جست‌وجوی استاد و پژوهشگر

Chengnian Sunمشاهده پروفایل

دانشیار

• Software Engineering
• Programming Languages
• Compiler Testing
• +۴ مورد دیگر

Chengnian Sun is an Associate Professor at the Cheriton School of Computer Science , University of Waterloo, Canada. His research focuses on software engineering and programming languages with an emphasis on software reliability and programming productivity. Education : Ph.D. in Computer Science from National University of Singapore (2013) His work spans compiler testing (EMI, Dfusor, Kitten), program reduction (Perses, Vulcan, PPR), Android testing, and DNN testing. He has received multiple grants including Google Research Scholar Program (2025) and NSERC Discovery Grants (2024-2029). His recent publications focus on LLM-based compiler testing, weighted delta debugging, and ransomware resilience. Scientific Awards : Most Influential Paper Award at SANER (2022) NUS Research Scholarship (2008-2012) ACM SIGSOFT Distinguished Paper Award at ASE (2012) IBM Cup Campus Innovation Contest First Prize (2005) He advises Ph.D. and MMath students in software engineering, compiler testing, and program analysis, including several who have contributed to top-tier conferences like ICSE, ISSTA, and ASPLOS. His service includes program committee roles in ICSE, OOPSLA, and ISSTA.

Olaf Spinczykمشاهده پروفایل

استاد

• Embedded Systems
• Aspect-Oriented Programming
• Operating Systems
• +۳ مورد دیگر

Olaf Spinczyk is a Professor in the Department of Computer Science 12 at Technische Universität Dortmund, leading the Embedded System Software Group. Previously, he held positions at Friedrich-Alexander-Universität Erlangen-Nürnberg and the University of Magdeburg. His research focuses on embedded systems, aspect-oriented programming, and operating system design. Affiliations: Technische Universität Dortmund: Head of Embedded System Software Group Former roles: University of Erlangen-Nürnberg (Dept. of Computer Science 4) and Magdeburg University Research Interests Spinczyk specializes in tailor-made operating systems , embedded systems , and aspect-oriented programming . His work emphasizes software product lines for embedded environments, fault tolerance, and energy-efficient system design. Key projects include: CiAO: Aspect-oriented OS product line AspectC++: AOP extension for C++ FAME-DBMS: Database management system family FAIL*: Fault-injection framework Recent Work Recent research explores energy-aware device drivers, cyber-physical system reliability, and virtualization strategies for industrial applications. He has contributed to frameworks like vGridLab for smart grid testing and PhyNetLab for IoT-based warehouses. Awards & Activities No explicit awards listed, but notable contributions include leadership roles in EuroSys and conference organization (e.g., PLOS workshops, AOSD tutorials). Active in academic service, including program committees for AOSD and MMB. Labs & Teams Leads the Embedded System Software Group at TU Dortmund, collaborating on projects involving automotive systems, real-time computing, and cloud federation strategies.

• In-Memory Databases
• Data Stream Processing
• Database Systems
• +۱۲ مورد دیگر

Matthias Uflacker is a Professor at the Hasso Plattner Institute (HPI), University of Potsdam, Germany, where he conducts research in database systems, in-memory computing, and data-driven enterprise applications. His work bridges systems research and practical applications in Industry 4.0, education, and bioinformatics. University: University of Potsdam School: Hasso Plattner Institute Department: Department of Digital Engineering Research Focus: In-Memory Databases, Stream Processing, Causal AI, and Database Education His research interests span in-memory database systems , real-time data stream processing , GPU-accelerated analytics , and causal structure learning . He also contributes to computer science education , particularly in agile software engineering and interactive learning tools for K-12. The recent publications reflect a strong trend in enterprise data management , with a focus on benchmarking (e.g., ESPBench), performance optimization (e.g., Kafka, Hyrise), and intelligent decision support using causal models in industrial contexts. His work increasingly integrates AI for monitoring and automation in manufacturing and e-commerce. He has co-authored numerous publications in top-tier venues such as VLDB, ICDE, EDBT, and KDD, often in collaboration with Hasso Plattner and other HPI researchers. Matthias Uflacker leads and contributes to research projects on autonomous database systems , dynamic pricing simulations , and educational technology platforms for programming exercises. His team develops tools for real-time data integration, causal analysis, and classroom software engineering assessment.

