جست‌وجوی استاد و پژوهشگر

Daniel N Jacksonمشاهده پروفایل

استاد

• Software Design and Specification
• Design Methods
• Tools and Analysis
• +۹ مورد دیگر

Prof. Daniel N. Jackson is a Professor of Electrical Engineering and Computer Science at MIT, serving as Associate Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and Director of the Middle East Education Through Technology (MISTI MIT-MEET) initiative. His research focuses on software dependability, formal methods, and design analysis, particularly through the Alloy framework. Jackson emphasizes lightweight formal methods to reduce development costs and enhance software safety, with applications in cybersecurity, autonomous systems, and safety-critical software. His work includes developing tools like Bluefish for declarative diagram composition and Riffle for reactive systems. He explores ethical software design frameworks to address dark patterns and advocates for concept-centric development. Jackson's contributions span academic publications, educational initiatives, and industrial collaborations, aiming to bridge formal methods with practical software engineering challenges. Recent projects involve certified control systems for autonomous vehicles, end-to-end dependability cases, and model checking for security flaws. His research integrates interdisciplinary approaches, combining programming languages, static analysis, and human-centered design principles.

• Information Retrieval
• Digital Libraries
• Informetrics
• +۵ مورد دیگر

Philipp Mayr-Schlegel is a Professor at the University of Göttingen’s Institute of Computer Science, leading the team 'Information & Data Retrieval' at GESIS - Leibniz-Institute for the Social Sciences. His research focuses on interactive information retrieval systems, scholarly recommendation mechanisms, and the integration of bibliometric methods with digital library technologies. University of Göttingen - Institute of Computer Science GESIS - Leibniz-Institute for the Social Sciences His work spans information retrieval , digital libraries , and applied informetrics , with particular emphasis on: Interactive search systems Non-textual ranking algorithms Scholarly document processing Knowledge representation Semantic search technologies User behavior analysis Recent research outputs (2025) include studies on LLMs for scholarly search, bibliometric reproducibility tools, scientific uncertainty annotation, and preprint adoption disparities. He has published extensively in Scientometrics , International Journal on Digital Libraries , and top conference proceedings like ACL and ECIR . As organizer of the International Workshop on Bibliometric-enhanced Information Retrieval (BIR) and Scholarly Document Processing (SDP) series, he has shaped academic discourse through editorial roles at ISSI , JCDL , and SocInfo conferences. His projects have attracted significant national and European funding.

• Data Mining
• Database Systems
• Spatial Databases
• +۵ مورد دیگر

Yubao Liu is a Professor at Sun Yat-sen University's School of Data and Computer Science, Department of Computer Science, with a prolific research career spanning over two decades in computer science. His work demonstrates significant contributions to database systems, data mining, and spatio-temporal analysis. Professor Liu's research interests focus on Data Mining , Database Systems , Traffic Flow Prediction , and Graph Neural Networks . His recent work has concentrated on developing advanced techniques for large-scale traffic flow prediction, crowd flow analysis, and spatio-temporal modeling using deep learning approaches. His research bridges theoretical computer science with practical applications in transportation systems and urban computing. Liu's publication record shows consistent high-impact contributions, with recent work emphasizing graph-based neural network architectures for traffic forecasting problems. His research demonstrates a clear evolution from foundational database work to cutting-edge applications of deep learning in transportation and social network analysis. Professor Liu has collaborated extensively with researchers including Weiyang Kong, Kaiqi Wu, Sen Zhang, Genan Dai, and Youming Ge, indicating a strong research group focused on spatio-temporal data analysis and deep learning applications. His academic advising is evident through publications where his students appear as first authors, suggesting an active mentorship role in training the next generation of computer scientists specializing in data-intensive applications.

