جستجوی استاد راهنمای دانشگاهی

Esther Duflo is the Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics in the Department of Economics at the Massachusetts Institute of Technology (MIT). She is also co-founder and co-director of the Abdul Latif Jameel Poverty Action Lab (J-PAL), holds the Chaire, Pauvreté et politiques publiques at the Collège de France, and serves as President of the Paris School of Economics. Her research focuses on understanding the economic lives of people living in poverty to help design and evaluate social policies. Her work spans multiple domains including: Development Economics Poverty Alleviation strategies Health interventions Educational programs Financial inclusion initiatives Environmental policy Governance improvements Duflo revolutionized developmental economics by pioneering the use of randomized controlled trials to test poverty reduction measures. Her empirical approach has challenged conventional opinions about development and has helped improve the efficient use of resources in poverty alleviation programs worldwide. She co-authored the influential books "Poor Economics" and "Good Economics for Hard Times" with Abhijit Banerjee, demonstrating through field experiments how specific interventions (like providing lentils to mothers for child immunization) can dramatically improve social outcomes. Her notable scientific achievements include: Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel (2019) Princess of Asturias Award for Social Sciences (2015) Infosys Prize (2014) John Bates Clark Medal (2010) MacArthur "Genius Grant" Fellowship (2009) A.SK Social Science Award (2015) Duflo has established J-PAL as a global network of over a hundred affiliated professors who use scientific evidence to inform policy decisions in the fight against poverty. J-PAL has offices across Africa, Europe, Latin America and the Caribbean, North America, and South and Southeast Asia. Her work has demonstrated the crucial importance of information in policymaking, with numerous field experiments showing how carefully designed interventions can have significant impacts on social outcomes across multiple domains including health, education, and economic opportunity.

• Development Economics
• Poverty Alleviation
• Health
• +۷ مورد دیگر

Nate Foster is a Professor of Computer Science at Cornell University and currently serves as the Associate Dean for Research in the Ann S. Bowers College of Computing and Information Science. He is also a Visiting Researcher at Jane Street and served as a Visiting Professor at École Polytechnique Fédérale de Lausanne during the 2023-24 academic year. His research uses ideas from programming languages to solve problems in networking, databases, and security. BA in Computer Science, Williams College (2001) MPhil in History and Philosophy of Science, University of Cambridge (2008, all work completed in 2003) PhD in Computer and Information Science, University of Pennsylvania (2009) Foster's research focuses on developing languages and tools that make it easy for programmers to build secure and reliable systems. His current work centers on the design and implementation of languages and tools for programmable networks, particularly using the P4 language. His past work includes bidirectional languages (also known as 'lenses'), database query languages, data provenance, type systems, mechanized proof, and formal semantics. His research group at Cornell has made significant contributions to network verification, software-defined networking, and formal foundations for programmable data planes. Analysis of Foster's recent publications reveals a strong focus on network verification and programming language foundations for networking. His work consistently applies formal methods to practical networking problems, with a particular emphasis on the NetKAT and P4 languages. Over the past five years, his research has evolved toward more complex network verification techniques, including infinite state verification, active learning of network models, and dependently-typed approaches to network programming. His work bridges theoretical computer science with practical networking systems, making formal methods accessible to network engineers. ACM Fellow (2025) ACM SIGPLAN Robin Milner Award (2023) ACM SIGCOMM Rising Star Award (2018) NSF CAREER Award (2013) Alfred P. Sloan Fellowship (2012) Multiple distinguished paper awards across top conferences including POPL, PLDI, and SIGCOMM Foster has advised numerous PhD and Master's students who have gone on to prominent positions in both industry and academia, with many continuing work in programming languages and networking. He has led multiple significant research grants including an NSF CAREER Award and has been involved in the P4 Language Consortium, serving as Chair of the P4 Language Governing Board. His work has been supported by various organizations including NSF, DARPA, and industry partners like Intel and Jane Street. Foster is also active in the programming languages research community, serving on numerous program committees and as Vice Chair of DARPA's Information Science and Technology (ISAT) study group. Foster leads a vibrant research group at Cornell focused on programming languages for networks, with collaborators from academia and industry. His group has developed several influential tools and frameworks including NetKAT, Petr4, and KATch. They maintain strong connections with the P4 community and work closely with industry partners to ensure their research has practical impact on real-world networking systems.