Jan Hiddersمشاهده پروفایل

مدرس

• Graph Data Management
• Workflow Modelling
• Conceptual Data Models
• +۲ مورد دیگر

Jan Hidders is a Lecturer in the School of Computing and Mathematical Sciences at Birkbeck, University of London. He joined Birkbeck in 2020 after holding academic positions at Vrije Universiteit Brussel (Associate Professor, 2016–2020), Delft University of Technology (Assistant Professor, 2008–2016), and the University of Antwerp (Postdoctoral Researcher, 2001–2008). He holds a PhD from Eindhoven University of Technology (2001) and has industry teaching experience at Avans Hogeschool (1996–2001). Research Focus Hidders' research centers on three interconnected domains: Graph Data Management : Design of graph query languages, schema definition systems (PG-Schema), and theoretical properties like expressive power and optimization. He contributes to ISO standardization for SQL/GQL graph extensions. Workflow Modelling : Hierarchical decomposition of Petri nets for workflow correctness verification and orchestration of multi-actor systems. Conceptual Data Models : Formal semantics of ORM2 and its relationship to graph data models, including ORM-native DBMS design. His recent publications emphasize graph database schemas , threshold query optimization , and scalable data processing , reflecting his involvement in LDBC benchmarks and ISO standards. No awards are documented. Academic Roles Programme Director for MSc Computer Science at Birkbeck. Researcher at Birkbeck Knowledge Lab and Birkbeck Institute for Data Analytics. ACM and IEEE member since 2003 and 2006, respectively. He teaches Software Engineering II and Computer Systems , with 1 recorded PhD supervision.

Konstantin Pavlikovمشاهده پروفایل

دانشیار

• Operations Research
• Stochastic Programming
• Integer Programming
• +۳ مورد دیگر

Konstantin Pavlikov is an Associate Professor at the Department of Business & Management (DBM) under Strategic Organization Design (SOD) at the University of Southern Denmark. His research focuses on Operations Research, Integer Programming, and Stochastic Programming , with particular emphasis on vehicle routing optimization and network flow modeling. Education : PhD in Operations Research (University of Florida, 2014), MSc in Applied Mathematics (Moscow State University, 2007) His work spans combinatorial optimization and network interdiction problems , developing exact and approximate solution algorithms for complex logistics challenges. Recent publications analyze heterogeneous vehicle routing capacity inequalities and two-commodity flow formulations for routing problems. Scientific contributions have been recognized with the Best Reviewer Award (2019). He actively reviews for journals like Computational Management Science and supervises academic works through examination roles.

Sandro Luigi Fioreمشاهده پروفایل

دانشیار

• Data Science
• Big Data
• Scientific Data Management
• +۱۳ مورد دیگر

Sandro Luigi Fiore is an Associate Professor in the Department of Information Engineering and Computer Science at the University of Trento, Italy. He has held academic positions at the University of Salento and visiting scientist roles at the University of Chicago and Lawrence Livermore National Laboratory. His research integrates data science, big data, and high-performance computing with climate informatics and open science. Education: Ph.D. in Innovative Materials and Technologies, University of Lecce, 2004 Master of Science in Computer Engineering (with honors), University of Lecce, 2001 His research interests span Data Science, Big Data, Scientific Data Management, Artificial Intelligence, and Distributed/Cloud/Parallel Computing , with a strong application focus on Climate Change and Open Science . He develops FAIR-enabled data analytics solutions and contributes to large-scale data infrastructures such as ESGF, EOSC-hub, and INDIGO-DataCloud. His work emphasizes provenance, reproducibility, and interoperability in scientific computing. The articles reflect a consistent trajectory in large-scale scientific data systems , evolving from Grid-DBMS and parallel computing to modern applications in climate informatics, AI, and FAIR data. Key themes include distributed data management, middleware, exascale software, and reproducible workflows in HPC environments. Scientific Awards: Earth System Grid Federation Team Award (2017) UNIDATA Community Equipment Award (2011) Best Student Paper Award, ITCC2003 Fiore has advised on and led multiple national and European projects including EOSC-hub, IS-ENES, and BARRACUDA (RDA-Europe3). He actively supports the adoption of FAIR data principles in scientific repositories, advising on data policies, architecture, provenance, and interoperability. He is a member of the FAIR Champions group and serves on the Advisory Board of FAIRsFAIR. He is involved in key research teams and projects such as the Earth System Grid Federation (ESGF) , Globus Lab (University of Chicago) , and PCMDI/LLNL . His work contributes to climate model intercomparison (CMIP5/6) and the development of next-generation data infrastructure for open science.

Thanaa Ghanemمشاهده پروفایل

دانشیار

• Data Science
• Database Systems
• Social Media Analysis
• +۴ مورد دیگر

Thanaa Ghanem is an Associate Professor in the Department of Computer Science and Cybersecurity at Metropolitan State University's College of Engineering. With a PhD from Purdue University (2014), she has held academic positions at Umm Al-Qura University (Assistant Professor, 2013-2014) and Qatar Computing Research Institute (Scientist, 2017-2018). Her research focuses on data science, social media analytics, spatio-temporal data processing, and geotagged microblog analysis. Education includes: PhD, Computer Science, Purdue University, West Lafayette MS, Computer Science, Purdue University, West Lafayette BS, Computer Science, Alexandria University, Egypt Research interests emphasize: Social network analysis for health communication Big data query language pedagogy Geotagged microblog visualization systems (Taghreed/VisCAT) Language diversity mapping in social media Spatio-temporal data processing Cloud DBMS architectures and tradeoffs Her recent publications demonstrate expertise in social media epidemiology, data visualization, and database systems. She has also contributed to educational curriculum design in data science. Scientific awards: No specific awards mentioned in available data