• Database Systems
• Data Management
• Cloud Computing
• +۵ مورد دیگر

Abdelkader Hameurlain is an active academic researcher specializing in database systems, data management, and cloud computing with a prolific publication record spanning over three decades (1990-2025). He has authored or co-authored more than 170 publications and serves as an editor for the prestigious 'Transactions on Large-Scale Data- and Knowledge-Centered Systems' series published by Springer as part of the Lecture Notes in Computer Science. His research interests focus on database systems, data management, cloud computing, query optimization, data replication, and big data analytics. Hameurlain has made significant contributions to multi-tenant database management systems, SLA-aware query optimization, data replication strategies in cloud environments, and knowledge-based systems. His work bridges theoretical foundations with practical applications in large-scale data processing environments. Analysis of his recent publications (2021-2025) reveals a continued focus on cloud database performance optimization, with particular emphasis on multi-tenant systems, SLA compliance, and cost-effective resource allocation. His research demonstrates a consistent trajectory from traditional database systems toward cloud-native and distributed data management solutions, reflecting the evolving landscape of data-intensive computing. Hameurlain has established long-term collaborations with prominent researchers including Franck Morvan (63 joint publications), Roland R. Wagner (50 joint publications), Josef Küng (40 joint publications), and A Min Tjoa (26 joint publications), indicating his central position in the database research community. As an editor of the Transactions on Large-Scale Data- and Knowledge-Centered Systems series, he has played a significant role in shaping research directions in data management through numerous special issues covering database technologies, big data analytics, cloud computing, and knowledge systems. His editorial work spans multiple volumes from TLS-DCS XIII (2014) through TLS-DCS LVI (2024), demonstrating sustained leadership in the field.

• Database Systems
• Web Data Extraction
• Information Integration
• +۴ مورد دیگر

Jayant Madhavan is a researcher at Google specializing in database systems, web data extraction, and information integration. His work primarily focuses on extracting structured data from the web, schema matching, and developing techniques for managing and visualizing large datasets, particularly through projects like Google Fusion Tables and WebTables. Madhavan's research interests center around the challenges of working with web data. His work explores methods for extracting structured information from unstructured web content, particularly focusing on tables and lists. He has made significant contributions to the field of schema matching, developing techniques that enable integration of data from diverse sources. His research also extends to geospatial data processing and visualization, where he has developed algorithms for efficiently handling large geographical datasets for map visualization. His publication record shows a consistent focus on practical applications of database research to web-scale problems. The evolution of his work demonstrates a progression from foundational research on schema matching and data integration to applied work on Google products like Fusion Tables, which enable non-experts to work with structured data. His most recent work examines the ecosystem of structured data on the web and how to effectively extract and utilize this information. Madhavan has collaborated extensively with Alon Y. Halevy (43 co-authored papers) and other researchers at Google, forming a core group that has advanced the state of the art in web data management. His work bridges theoretical database research with practical applications, making significant contributions to both academic literature and real-world data management systems.

• Earthquake Engineering
• Seismic Hazard Analysis
• Structural Engineering
• +۲ مورد دیگر

Dr. Ebru Harmandar is an Associate Professor at the Department of Civil Engineering, Faculty of Engineering, Muğla Sıtkı Koçman University. She holds a Doctorate in Earthquake Engineering from Boğaziçi University (2009) and has contributed extensively to earthquake hazard assessment, structural response analysis, and ground motion modeling. Her research focuses on seismic resilience, spatial coherency of ground motions, and infrastructure risk mitigation. Key research areas: Earthquake Engineering, Seismic Hazard Analysis, Structural Engineering Major projects: EMME ground-motion logic tree, Istanbul Rapid Response Network Notable students: Soukaina Mellouk (2021), Hüssam-Almukdad (2022) Her recent work includes improving seismic resilience indices for school buildings (2024) and analyzing multi-point earthquake effects on bridges. She has served as an academic editor for journals like Soil Dynamics and Earthquake Engineering and received the 2016 Yollar Türk Milli Komitesi award.

Angela Demke Brownمشاهده پروفایل

استاد

• Operating Systems
• Programming Languages
• Distributed Systems
• +۷ مورد دیگر

Angela Demke Brown is a Full Professor in the Department of Computer Science at the University of Toronto. She is cross-appointed to the Faculty of Applied Science and Engineering. Her research focuses on the intersection of programming languages and operating systems, leveraging high-level analysis to enhance low-level systems software performance and reliability. Education : B.Sc., York University M.Sc., University of Toronto Ph.D., Carnegie Mellon University (2005), supervised by Todd Mowry Her research spans critical areas including file system reliability, dynamic binary instrumentation for Linux, spatial database performance, and compiler optimization techniques. She has spearheaded projects like compiler-based memory management, I/O prefetching strategies, and non-volatile memory file systems such as NOVA-Fortis. Her work also extends to distributed systems and non-volatile memory management. Scientific Awards and Recognitions : Carnegie Mellon Doctoral Dissertation Award (PhD thesis) IBM Faculty Fellowship (2004-2007) IBM Centre for Advanced Studies Team of the Year (2005) NetApp Faculty Fellowship Microsoft Research Visiting Researcher (2015-16) Teaching Award, Computer Science Students Union (2008) Active member of ACM, IEEE, and USENIX Professor Demke Brown has supervised numerous graduate students across PhD, Master’s, and undergraduate levels, often in collaboration with Prof. Ashvin Goel. Her professional service includes roles on program committees for conferences like USENIX ATC, ASPLOS, and NSERC scholarship evaluations.