• Programming Languages
• Networking
• Databases
• +۵ مورد دیگر

Hami Amiraslani serves as Assistant Professor of Accounting at ESMT Berlin, holding a PhD and MSc from the London School of Economics. Previously faculty at INSEAD and a Wharton School visiting scholar, he teaches Management Accounting and Sustainable Business Finance across master's and executive programs. His educational credentials include: PhD in Accounting, London School of Economics and Political Science MRes, City St George’s, University of London MSc in International Accounting and Finance, London School of Economics and Political Science Amiraslani's research investigates capital markets, corporate governance, and sustainability interfaces with financial contracting and regulation. His work critically examines how ESG integration, board oversight structures, and climate disclosure frameworks reshape market efficiency and investor behavior, blending theoretical rigor with empirical analysis of regulatory impacts. Recent publications (2023-2025) reveal three dominant research trajectories: 1) Board-level governance mechanisms for ESG risk management, 2) Regulatory consequences of climate disclosure mandates on capital allocation, and 3) Bond market valuation effects of sustainability performance. These studies consistently demonstrate how governance quality mediates the relationship between sustainability practices and financial outcomes across debt and equity markets. No scientific awards are documented in the provided materials. His teaching portfolio indicates active mentorship in accounting education though specific student advisees aren't listed. Research activities appear institutionally supported through ESMT's academic infrastructure without explicit grant mentions.

• Capital Markets
• Corporate Governance
• Corporate Sustainability
• +۴ مورد دیگر

Jan Oliver Borchers is a full professor of computer science and head of the Media Computing Group at RWTH Aachen University, where he holds the endowed Chair in Media Informatics and Human-Computer Interaction (Computer Science 10). He established his research group in 2003 and pioneered modern HCI academic research and teaching in Germany, becoming a leading lab in terms of archival publications at CHI, the top international conference in HCI. Before joining RWTH, he held faculty positions at Stanford University and ETH Zurich. His research focuses on Human-Computer Interaction with particular interest in new user interfaces for soft robotics, textile user interfaces, 3D printing and personal fabrication, augmented reality, wearable and tangible computing, interfaces for software development, deceptive patterns, and interactive guides and exhibits. He opened Germany's first Fab Lab in 2009 and has been instrumental in advancing digital fabrication and maker culture in academia. His work bridges theoretical HCI research with practical applications, as evidenced by his consulting for major companies including AirBus, Apple, ARD, Bayer, Children's Museum Boston, Daimler, Handelsblatt, OTIS, Scout24, TEDx, and Deutsche Telekom. His recent publications show a strong focus on deceptive patterns in UI design, textile interfaces, and the intersection of AI with human interaction. The research demonstrates consistent innovation in tactile interaction techniques, with numerous honorable mentions at top conferences like CHI. His lab has produced significant contributions to eyes-free interaction, textile computing, and the ethical implications of dark patterns, particularly regarding children's experiences with deceptive designs. IDC 2025 Best Work in Progress for research on children's assessment of deceptive designs CHI'25 Student Games Competition Winner for The Deceptive Dungeon RWTH-Wissenschaftsnacht 2024 Best Science Slam for Usability: 4 Prinzipien guter User Interfaces Multiple CHI Honorable Mentions spanning from 2008-2021 Best Note and Best Demo awards at ITS and UIST conferences Borchers has served in numerous leadership roles including heading the Computer Science Department's Examination Board (2015-2025), coordinating the department's public relations since 2010, and organizing the weekly Faculty Lunch since 2003. He is an active member of the ACM, SIGCHI, SIGCHI Germany, and GI, and introduced the Interactivity format to the CHI conference in 2005. His PhD thesis, A Pattern Approach to Interaction Design, became the first book to bring design patterns to HCI. The Media Computing Group under his leadership has developed significant expertise in physical computing, textile interfaces, and fabrication technologies, with a strong emphasis on both theoretical contributions and practical applications. His lab continues to push boundaries in interactive technologies while maintaining a strong ethical stance on user experience, particularly regarding deceptive design patterns.

