جستجوی استاد راهنمای دانشگاهی

• Social Media Analysis
• Online Political Polarization
• Misinformation Detection
• +۷ مورد دیگر

Ashwin Rao is a Research Professor at the University of Southern California's Information Sciences Institute (ISI) within the Viterbi School of Engineering. With a research career spanning over two decades, his work bridges computer science, social sciences, and political science, focusing on understanding human behavior through digital footprints. His academic journey began with signal processing research in the 1990s before evolving into network protocols and mobile computing, and most recently into computational social science and AI ethics. Rao's research interests encompass Social Media Analysis, Online Political Polarization, Misinformation Detection, Network Protocols, Mobile Computing, Privacy in Mobile Applications, Natural Language Processing, and AI Ethics. His work demonstrates a consistent trajectory from technical networking research to the societal implications of technology. His most recent publications reveal a strong focus on understanding political discourse online, particularly examining polarization, emotional responses to events, and the impact of social media algorithms on information ecosystems. His interdisciplinary approach combines computational methods with social science theories to address pressing issues in digital society. Rao has published extensively across top venues including ICWSM, WWW, ACL, IEEE Transactions, and numerous conferences in networking and systems. His work often appears with Kristina Lerman, with whom he collaborates closely at USC ISI. His recent research portfolio shows a sophisticated integration of machine learning techniques with social science questions, particularly examining how language models reflect and potentially amplify societal biases. Rao has made significant contributions to understanding privacy issues in mobile applications, network protocols, and social media dynamics. His research has been influential in both technical communities studying network performance and social science communities examining online behavior. His work on BitTorrent performance, mobile privacy, and social media analysis has been widely cited across disciplines. His laboratory work appears to focus on computational social science methodologies, developing tools and frameworks for analyzing large-scale social media data while addressing ethical considerations in AI and data analysis. Recent projects suggest strong connections with public health research through social media analysis during the pandemic.

Yasmine Briefsمشاهده پروفایل

پژوهشگر

• Algorithms and Complexity
• Computer Vision
• Machine Learning
• +۱۰ مورد دیگر

Yasmine Briefs is a Doctoral Researcher at the Max Planck Institute for Informatics since April 2025, affiliated with the Automation of Logic research group. Her work intersects multiple disciplines within computer science. Algorithms and Complexity Computer Vision Machine Learning Internet Architecture Computer Graphics Databases Information Systems Visual Computing Artificial Intelligence Automation of Logic Network Systems Cloud Systems Multimodal Language Processing Contact: Email ybriefs@mpi-inf.mpg.de , Phone: +49 681 9325 2932, Room 634, Campus E1 5, Saarbrücken, Germany.

• Environmental Chemistry
• Nuclear Waste Management
• Geochemistry
• +۳ مورد دیگر

Dr. Norbert Jordan is a Senior Scientist at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) , affiliated with the Institute of Resource Ecology and the Surface Processes department. His career spans over two decades in environmental and radiochemistry research. Ph.D. in Molecular Chemistry (University of Nice Sophia Antipolis) M.Sc. in Molecular Chemistry (University of Nice Sophia Antipolis) Research Interests: Norbert specializes in thermodynamic database development for rare earth elements (REE) and actinides, focusing on complexation with inorganic ligands (phosphate, silicate), surface processes at solid-liquid interfaces using advanced techniques (ATR FT-IR, XAS, TRLFS), surface complexation modeling, isothermal titration calorimetry, and biogenic selenium nanoparticle characterization. Selected Projects: Norbert leads work packages in the EU-funded RadoNorm project (2022-2025), coordinates the national iCross initiative (2018-2022), and previously managed projects on rare earth element extraction ( r4-SEM2 , 2015-2018), pollutant trapping ( POLLTRAP , 2010-2013), and nuclear waste repository systems ( VESPA , 2010-2014). Advising & Collaborations: He has supervised multiple Ph.D. students including Andrea Sabǎu (2015), Sarah Fischer (2022), and Isabelle Jessat (2024), as well as international collaborations with institutions in France, India, and the U.S. Scientific Contributions: Norbert has authored over 50 peer-reviewed publications and book chapters, and organized sessions at major conferences including the Helmholtz Energy Conference (2023).