Kalogeraki Vanaمشاهده پروفایل

استاد

• Distributed Systems
• Real-Time Systems
• Big Data Systems
• +۸ مورد دیگر

Prof. Vana Kalogeraki is a Faculty Member at the Department of Informatics , Athens University of Economics and Business (AUEB) , and serves as the Dean of the School of Information Sciences and Technology and Director of the Computer Systems and Communications Laboratory . She has held academic positions at the University of California, Riverside and was a Research Scientist at Hewlett-Packard Labs . PhD: University of California, Santa Barbara M.S. & B.S.: University of Crete, Greece Her research focuses on Distributed and Real-Time Systems , Big Data Systems , Cloud Computing , Human-Centered Systems , and Crowdsourcing . She has published over 200 papers at top journals (IEEE TPDS, ACM TOS, etc.) and conferences (RTSS, DSN, ICDCS, VLDB, MDM), including co-authoring the OMG CORBA Dynamic Scheduling Standard . Her 2023-2025 publications address AI pipelines in serverless environments, edge computing for trauma detection via eye-tracking, and fairness in resource scheduling. She has received prestigious awards including an ERC Starting Grant , Best Paper Awards (DEBS 2017, IPDPS 2009), a Best Poster Award (EuroSys 2024), and multiple UC Research Awards . Her research is funded by the European Union (ARISTEIA, THALIS), NSF, and industry partners like SUN and Nokia. Advising Legacy : Supervised 10 PhD graduates (now at Google, Amazon, IBM, Apple) and over 60 MS/PhD committees Labs & Teams : Leads the Computer Systems and Communications Laboratory at AUEB, focusing on mobile human-centered systems and urban data analytics

Dariusz Królمشاهده پروفایل

استاد

• Knowledge Engineering
• Multi-agent Systems
• Data Quality
• +۵ مورد دیگر

Dariusz Król is a Professor at the Department of Applied Computer Science, Faculty of Computer Science and Telecommunications at Wrocław University of Science and Technology. He serves as Vice-dean for general matters and Head of the Knowledge Engineering Lab. With a strong background in technical and engineering sciences, his academic career spans over two decades of teaching and research in computer science and telecommunications. Professor Król's educational background, though not explicitly detailed in the provided texts, is evidenced by his habilitation (dr hab. inż.) and professorship at one of Poland's leading technical universities. His extensive experience is reflected in his long-standing teaching career and research leadership. Professor Król's research interests focus on knowledge engineering, multi-agent systems, data quality, and intelligent production. His scholarly output shows a progression from foundational work in multi-agent systems to contemporary applications of deep learning in industrial contexts. Recent publications demonstrate increasing emphasis on practical applications of data quality assessment in production environments, with strong connections to Industry 4.0 and intelligent manufacturing concepts. His work consistently bridges theoretical foundations with real-world industrial applications where data quality and intelligent systems play crucial roles. His scholarly impact is evidenced by his edited books ranking among Springer's top downloaded publications, with two titles placing in the top 25% most downloaded books in 2018. His editorial leadership extends to serving as editor for Computational Intelligence (Wiley-Blackwell) since 2008 and International Journal of Distributed Systems and Technologies since 2010. Book 'Advanced Topics in Intelligent Information and Database Systems' among top 25% most downloaded Springer books in 2018 (31,481 downloads) Book 'Recent Developments in Intelligent Information and Database Systems' among top 25% most downloaded Springer books in 2018 (24,896 downloads) Book 'Propagation Phenomena in Real World Networks' among top 50% most downloaded Springer books in 2015-2016 Professor Król has supervised over 50 Master's and Engineering theses across diverse topics in computer science. He teaches courses ranging from foundational programming to advanced topics in knowledge engineering, maintaining an active teaching schedule for over 18 academic years. He leads the KNJavaTech scientific circle, which has provided research opportunities for students since 2005. His international collaborations include invited seminars at prestigious institutions worldwide, demonstrating global recognition of his expertise in knowledge engineering and intelligent systems.

