: M.Sc. with Honours award for completing the Honour’s track at TUM 2012: BayLat grant for study exchange program Latin America

Juliane Maiمشاهده پروفایل

عضو هیئت علمی

• Computational Hydrology
• Hydrological Modeling
• Sensitivity Analysis
• +۴ مورد دیگر

Juliane Mai is a Research Associate Professor at the University of Waterloo's Department of Earth and Environmental Science and a former Research Scientist at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig. Her work focuses on computational hydrology, model calibration, sensitivity analysis using high-performance computing, and data dissemination tools like HydroHub and CaSPAr. She develops blended hydrological models that combine multiple process implementations and leads large-scale intercomparison projects (GRIP-E, GRIP-GL) across North America's 3,000+ basins. Her research bridges environmental modeling with machine learning and data science, emphasizing open-access platforms for stakeholders. Key projects: GRIP-E/GRIP-GL model intercomparisons Methodological innovations: xSSA, EEE, MVA sensitivity techniques Created data portals: HydroHub for visualization, CaSPAr for climate data Her 2023 Journal of Hydrology paper outlines calibration strategies for environmental models, while 2022 Nature Communications work quantifies process sensitivities across North America. She received the 2023 ASCE-EWRI best case study award for GRIP-E research and serves on editorial boards like Journal of Hydrology .

Johannes Knolleمشاهده پروفایل

استاد

• Condensed Matter Physics
• Quantum Matter Theory
• Quantum Spin Liquids
• +۷ مورد دیگر

Professor Johannes Knolle holds the Professorship for Quantum Matter Theory and Nanophysics at the Technical University of Munich (TUM), within the TUM School of Natural Sciences, Department of Physics. His research focuses on understanding complex emergent behavior in condensed matter systems arising from interactions between many simple components. His work addresses fundamental questions about new quantum phases of matter and their potential applications in quantum technology. Knolle's research interests span condensed matter physics , quantum spin liquids , Kitaev models , and Majorana fermions . His work explores how exotic quantum properties can be harnessed for materials research and quantum technology applications. He has made significant contributions to understanding fractionalization, dynamical correlations, and material connections in quantum spin liquid systems. His recent publications (2021-2025) demonstrate a strong focus on quantum oscillations, topological magnon insulators, Kitaev honeycomb materials, and real-time dynamics in quantum systems. These works reveal trends toward understanding non-Fermi liquid behavior, topological quantum phenomena, and emergent quasiparticles in frustrated magnetic systems. Scientific awards: Charles & Katherine Darwin Research Fellow, Darwin College Cambridge (2015-18) Dissertation Prize SKM of the German Physical Society (DPG) (2015) International Springer Dissertation Award (2015) Doctoral scholarship from the German Academic Scholarship Foundation Fulbright Scholar (2007) Professor Knolle teaches advanced courses including Advanced Statistical Physics, Theory of Quantum Matter, and Journal Clubs on Quantum Matter. His academic journey includes a doctorate from the Max Planck Institute for the Physics of Complex Systems (2014), postdoctoral research at Cambridge University, and a lectureship at Imperial College London before joining TUM in 2019 as Associate Professor. His research contributes to Sustainable Development Goals related to clean energy and advanced materials.

• Neural Machine Translation
• Computational Linguistics
• Natural Language Processing
• +۳ مورد دیگر

Yang Liu is a researcher at the Institute of Computing Technology (ICT), Tsinghua University , and affiliated with the Beijing Academy of Artificial Intelligence . His work spans computational linguistics, machine translation, and dialogue systems, with additional collaborations in medical NLP and cross-lingual knowledge representation. Doctorate from Purdue University Collaborations with Microsoft, Amazon, and Facebook researchers Research focuses on Neural Machine Translation (NMT) advancements through: Self-supervised alignment and regularization Document-level context integration Robust translation frameworks for low-resource scenarios Adapter-based pluggable models Recent works extend to conversational AI, including: Subjective knowledge integration in task-oriented dialogue Context representation analysis for open-domain dialogue Synthetic conversation dataset generation Key contributions include: THUMT: Open-source NMT toolkit Earth Mover's Distance for lexicon induction Context Gates for translation fluency Publications demonstrate continuous engagement with top-tier conferences including ACL, EMNLP, and COLING, collaborating with prominent figures like Maosong Sun and Qun Liu.

Oliver Lüdtkeمشاهده پروفایل

استاد

• Educational Psychology
• Psychological Methodology
• Multilevel Analysis
• +۷ مورد دیگر

Oliver Lüdtke is a Professor for Educational-Psychological Methodological Research at the Christian-Albrechts-University of Kiel and Director of the Department of Educational-Psychological Methods and Data Science at the Leibniz Institute for Science and Mathematics Education (IPN) in Kiel, Germany. His work bridges advanced statistical methodology with applications in educational and psychological research. His research interests include: Multilevel analysis in psychological research National and international comparative school performance studies (e.g., PISA) Personality development in adolescence and young adulthood Application of Bayesian methods in psychology Estimating causal effects with non-experimental data Methodological research and machine learning in education The recent publications highlight his focus on cutting-edge statistical techniques, particularly in psychometrics and longitudinal modeling. His work emphasizes methodological rigor in educational assessment, small-sample estimation, dynamic modeling, and data quality in experience sampling studies. Scientific contributions and leadership roles include: Director, Department of Educational-Psychological Methods and Data Science, IPN (since 2015) Professor at Christian-Albrechts-University of Kiel (since 2014) Key involvement in PISA and the Center for International Educational Comparative Studies (ZIB) He has advised on methodological frameworks in large-scale educational assessments and continues to advance statistical practices in psychology and education. His collaborative work spans institutions across Europe, focusing on data science applications in the social sciences.