Calvin Yehمشاهده پروفایل

پژوهشگر

• Digital Humanities
• Software Development
• AI in Humanities
• +۳ مورد دیگر

Calvin Yeh is a researcher at the Max Planck Institute for the History of Science (MPIWG) since 2017, specializing in digital humanities and software development. He bridges humanistic inquiry with advanced software design, focusing on tools that integrate textual, visual, and geospatial data for historians of science. Role: Central to technical development in projects like LoGaRT, Books in China, CHMap, and Music in Tombs Expertise: Full-text search systems, image/text annotation tools, interactive data visualizations His research emphasizes user-centered digital methodologies and iterative development driven by scholarly feedback. He also explores the application of AI and large language models in humanities research, sharing insights through international workshops and talks. Calvin's recent publications highlight his work on geospatial digital tools, gazetteer analysis, and epistemological approaches to historical data visualization. His contributions span interdisciplinary collaborations and open-access initiatives.

Ren-Yuan Liمشاهده پروفایل

پژوهشگر ارشد

• History of Science
• East Asian Studies
• Textual Analysis
• +۳ مورد دیگر

Ren-Yuan Li is an Associate Research Fellow at the Institute of History and Philology, Academia Sinica, Taiwan, and serves as Director of the IHP Archives. His research focuses on books, knowledge systems, and societal structures in imperial China, with expertise in textual analysis and dissemination of knowledge across social layers. PhD in East Asian Languages and History from Harvard University (2014) Director of Scripta Sinica and Database of Chinese Historical Biographies Current research explores leishu (encyclopedias) and commercial publication in late imperial China His work spans handwritten and printed texts, analyzing their circulation from village to intellectual levels. At the Max Planck Institute for the History of Science (MPIWG), he co-led the working group 'Common Knowledge and Its Sources in the Sinosphere, 14th to 20th Centuries.'

Hannah Zagelمشاهده پروفایل

استاد

• Life Course Sociology
• Reproduction and Family
• Social Inequality
• +۱۲ مورد دیگر

Hannah Zagel is Professor of Life Course Sociology at TU Dortmund University and former Head of the Emmy Noether Research Group 'Varieties of Reproduction Regimes' at the WZB Berlin Social Science Center. She has held visiting and interim professorships at Humboldt-Universität zu Berlin, Freie Universität Berlin, and Harvard University’s Minda de Gunzburg Center for European Studies. Her research is situated at the intersection of sociology, demography, and social policy. Education and Career Highlights: Professor of Life Course Sociology, TU Dortmund University (since 10/2024) Head of Emmy Noether Research Group, WZB Berlin (2022–2028) Visiting Researcher, Harvard University (2024) Interim Professor, Humboldt-Universität zu Berlin (2021–2022) Guest Professor, Freie Universität Berlin (2020–2021) Postdoctoral Researcher at University of Hamburg, University of Bremen, and Yale University Research Interests: Hannah Zagel's work centers on life course sociology, reproductive regimes, family policy, and social inequality. She investigates how institutional frameworks and social norms shape reproductive decisions, family formation, and economic vulnerability across different welfare states. Her research emphasizes comparative analysis across Europe, with a focus on Germany, and integrates micro-level behavior with macro-level policy. Publication Trends: Her recent publications reveal a strong focus on reproductive policy, household structures, and poverty dynamics. She develops conceptual tools like the International Reproduction Policy Database and analyzes how non-teleworkable jobs, single-earner status, and migration status affect household resilience. Her work combines qualitative policy analysis with quantitative social research, often in interdisciplinary collaborations. Scientific Awards: Emmy Noether Research Group Grant (DFG) Advising and Grants: As Principal Investigator of the Emmy Noether Group, Dr. Zagel leads a major research project funded by the German Research Foundation (DFG) from 2022 to 2028. She has also co-led projects funded by the German Federal Ministry of Labour and Social Affairs. While she collaborates widely and mentors junior researchers, no formal PhD or Master’s students are listed in the provided materials. Labs and Research Groups: Dr. Zagel leads the Emmy Noether Research Group 'Varieties of Reproduction Regimes: Institutions, Norms and Inequalities' at WZB Berlin. She was previously associated with the Completed Research Group 'Demography and Inequality' at the same institution. Her work is embedded in a network of collaborations across German and international social science research centers.