• Database Systems
• Integration of heterogeneous databases
• Data quality and data integrity
• +۶ مورد دیگر

Thomas Kudraß serves as Professor for Database Systems at the Faculty of Computer Science, Mathematics and Natural Sciences (IMN) at Leipzig University of Applied Sciences (HTWK Leipzig). With over 25 years of academic and industry experience, he teaches courses including Database Basics, Database Application Programming, Data Warehousing, and Big Data Technologies. His leadership roles include Internship Coordinator for Computer Science since 2001, Member of the Academic Senate since 2011, and Contact person for the IMN faculty alumni association since 2005. Dr. Kudraß earned his Dipl.-Ing. in Computer Science from Technical University of Dresden (1985-1990) and completed his doctorate at Darmstadt University of Technology (1992-1997), where his dissertation received the prestigious Jos Schepens Memorial Award. Prior to academia, he worked as an Information Systems Architect at UBS AG Zurich and Database Specialist at Swiss Bank Corporation Basel. His research spans database technologies with focus on heterogeneous database integration, data quality, data privacy, and modern database concepts. Recent work explores cloud-native billing applications for 5G, NoSQL databases, and privacy-preserving record linkage techniques. His publication record shows continuous evolution from traditional database systems to contemporary challenges in big data and distributed systems. Jos Schepens Memorial Award for doctoral dissertation (1997) Active participation in German Informatics Society (GI) specialist groups Organizer of multiple database-related workshops and conferences Professor Kudraß has significantly contributed to academic governance as E-Learning Officer (2000-02), Faculty Council member (2009-12), and liaison lecturer for the German Society for Computer Science (2001-14). He has coordinated numerous student projects and served on program committees for major conferences including INFORMATIK 2017 and BTW series.

Manuel Schechtlمشاهده پروفایل

استادیار

• Tax Policy
• Social Policy
• Wealth Inequality
• +۶ مورد دیگر

Manuel Schechtl is an Assistant Professor of Public Policy at the University of North Carolina at Chapel Hill , with affiliations at the Carolina Population Center and Yale's Center for Empirical Research on Stratification and Inequality. As a sociologist, his work bridges tax policy, social policy, and economic inequality, focusing on how fiscal institutions shape wealth distribution and mobility. PhD, Humboldt University Berlin (2022) Postdoc, Stone Center on Socio-Economic Inequality (CUNY, 2022–2024) Research Focus: • Wealth inequality dynamics and intergenerational mobility • Inheritance/gift taxation as mobility determinant • Gender disparities in asset transfers • Municipal policy impacts on racial inequality • Comparative fiscal impoverishment analysis Recent Article Trends: His 15 most recent publications (2021–2025) span wealth inequality, gendered tax effects, place-based policy impacts, and democratic backsliding. Key themes include taxation's role in inequality reproduction, spatial mobility patterns, and policy feedback mechanisms. Scientific Recognition: University of Michigan Stone Center Visiting Fellowship (2025–2026) Collaborative projects with leading inequality centers Contributions: Co-developed wealth-transfer gender gap analysis, advanced fiscal federalism frameworks, and led place-based mortality studies. Currently exploring municipal police impacts on racial mobility gaps and GEOWEALTH-US data applications.

Dimitrios Tsoumakosمشاهده پروفایل

دانشیار

• Big Data Management
• Distributed Systems
• Cloud Computing
• +۵ مورد دیگر

Dimitrios Tsoumakos serves as an Associate Professor of Big Data Management Systems at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) where he also directs DBLab, the Knowledge and Database Systems Laboratory. His academic career spans over two decades with significant contributions to large-scale data management and distributed systems. Diploma in Electrical and Computer Engineering from NTUA (1999) M.Sc. in Computer Sciences from University of Maryland (2002) Ph.D. in Computer Sciences from University of Maryland (2006) Professor Tsoumakos' research focuses on the intersection of big data management, cloud computing, and distributed systems. His work addresses fundamental challenges in large-scale data processing, including wavelet synopses for data summarization, vector embedding frameworks for analytics operators, multi-engine analytics systems, and cloud application deployment with failure recovery mechanisms. His research consistently bridges theoretical algorithms with practical implementations for real-world data challenges. His publication record demonstrates consistent innovation from early work on P2P data management systems through to current research on vector embeddings and deep reinforcement learning for cloud autoscaling. Recent work shows a clear progression toward content-based analytics, multi-dataset integration, and intelligent resource management in heterogeneous environments. Best Paper Runner Up Award at SSDBM 2019 Best Paper Award at CCGrid 2013 Professor Tsoumakos has secured substantial research funding through multiple European projects including RELAX (2023-2027), HiDALGO2 (2023-2026), DAPHNE (2021-2024), and previous initiatives like HiDALGO, TraMOOC, ASAP, CELAR, ARCOMEM, and GREDIA. These projects reflect his leadership in big data analytics, cloud computing, and distributed systems research. As director of DBLab, Professor Tsoumakos oversees research on the Knowledge and Database Systems Laboratory, which has produced significant work on analytics operators, multi-engine resource scheduling (IReS platform), cloud elasticity (TIRAMOLA), and RDF data management (H2RDF+). The lab maintains strong industry connections and has developed multiple open-source tools for big data analytics.