• Human-Computer Interaction
• Textile User Interfaces
• Soft Robotics
• +۵ مورد دیگر

Dr. Feng Cheng is a Senior Researcher and head of the IT Security Engineering (Sec-Eng) Team at the Hasso Plattner Institute (HPI), Germany, and serves as the Representative of the Chair "Internet Technologies and Systems" at the Digital Engineering Faculty, University of Potsdam. He holds a PhD from the University of Potsdam, an MEng from Beijing University of Technology, and a BEng from Beijing University of Aeronautics and Astronautics. His research is centered on data-driven security engineering, security analytics, network security, cloud security, firewall, IDS/IPS, attack modeling, and penetration testing. Dr. Cheng's research interests span a broad range of cybersecurity domains, with a strong emphasis on security analytics , data-driven threat detection , cloud and network security , and authentication . His work integrates advanced data engineering and machine learning techniques to enhance security operations, including intrusion detection, threat intelligence, and security information and event management (SIEM). Key application areas include IoT security, mobile security, and web security. The recent publications of Dr. Cheng and his team reflect a significant trend towards leveraging big data analytics , machine learning , and graph-based methods for cybersecurity. Their work focuses on developing frameworks for blockchain-based public key infrastructures, advanced SIEM analytics, malware detection using NLP, and chaos engineering for cloud security. This demonstrates a strong commitment to creating practical, scalable, and intelligent solutions for modern security challenges in complex, distributed environments. Dr. Cheng is actively involved in the academic community as a member of ACM and IEEE, a program committee member for numerous international conferences, and an organizer of workshops on cloud computing and cybersecurity. He has also served on editorial boards for international journals. He supervises a large group of PhD, master's, and bachelor's students, guiding research on topics such as security analytics, cyber threat intelligence, digital credentials, and behavioral authentication. He leads the Sec-Eng team, which conducts research on a diverse portfolio including the Security Analytics Lab, HPI-VDB (vulnerability database), Lock-Keeper (physical separation technology), and the Security Lab Generator for scenario-driven security training.

• Data-Driven Security Engineering
• Security Analytics
• Network Security
• +۱۹ مورد دیگر

Prof. Dr. Amelie Hagelauer holds a professorship in Micro- and Nanosystem Technology at the TUM School of Computation, Information and Technology, Technical University of Munich. Her work focuses on advanced electronics and systems integration across quantum computing hardware, resistive memory technologies, and high-frequency RF systems. She has contributed to innovations in superconducting qubit readout architectures, multi-level RRAM designs, and 3D-integrated CMOS-compatible quantum devices. Research interests span quantum hardware design, nanoelectronic devices, RF front-end systems, and emerging memory technologies. Her work emphasizes practical implementation challenges such as low-power operation, high-voltage handling in RF switches, and wafer-scale fabrication processes. Recent projects include D-band radar systems, energy-efficient 60 GHz transceivers, and antenna tuning solutions for 5G applications. Publications from 2023-2025 showcase advancements in resistive switching device characterization, mitigation of TLS losses in superconducting qubits, and reconfigurable AI accelerators using RRAM-based digital twins. Her work bridges theoretical device physics with practical integrated circuit design, addressing scalability and reliability in next-gen electronics. Awards and grants: None explicitly listed in provided texts. Active collaborations include EU-funded projects on quantum computing platforms and TUM's Electronic Photonic Integration initiatives. Leads research teams in microsystem technology with emphasis on cross-disciplinary approaches combining CMOS processes, MEMS, and quantum engineering.