• Machine Learning
• Artificial Intelligence
• Speech Processing
• +۶ مورد دیگر

Saeed Amizadeh is a prominent researcher specializing in artificial intelligence and machine learning, currently affiliated with Microsoft's research division. His work spans multiple domains of AI including speech processing, natural language understanding, computer vision, and time series analysis, with a particular focus on developing novel frameworks that bridge symbolic reasoning with neural approaches. Over the past decade, he has established himself as a significant contributor to the field through publications in top-tier conferences including ICASSP, ICLR, AAAI, KDD, and IJCAI. Dr. Amizadeh's research interests primarily center around advancing the theoretical foundations and practical applications of machine learning systems. His work on neuro-symbolic visual reasoning has contributed to understanding how to effectively disentangle visual perception from logical reasoning in AI systems. He has made significant contributions to differentiable programming, particularly in making classical machine learning pipelines fully differentiable, which enables end-to-end optimization of complex ML workflows. His research on speech enhancement using GANs represents cutting-edge work in audio processing, while his time series anomaly detection frameworks have practical applications in numerous industry settings. Analysis of his publication trends reveals a consistent trajectory from theoretical machine learning foundations toward increasingly applied research with practical industrial relevance. His early work (2010-2015) focused on fundamental algorithms and probabilistic modeling approaches, while his more recent publications (2019-2025) demonstrate a shift toward practical AI systems with direct applications in speech processing, audio separation, and enterprise machine learning. A notable theme throughout his career is the development of frameworks that enable more efficient, scalable, and interpretable AI systems. As a key contributor to Microsoft's ML.NET framework, Dr. Amizadeh has played an important role in developing tools that make machine learning more accessible to enterprise developers. His collaborative work spans academia and industry, with notable partnerships with researchers from various institutions as well as within Microsoft Research.

• Federated Learning
• Edge Computing
• Mobile Computing
• +۴ مورد دیگر

Zimu Zhou is an Assistant Professor at Tsinghua University's School of Software, Department of Computer Science and Technology, specializing in federated learning, edge computing, and mobile systems. With an extensive publication record spanning from 2018 to 2025, Dr. Zhou has established themselves as a leading researcher in distributed machine learning systems. Dr. Zhou's research focuses on federated learning systems , mobile AI optimization , and spatial data processing . Their work addresses critical challenges in distributed machine learning including data heterogeneity, communication efficiency, privacy preservation, and practical deployment constraints. Recent research has expanded into federated large language models and advanced personalization techniques for mobile environments. Analysis of Dr. Zhou's publication trends reveals a strong emphasis on practical deployment of federated learning systems, with increasing focus on real-world applications in mobility, urban computing, and AIoT. Their work bridges theoretical advances with practical implementations, as evidenced by multiple publications in top-tier systems and AI conferences. Best Paper Award, MobiCom 2024 ACM SIGSPATIAL Best Paper Honorable Mention, 2022 Dr. Zhou has supervised several PhD students who have become active contributors in the field, including Xiaochen Li, Sicong Liu, and Yexuan Shi. Their research has been supported by multiple grants focused on edge intelligence and privacy-preserving distributed learning. Current projects include federated reasoning with large language models and resource-efficient AIoT systems. Dr. Zhou leads the Distributed Intelligence Lab at Tsinghua University, which focuses on building practical frameworks for decentralized machine learning across mobile and edge environments. The lab collaborates with industry partners to deploy federated learning solutions in real-world settings.

• Virology
• Molecular Virology
• Cell Biology
• +۳ مورد دیگر

Dr. Walter Fuchs serves as Laboratory Head at the Institute of Molecular Virology and Cell Biology (IMVZ), part of the Friedrich-Loeffler-Institut in Greifswald, Germany. Holding a doctoral degree in natural sciences (Dr. rer. nat.), he operates from the institute's campus on Riems Island. His research spans Virology, Molecular Virology, and Cell Biology, with specialized focus on Asfarviruses (including African Swine Fever virus) and Animal Herpesviruses. As leader of the Laboratory for Asfar and Animal Herpes Viruses, Dr. Fuchs investigates viral pathogenesis, molecular mechanisms, and host-pathogen interactions critical to animal health. His work directly supports veterinary virology and pandemic preparedness through the institute's reference laboratory functions. Dr. Fuchs actively supervises academic theses, with records accessible via OpenAgrar, and maintains research collaborations across IMVZ's scientific team including Prof. Dr. S. Finke and PD Dr. A. Groseth. The institute facilitates publication discovery through PubMed and OpenAgrar databases.