Il-Yeol Songمشاهده پروفایل

استاد

• Data Science
• Conceptual Modeling
• Big Data Analytics
• +۴ مورد دیگر

Il-Yeol Song is a Professor of Information Science at Drexel University's College of Computing & Informatics (CCI). His research focuses on modeling & design theory applications, particularly in conceptual modeling , data warehousing , big data analytics , UML , healthcare informatics , and smart health . PhD, Computer Science, Louisiana State University (1988) MS, Systems Sciences, Louisiana State University (1984) BS, Nuclear Engineering, Han-Yang University, Seoul, Korea (1975) Song has contributed extensively to data science and big data, with over 25 years of research in DOLAP (Data Warehousing and OLAP) and DaWaK (Big Data and Knowledge Discovery). His work bridges database systems with healthcare applications and educational standards modeling. Recent publications analyze the evolution of data & knowledge engineering and trends in big data research. He has co-edited proceedings for conferences like DaWaK 2019 and DOLAP 2020 , reflecting his leadership in data science. ACM Distinguished Scientist Recipient of the 2001 Christian R. and Mary Lindback Distinguished Teaching Award Song serves on editorial and conference committees, advancing database education through workshops and curriculum development. His email is song@drexel.edu , and his research is available at cci.drexel.edu/faculty/song .

Wendy Powleyمشاهده پروفایل

دانشیار

• Database Management Systems
• Autonomic Computing
• Cloud Computing
• +۳ مورد دیگر

Wendy Powley is an Associate Professor at Queen’s University’s School of Computing within the Faculty of Arts and Science. She holds a B.A. in Psychology (1984), B.Ed. in Primary Junior Education (1985), and M.Sc. in Computer Science (1990), all from Queen’s University. Her research focuses on database systems, autonomic computing, workload management, and cloud computing. She co-founded the Women in the School of Computing (WISC) group and pioneered the Ontario Celebration of Women in Computing, promoting gender equity in computing education and careers. Education History: B.A., Psychology, Queen’s University (1984) B.Ed., Primary Junior Education, Queen’s University (1985) M.Sc., Computer Science, Queen’s University (1990) Research Interests: Database Management Systems (DBMS) Autonomic Computing and Self-Managing Systems Workload Control and Resource Management Policy-Based Management for Complex Systems Cloud Computing and QoS-aware Applications Publications reflect expertise in DBMS performance optimization, autonomic frameworks, and workload adaptation strategies. Her work has been published in leading conferences/journals since 1993. Scientific Awards: Queen’s University Equity Award (for advancing gender equity in computing) Professional Contributions: First-year course and internship program coordinator at Queen’s School of Computing Co-chair of ACM-W (Association for Computing Machinery-Women in Computing) Organized CAN-CWiC (Canadian Celebration of Women in Computing) events Labs/Teams: Active member of the Database Systems Lab (DSL) led by Dr. Pat Martin (1992–2016). Currently involved in ACM-W initiatives promoting women in computing globally.

• Model-Driven Engineering
• Computer Science
• Artificial Intelligence
• +۷ مورد دیگر

Moussa Amrani is a researcher with expertise in Model-Driven Engineering , Artificial Intelligence , and Database Performance Testing . His work contributes to the United Nations Sustainable Development Goals, particularly in advancing technological innovation and systems modeling. He collaborates with scholars like P.-Y. Schobbens and participates in projects such as CoTu: Erasmus+ICM for Higher Education Mobility and THCS: Testing Highly-configurable Systems . His research interests span Model Federation , UAV Coordination , and Machine Learning Applications in Databases . Recent publications highlight trends in federative model management, autonomous drone control in dynamic environments, and enhancing reproducibility in database testing. These works reflect interdisciplinary efforts bridging Computer Science , Cyber-Physical Systems , and Software Engineering . Collaborations : Active in international research groups (e.g., VeriLearn, MPM4CPS) with focus on AI verification and model-driven approaches. Research Themes : Model transformations, configurability in systems, and real-time coordination mechanisms.