• Microelectronics
• Nanotechnology
• RF Engineering
• +۳ مورد دیگر

Rainer Watermann is a Full Professor for Empirical Research in Education at the Free University of Berlin since 2011, previously serving as Full Professor for Education and Empirical Research in Schools at Georg-August University of Göttingen (2005-2011). His academic career includes significant research positions at the Max Planck Institute for Human Development in Berlin (1997-2005). Watermann earned his Diploma in Educational Science from the University of Münster (1996), followed by a Dr. phil (2002) and Habilitation (2005), both from Freie Universität Berlin. His educational background established the foundation for his extensive research in educational transitions and disparities. His research focuses on educational transitions, particularly from primary to secondary school and into higher education, examining motivational factors, social background influences, and achievement goal development. Watermann's work consistently addresses how social disparities affect educational opportunities and outcomes, with particular attention to gender differences and longitudinal developmental patterns. His methodological expertise includes latent class analysis, structural equation modeling, and large-scale assessment design. Watermann's publication portfolio reveals consistent research trajectories examining motivational frameworks (particularly expectancy-value theory), educational transitions, social disparities in education, and political socialization. His work spans both theoretical development and practical applications for educational policy and practice, with increasing focus on intervention effectiveness in recent years. As an active member of the academic community, Watermann serves on multiple editorial boards including the Swiss Journal for Educational Sciences and Empirical Educational Science , and regularly reviews for major educational and psychological journals. He has also contributed to significant research centers, including serving as spokesman for the Center for Empirical Research on Teaching and Learning in Schools (ZeUS) at the University of Göttingen (2008-2010). Watermann maintains an active research program with numerous collaborations across Germany and internationally, evidenced by his consistent publication record through 2025. His work bridges educational psychology, sociology of education, and policy-relevant research, maintaining strong connections between theoretical frameworks and practical educational contexts.

• Educational Science
• Empirical Research in Education
• Student Motivation
• +۵ مورد دیگر

Krishna Gummadi is a Scientific Director and Professor at the Max Planck Institute for Software Systems (MPI-SWS) in Germany, where he leads the Networked Systems Research Group. He also holds a professorship at the University of Saarland, demonstrating his dual commitment to research and academic instruction in computer science. His educational background includes: Ph.D. in Computer Science and Engineering from the University of Washington (2005) B.Tech. in Computer Science and Engineering from the Indian Institute of Technology, Madras (2000) Gummadi's research spans networked and distributed computer systems with a current focus on social computing systems. His work addresses critical challenges in algorithmic fairness, privacy in social media, trustworthiness of online identities, and information dissemination in social networks. He approaches these problems through interdisciplinary methods combining user-centric studies, data-centric analysis, and systems-centric design to create practical solutions that enhance fairness, transparency, and user control in online platforms. His methodology integrates large-scale observational studies, computational modeling, and system implementation to tackle complex human-computer interaction challenges at societal scale. His recent publications reveal a strong emphasis on fairness in algorithmic decision making, with significant contributions to quantifying and addressing discrimination in machine learning systems. His work bridges computer science, social science, and ethics, creating frameworks for fair classification, understanding media bias, and developing privacy-preserving techniques that maintain functionality while protecting user data. The research demonstrates a progression from technical system design to addressing societal implications of computing systems. Among his notable scientific achievements: ERC Advanced Grant in 2017 for 'Foundations for Fair Social Computing' Test of Time Awards at ACM SIGCOMM and AAAI ICWSM Casper Bowden Privacy Enhancing Technologies (PET) and CNIL-INRIA Privacy Runners-Up Awards IW3C2 WWW Best Paper Honorable Mention Multiple Best Paper awards across prestigious conferences Gummadi has advised numerous PhD students and postdoctoral researchers who have gone on to prominent positions in academia and industry. His ERC Advanced Grant has supported extensive research into fair social computing, while his leadership in major conferences (including serving as General Chair for ICWSM 2016 and Program Chair for WWW 2015) has shaped research directions in the field. His teaching portfolio includes courses on Distributed Systems, Human-Centered Machine Learning, and Social Media Analysis. He leads the Networked Systems Research Group at MPI-SWS, which has developed several publicly available systems including tools for fair classification, privacy risk assessment, trust evaluation in social media, and information diet management. The group's work bridges theoretical advances with practical implementations that address real-world challenges in social computing, with numerous software releases and datasets made available to the research community.