• Thermodynamic Modeling
• Actinide Chemistry
• Environmental Radiochemistry
• +۳ مورد دیگر

Dr. Anke Richter is a researcher at the Helmholtz-Zentrum Dresden-Rossendorf since 2002, affiliated with the Institute of Resource Ecology 's Actinide Thermodynamics department. She specializes in thermodynamic modeling of actinide interactions with mineral surfaces, focusing on environmental safety assessments for radioactive waste repositories. Education: PhD in Technical Chemistry, TU Bergakademie Freiberg (1993) Key research areas include development of THEREDA and RES3T databases for geochemical modeling Current work involves surface complexation modeling and sorption database systems Her publications emphasize predictive modeling of actinide sorption processes and uncertainty analysis in environmental radiochemistry. She leads major committee roles at HZDR including Chairwoman of the General Works Council since 2014.

Michael Eischerمشاهده پروفایل

پژوهشگر

• Distributed Systems
• Byzantine Fault Tolerance
• Cloud Computing
• +۴ مورد دیگر

Michael Eischer is a researcher at the Chair of Computer Science 4 (System Software) within the Department of Computer Science at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He has been actively involved in teaching exercises for courses including Middleware - Cloud Computing and Verteilte Systeme (Distributed Systems) from Winter semester 2016/17 through Winter semester 2021/22. His academic work culminated in the 2024 dissertation titled Geo-Replicated Byzantine Fault-Tolerant State-Machine Replication with Low Latency . Dr. Eischer's research focuses on distributed systems with particular emphasis on Byzantine Fault Tolerance, geo-replication, and low-latency state-machine replication. His work addresses critical challenges in cloud computing environments where fault tolerance and performance must be balanced effectively. His research has significant implications for building reliable and efficient distributed systems that can withstand malicious failures while maintaining acceptable performance levels across geographically dispersed data centers. Analysis of his publication record reveals a consistent research trajectory focused on improving Byzantine Fault Tolerant (BFT) systems. Starting with foundational work on scalable BFT on heterogeneous servers (2017), he progressed to address specific challenges including latency-aware leader selection (2018), efficient checkpointing mechanisms (2019), and ultimately developing comprehensive solutions for geo-replicated BFT systems with low latency (2024). His research demonstrates an evolution from theoretical foundations to practical implementations, with recent work culminating in the SPIDER architecture for geo-replicated cloud services. Scientific Awards: Best Student Paper Award at Middleware 2020 for Resilient Cloud-based Replication with Low Latency Dr. Eischer has made significant contributions to the field of distributed systems through his extensive publication record in top-tier conferences including Middleware, PRDC, SRDS, EDCC, and DSN. His work on Byzantine Fault Tolerance has been consistently published in premier venues for dependable computing. While specific grant information isn't detailed in the available materials, his research output suggests involvement in projects related to reliable distributed systems, likely supported by institutional or collaborative funding mechanisms. As part of the Chair of Computer Science 4 (System Software) at FAU, Dr. Eischer works within a research environment focused on system software with applications in dependable distributed computing. His work contributes to FAU's strong research profile in computer science, particularly in areas of systems research with practical applications in cloud infrastructure and distributed services.

• Epigraphy
• Type Design
• Text-Image Relations
• +۲ مورد دیگر

Kristine Weber is a Researcher at the Inscriptions Department, Institute of History, University of Bonn, specializing in epigraphy, type design, and medieval book culture. She has been a research associate in the 'German Inscriptions' project since 2012, contributing to the development of the image database for photographs of North Rhine-Westphalian inscriptions in collaboration with the Cologne Center for eHumanities. Education: Master's degree in art history, medieval history, auxiliary historical sciences, and archival studies (1987–1994) at Universities of Marburg and Bonn Graphic Design studies (1985–1987) at Bielefeld University of Applied Sciences Research Interests: Epigraphic studies focusing on text-image relations and type design Medieval manuscript production and book culture Historical documentation of urban and religious institutions Key Projects: Co-editor of The Inscriptions of the City of Lemgo (2004), part of the 'German Inscriptions' series Contributor to the cataloging of St. Vitus Gladbach's book collection (1993–1996)

Gustavo Castellanos-Galindoمشاهده پروفایل

پژوهشگر

• Tropical fish ecology
• Invasion biology
• Small-scale fisheries management
• +۳ مورد دیگر