• Applied cryptography
• Cryptographic protocols
• Network security
• +۵ مورد دیگر

Dr. Ji Sun Shin is a Professor in the Department of Computer and Information Security at Sejong University, where she has been faculty since 2012. Her research bridges theoretical cryptography with practical security applications across multiple domains including IoT, smart devices, and critical infrastructure systems. Education: Ph.D. in Computer Science, University of Maryland at College Park (2009) B.S. in Computer Engineering, Seoul National University (2001) Professor Shin's research focuses on applied cryptography and network security with particular expertise in authentication systems. Her work spans password-based key exchanges , keystroke dynamics authentication , privacy-preserving protocols , and IoT security . She has made significant contributions to provably secure cryptographic protocols including HB/HB+ protocols, forward-secure identity-based signatures, and functional signatures. Her research addresses both theoretical foundations and real-world implementation challenges in cryptographic systems. Analysis of her recent publications reveals a strong trend toward privacy-preserving techniques in distributed systems, with significant work in federated learning security, blockchain applications for IoT, and efficient cryptographic implementations. Her research demonstrates consistent evolution from theoretical cryptography toward practical security solutions for emerging technologies like smart grids, drone systems, and smartphone authentication. Research Leadership: Principal Investigator of the Information Security Lab at Sejong University Active research collaboration across multiple domains including smart cities, healthcare systems, and critical infrastructure security Extensive patent portfolio with numerous domestic and international patents related to location verification, blockchain security, and authentication systems Professor Shin's laboratory focuses on practical security implementations with research areas spanning smartphone security, short-range communication protocols, IoT authentication mechanisms, and smart car security systems. Her team develops fundamental security technologies that address both theoretical security guarantees and real-world usability constraints.

• Cloud-native data systems
• Secure cloud databases
• Distributed systems
• +۳ مورد دیگر

Dr. Muhammad El-Hindi is a Postdoctoral Researcher at the Chair of Decentralized Information Systems and Data Management at the Technical University of Munich . He joined the chair in August 2025 and focuses on cloud-native data systems, distributed systems, and formal verification of distributed protocols. His work emphasizes designing high-performance, cost-efficient services like write-ahead logging and distributed page servers, aiming to enhance reliability and security in large-scale systems. Research Interests: Cloud-native data systems, secure cloud databases, distributed systems, formal verification of protocols Teaching: Cloud Information Systems, Data Structure Engineering, Blockchain Technologies, Federated Learning, Distributed Graph Processing Email: muhammad.el-hindi@tum.de His recent publications explore kernel-bypass optimization, AWS Nitro Enclaves, Intel SGX hardware, and blockchain-based shared databases. While no scientific awards are explicitly mentioned in the available data, his work contributes to advancing secure and efficient data management in cloud environments.

Andreas Pavlogiannisمشاهده پروفایل

دانشیار

• formal methods
• algorithmic verification
• automata theory
• +۶ مورد دیگر

Andreas Pavlogiannis is an Associate Professor in the Department of Computer Science at Aarhus University. His research focuses on formal methods , algorithmic verification , automata theory , concurrency , static and dynamic program analysis , network diffusion , evolutionary graph theory , and evolutionary game theory . Teaching courses: Programming Languages (Bachelor) , Algorithmic Model Checking (Master) , and Program Analysis (Master) Service: Program committee member for POPL, ESOP, AAAI, IJCAI, CONCUR, OOPSLA, and organizer of CONFEST'25 His research has been supported by the Austrian Science Fund (FWF), VILLUM Foundation, Stibo Foundation, and Danish Council for Independent Research (DFF). He is actively recruiting PhD and PostDoc researchers. Recent publications span quantum computing , concurrent systems , evolutionary dynamics , and network science , with particular emphasis on symbolic algorithms , dynamic analysis , and graph-based models .