• Networked Systems
• Distributed Systems
• Social Computing
• +۵ مورد دیگر

Kaye Morgan is a Research Fellow at Monash University's School of Physics within the Faculty of Science. She holds a Hans Fischer Fellowship at the Technische Universität München (TUM), hosted by Prof. Franz Pfeiffer. Her research focuses on phase contrast X-ray imaging (PCXI), particularly its application in biomedical research and translation to compact imaging systems for clinical use. Educated at Monash University, she earned her PhD in 2011, followed by a Discovery Early Career Researcher Award (2012–2015) from the Australian Research Council. She is also a Veski Victorian Postgraduate Research Fellow, combining her roles at Monash with visits to TUM supported by her Hans Fischer Fellowship. Her research interests include developing PCXI methods for non-invasive imaging of soft tissues, such as lung and airway dynamics, and optimizing imaging techniques to minimize radiation exposure. Key projects include assessing cystic fibrosis treatments via airway surface hydration analysis and improving X-ray source accessibility for clinical applications. Notable achievements include pioneering single-grid phase imaging techniques and contributing to high-speed imaging of biological dynamics. Her work has been recognized with awards like the 2014 Tall Poppy Young Scientist Award and the 2011 Australian Synchrotron Thesis Medal. Morgan collaborates across disciplines, working with biomedical researchers to advance imaging technologies for respiratory health. Her publications span journals like Scientific Reports, Optics Letters, and the American Journal of Respiratory and Critical Care Medicine.

• Phase Contrast X-ray Imaging
• Biomedical Imaging
• Medical Imaging Technology
• +۳ مورد دیگر

Mike Kosek (Dr. rer. nat.) is a Research Fellow at the Chair of Connected Mobility (Department of Informatics) at the Technical University of Munich (TUM). His research focuses on transport protocols, congestion control, internet architecture, and internet measurements. Research Interests: Transport protocol design and analysis Congestion control mechanisms Internet architecture and measurement Network performance optimization DNS protocol behavior and privacy Applications in satellite and aerial communication Recent Research Trends: His publications emphasize QUIC protocol analysis, DNS over QUIC investigations, cross-layer protocol interactions, and satellite communication adaptations. Key methodologies include real-world measurements, protocol design extensions, and dataset creation for reproducibility. Contact: E-mail: kosek@in.tum.de Phone: +49 89 289-18665 Office: 01.05.038, Boltzmannstr. 3, 85748 Garching

• Transport Protocols
• Congestion Control
• Internet Architecture
• +۳ مورد دیگر