Gustavo Castellanos-Galindo serves as Programme Area Manager (PA1) for Coastal Resources and Sustainable Blue Economy at the Leibniz Centre for Tropical Marine Research (ZMT) in Bremen, Germany. His research focuses on tropical marine ecosystems with emphasis on conservation biology and human-environment interactions. His primary research interests include tropical fish ecology , mangrove conservation , invasion biology , and small-scale fisheries management . His work integrates ecological modelling with field studies to address sustainability challenges in tropical social-ecological systems, particularly examining how climate change and anthropogenic pressures affect coastal communities and biodiversity. Analysis of his recent publications reveals a consistent focus on mangrove ecosystems as critical nurseries supporting global fisheries, interoceanic species invasions through canals like Panama, and community-based conservation approaches . His research spans methodologies from environmental DNA analysis to AI-based habitat mapping, demonstrating interdisciplinary innovation in marine science. Dr. Castellanos-Galindo actively contributes to international conservation initiatives including the STRONG High Seas project, where he co-authored reports on biodiversity beyond national jurisdiction in the Southeast Pacific. His work bridges scientific research with policy-relevant applications for marine resource management. His laboratory and field research primarily operates in the Tropical Eastern Pacific, with significant work in Colombia and Panama, focusing on mangrove forests, coral reefs, and associated fisheries. Current projects examine Panama Canal-mediated species invasions and sustainable management frameworks for small-scale fisheries.

Véronique Helferمشاهده پروفایل

پژوهشگر

• Mangrove Ecology
• Environmental Change
• Species Distribution Modelling
• +۸ مورد دیگر

Véronique Helfer is a Senior Scientist at the Leibniz Center for Tropical Marine Research (ZMT) GmbH, working in Programme Area 4 – Ecosystem Co-Design towards a sustainable Anthropocene and the Working Group Mangrove Ecology. Her research focuses on mangrove ecosystems, their protection, restoration, and resilience to global change. Using interdisciplinary approaches, she investigates factors driving microbial, faunal, and floral community composition in mangroves and how these translate into ecosystem services. Her work spans molecular biology (eDNA metabarcoding, landscape genetics), chemical ecology, functional ecology, and species distribution modeling. Recent publications highlight her expertise in mangrove canopy gaps, Blue Carbon verification frameworks, and interdisciplinary research. She has contributed to stakeholder initiatives like the sea4soCiety project and the Floating Mangroves energy solutions publication. Her educational background includes a 2010 PhD in Conservation Genetics from the University of Lausanne (supervised by Fumagalli L), with prior educational brochures on evolutionary biology and alpine ecosystems.

• Database Systems
• High-Performance Storage Engines
• Concurrency Control
• +۳ مورد دیگر

Adnan Alhomssi is a researcher specializing in database systems and high-performance storage engines, affiliated with the University of Erlangen-Nuremberg, Germany. His work focuses on optimizing database performance through innovative approaches to concurrency control, transaction processing, and storage management. PhD in Computer Science from University of Erlangen-Nuremberg (2024) Specializes in high-performance database systems Active researcher with publications in top-tier database venues including SIGMOD, VLDB, and CIDR Alhomssi's research interests center around database systems optimization, particularly in the areas of concurrency control, high-performance storage engines, and transaction processing. His work addresses fundamental challenges in database management systems, with a focus on improving throughput, latency, and robustness in modern storage environments. He has made significant contributions to understanding and optimizing B-tree structures, snapshot isolation techniques, and buffer management strategies. His research bridges theoretical database concepts with practical implementation concerns, particularly for NVMe SSD storage technologies. Analysis of Alhomssi's publications reveals a clear progression from foundational database concepts to cutting-edge storage optimization. His early work focused on B-tree structures and index management, while more recent publications tackle the challenges of modern storage hardware like NVMe SSDs. His research shows consistent emphasis on balancing theoretical rigor with practical performance considerations, particularly in transaction processing and concurrency control. The recurring collaboration with Viktor Leis across multiple publications suggests a strong research partnership focused on advancing database storage engine technology. Alhomssi has published extensively in premier database conferences and journals including: Proceedings of the ACM on Management of Data (Proc. ACM Manag. Data) Proceedings of the VLDB Endowment (Proc. VLDB Endow.) Conference on Innovative Data Systems Research (CIDR) Bachelor's and Master's Thesis Workshop (BTW) His research demonstrates strong collaboration with colleagues across multiple institutions, particularly evident in his work with Viktor Leis, Tobias Ziegler, and other researchers at what appears to be the University of Erlangen-Nuremberg database group. While specific grant information isn't provided in the available data, his publication pattern suggests involvement in research projects focused on database systems and storage technologies. Alhomssi's work appears to be associated with a database research group that has developed the LeanStore database system, as evidenced by his publication on 'The Evolution of LeanStore.'