• Cloud Computing
• Distributed Systems
• High-Performance Computing
• +۵ مورد دیگر

Raja Appuswamy is an Assistant Professor in the Department of Data Science at EURECOM, focusing on data management on modern hardware and molecular information storage. His research integrates cutting-edge storage technologies with bioinformatics, particularly in DNA-based data storage. He teaches courses in cloud computing, distributed systems, and databases. His work spans Optimizing storage hierarchies with DNA archival systems Hardware-conscious algorithms for GPUs and heterogeneous architectures Error correction in molecular storage Long-term database preservation strategies Key research interests include Cross-architecture data joins (e.g., OneJoin, XJoin) Cold storage innovation with CMOSS and OligoArchive Integration of bio-inspired storage with traditional computing and explores interdisciplinary challenges at the intersection of computer science and molecular biology. Publications emphasize scalable solutions for DNA storage density, error tolerance, and archival systems. Awards highlight contributions to DNA-based image encoding, storage reliability, and page cache checksums. Current projects focus on enzymatic DNA ligations for storage density improvement, motif-based error correction, and hardware acceleration for knowledge graphs. His work targets both theoretical advancements and practical implementations in storage systems.

• Database Systems
• Distributed Computing
• Machine Learning
• +۳ مورد دیگر

Carsten Binnig is a researcher affiliated with TU Darmstadt, Germany, focusing on database systems, distributed computing, and machine learning integration. His work spans high-performance data management, query optimization, and hardware-software co-design for modern networks. He holds a PhD from Heidelberg University (2008) and has contributed extensively to conferences like SIGMOD, VLDB, and CIDR. His research emphasizes scalable OLTP/OLAP systems, secure cloud DBMSs, and leveraging GPUs/accelerators for database operations. Notable projects include GOLAP (GPU-accelerated OLAP), ScaleStore (storage engine using NVMe/RDMA), and DBMS Annihilator (workload generator). He co-leads initiatives on testing database systems (DBTest workshop) and benchmarks for shared databases.

• Geospatial Data Management
• Database Systems
• Cluster Computing
• +۵ مورد دیگر

Jia Yu is a researcher affiliated with Arizona State University , Tempe, AZ, USA. Their work focuses on geospatial data management, database systems, and cluster computing frameworks like Apache Spark. They have collaborated extensively with Mohamed Sarwat and other researchers on projects such as GeoSpark , GeoSparkViz , and GeoSparkSim , contributing to scalable spatial data processing and visualization systems. Key research areas include Learned indexing mechanisms (e.g., GLIN) Microscopic traffic simulation Parallel and distributed data processing Interactive geospatial dashboards Column correlation exploitation for database efficiency Integration of visualization with backend data systems Recent publications (2014-2024) demonstrate expertise in geospatial analytics, database indexing, software testing, and Apache Spark-based systems. Notable projects include Turbocharging Visualization Dashboards , HERMIT Indexing , and Spindra Knowledge Graph Management . Work emphasizes both theoretical innovation and practical implementation for handling massive-scale spatial data.

Albert Crokerمشاهده پروفایل

استاد

• Database Management Systems
• Relational Database Theory
• Temporal Database Theory
• +۳ مورد دیگر

Albert Croker is a Professor in the Paul H. Chook Department of Information Systems and Statistics at Baruch College's Zicklin School of Business. With a PhD in Computer Science from SUNY Stony Brook (1984), he specializes in database systems and object-oriented programming. BS in Mathematics (SUNY Stony Brook, 1972) MS in Computer Science (SUNY Stony Brook, 1978) PhD in Computer Science (SUNY Stony Brook, 1984) His research focuses on database management systems , particularly relational database theory , temporal database theory , and object-oriented programming applications. He has developed innovative approaches to constraint satisfaction problems and temporal data representation. Professor Croker's publications highlight his expertise in temporal databases and object-oriented programming . His work explores time-variant data modeling, constraint satisfaction frameworks, and concurrency control mechanisms. Scientific Awards: Zicklin School of Business Teaching Excellence Award (1997) Golden Key National Honor Society Honorary Member (1997) He serves as Course Coordinator for multiple CIS courses including 9310/9410, 3100/4100, and 3650/9365, while maintaining active roles in curriculum development and faculty recruitment.

• Database Systems
• Cloud Applications Architecture
• Temporal Data Modeling
• +۲ مورد دیگر

Lecturer Dr. Horea Adrian Grebla is affiliated with the Department of Computer Science at Babeș-Bolyai University, Faculty of Mathematics and Computer Science. He teaches courses including Cloud Applications Architecture , Advanced Database Chapters , and Data Collection and Modeling for master's programs in computer science. His instructional responsibilities include both lectures and labs, with grading components combining quizzes, projects, and exams. He utilizes platforms like PostgreSQL and Oracle for database-related coursework. Research interests include: Temporal data modeling and implementation Database schema design for cloud applications Advanced database operations (CRUD with history tracking) Historical data analysis and reporting Database transaction management Temporal attribute modeling in relational DBMS Courses emphasize practical implementations of temporal databases, with projects requiring: Design of entities with transaction/valid time attributes Scripting for data population and modification Complex temporal query operations Team-based project execution Contact: horea.grebla@ubbcluj.ro