Daniel Frischemeier is a Professor of Mathematics Didactics with a focus on Primary Education at the University of Münster's Faculty of Mathematics and Computer Science. He has established himself as a leading researcher in statistics and data science education for primary school students, with extensive contributions to educational methodology and teacher training. University of Münster (2021-present) TU Dortmund (2020-2021) University of Paderborn (2009-2020) Ludwig-Maximilians-Universität München (2017-2018) Dr. Frischemeier completed his doctoral studies at the University of Paderborn with a dissertation on statistical thinking and research using TinkerPlots software. His educational background includes graduate studies in Mathematics and undergraduate studies in Mathematics and Physics for teaching at various school levels. His research focuses on the design and testing of teaching-learning environments for primary mathematics education, particularly in the areas of data analysis, probability, and statistics. He conducts qualitative analysis of learners' cognitive processes related to the guiding principle of 'data and chance' in primary education. His work also includes the design and evaluation of teaching materials in data science and civil statistics, the use of learning videos to promote process-related skills, and the implementation of Fermi tasks and computer science education within primary mathematics lessons. Analysis of Dr. Frischemeier's recent publications reveals a strong emphasis on data literacy development in primary education, with increasing focus on the integration of digital tools and the conceptual understanding of data as models. His work bridges mathematics education with emerging fields of data science, addressing both theoretical frameworks and practical classroom applications. The research demonstrates a progression from basic statistical concepts toward more complex data modeling approaches suitable for young learners. Elected member of the International Statistical Institute (ISI) Chair of the Local Organizing Committees for IASE Satellite 2025 Conference Council-Member of the International Statistical Institute Special Edition Editor of the Statistics Education Research Journal Member of International Program Committees for major statistics education conferences Co-Leader of CERME Thematic Working Group 5 on Probability and Statistics Education Dr. Frischemeier serves in numerous editorial capacities and review roles for prominent journals in mathematics and statistics education. He leads significant research projects including 'Promoting Data Science Education for Teacher Education at the University level (DataSETUP)' and 'Data Science Education in STEAM for Civic Engagement and Social Justice from the Early Years (DataScEd4CiEn)'. His work has substantial impact on teacher education programs and curriculum development in statistics and data science for primary schools. He is actively involved in the development and leadership of the Math Center Münster (MaZ), which promotes mathematical potential for all students. His team includes numerous research assistants and doctoral candidates working on various aspects of mathematics education research, particularly focusing on data literacy and statistical reasoning in primary education contexts.

• Mathematics Education
• Statistics Education
• Data Science Education
• +۵ مورد دیگر

Muhammad Ali Gulzar is an Assistant Professor in the Computer Science Department at Virginia Tech and an Amazon Scholar at Amazon Web Services. His research focuses on improving developer productivity through automated debugging and testing for applications in emerging domains, including data-intensive software such as dataflow programs, ML/AI applications, and computational notebooks. Education Ph.D. in Computer Science from University of California, Los Angeles (Google Ph.D. Fellow 2017-2020) Research Interests Gulzar's research spans three primary areas: (1) automated tracking-code localization techniques in web applications, (2) re-engineering testing and debugging for data-intensive applications, and (3) advancing current testing and debugging practices in Federated Learning Applications. His work addresses the challenges of debugging in complex systems where traditional approaches fail due to the scale and distributed nature of modern applications. His research has significant implications for improving software quality, developer productivity, and accessibility in web applications. Research Trends Recent publications demonstrate a strong focus on debugging and testing challenges in emerging application domains. His work bridges traditional software engineering with machine learning, data-intensive systems, and web technologies. Notably, he has made significant contributions to Federated Learning debugging (FedDebug), accessibility challenges in ad-driven web applications, and semantic caching for Large Language Models. His approach often combines novel algorithmic insights with practical implementations that address real-world challenges in software development and maintenance. Scientific Awards Google Ph.D. Fellow (2017-2020) $1.1 million NSF award for Federated Learning research ACM CCS 2024 Distinguished Artifact Award Advising and Grants Gulzar leads a productive research group with multiple students contributing to publications in top-tier venues. His NSF-funded research on Federated Learning demonstrates his ability to secure competitive funding for innovative projects. His advising style appears to emphasize practical impact alongside theoretical contributions, with students often taking lead roles in publications. Current research directions include debugging techniques for Large Language Models, accessibility challenges in modern web applications, and novel testing approaches for distributed data processing systems.

• Fault Localization
• Big Data systems
• Data Intensive scalable computing
• +۵ مورد دیگر

Prof. Chiara Manfletti is a Professor at the Technical University of Munich (TUM), leading the Chair of Space Propulsion and Mobility. She also serves as Director and COO of Neuraspace. Her academic journey includes a degree from Imperial College London (2001), a master's from the International Space University (2002), and a PhD from RWTH Aachen (2010). Previously, she worked at the German Aerospace Center, served as Programme Advisor to the European Space Agency Director General, and became the first President of Portugal's national space agency. Her research focuses on innovative propulsion systems, satellite autonomy, and AI-driven propulsion controls. She has received the National Defence Medal (2020) and Medal of Merit (2020) from Portugal. Research Interests: Democratization of space access via novel propulsion technologies Autonomous and sustainable satellite propulsion systems Data-driven propulsion control using AI and health monitoring Key Contributions: Her work bridges numerical/experimental expertise with space safety policy. Recent publications analyze water hammer phenomena in propulsion systems and propose frameworks for planetary protection in space activities. Awards: National Defence Medal 1st class (2020) Medal of Merit from Portuguese Ministry of Science (2020) Professional Roles: Combines academic leadership with industry roles, actively shaping space policy and innovation. No listed grants are detailed publicly in the provided text.

• Space Propulsion
• Satellite Technology
• Sustainable Space Systems
• +۳ مورد دیگر

David W. Hogg is Professor of Physics and Data Science in the Center for Cosmology and Particle Physics in the Department of Physics at New York University. He serves as Senior Research Scientist in the Astronomical Data Group in the Center for Computational Astrophysics of the Flatiron Institute and maintains an affiliation with the Max-Planck-Institut für Astronomie in Heidelberg. His primary research focuses on observational cosmology, particularly approaches that use galaxies to infer physical properties of the Universe. He also conducts significant research on stellar kinematics in the Milky Way and the measurement and discovery of exoplanets. Across all domains, Hogg develops engineering systems and statistical methodologies that enable large-scale astrophysical projects for both his research group and the broader community. Recent work demonstrates expertise in robust statistical methods, particularly dimensionality reduction techniques like Robust-HMF. His research bridges theoretical statistics with practical applications in major astronomical surveys including Gaia, SDSS-V, and SPHEREx. He frequently explores connections between Bayesian and frequentist approaches to astronomical data analysis, with recent work on nuisance parameter integration, anomaly detection, and robust matrix factorization. Research supported by NYU, NASA, NSF, Moore Foundation, Sloan Foundation Additional support from Max Planck Society, Humboldt Foundation, ERC, Simons Foundation Hogg is actively involved in major astronomical projects including Astrometry.net, Gaia, and SDSS, with long-term comprehensive goals of analyzing all galaxies, stars, and astronomical images. His work emphasizes open science principles, reproducible research practices, and the development of publicly accessible tools for the astronomical community.

• Observational cosmology
• Galactic astronomy
• Exoplanet science
• +۵ مورد دیگر

Prof. Dr. Michael Bosnjak leads the Department for Psychological Research Methods at the University of Trier, Germany, focusing on research synthesis methods, theory-driven machine learning, survey methodology, and experimental designs applied to personality psychology (HEXACO model), consumer behavior, and public health. His team includes Dr. Henning Silber (GESIS), Dr. Bernd Weiß (GESIS), and international collaborators at Utrecht University. Affiliation: University of Trier (Department of Psychology) Editorial Roles: Zeitschrift für Psychologie (Editorial Board), Social Science Computer Review (Associate Editor), Frontiers in Psychology (Review Editorial Board) Grants: DFG SFB 884 (co-applicant), DFG Project PaCO (2019-2024, principle investigator), BMBF-funded GESIS Panel Campus His recent publications analyze panel conditioning effects in longitudinal studies, e-commerce privacy dynamics, personality-trait interactions, and psychosis proneness measurement. Scientific awards include the 2016 BMBF infrastructure grant, 2011 Isaac Manasseh Meyer Fellowship, and 2003 Karin Islinger Award. Current projects address data quality in probability-based and opt-in panels, with experimental designs across eight groups testing measurement error mechanisms. He serves as a co-editor for multiple special issues on survey methodology and tourism psychology.

• Research Synthesis Methods
• Meta-Analysis
• Evidence Gap Maps
• +۱۲ مورد دیگر