جستجوی استاد راهنمای دانشگاهی

Vincent Danjeanمشاهده پروفایل

دانشیار

• Parallel Computing
• High-Performance Computing
• Task-Based Parallelism
• +۶ مورد دیگر

Vincent Danjean is an associate professor at Grenoble Alpes University , specializing in parallel computing, high-performance computing, and bioinformatics. He earned his PhD in 2004 from École Normale Supérieure de Lyon under the supervision of Raymond Namyst. Research Interests: Vincent's work spans several critical areas in computational science: Parallel and Distributed Systems: Focus on task-based parallelism and hybrid cluster architectures. Performance Analysis: Development of visual frameworks for analyzing parallel applications. Bioinformatics: Application of computational methods to genetic and genomic data analysis. GPU Computing: Efficient scheduling and work stealing strategies for multi-GPU systems. Reproducible Research: Workflows using Git and Org-mode for scientific transparency. Publication Trends: His publications demonstrate a consistent focus on advancing parallel computing techniques, with significant contributions to GPU scheduling, cache-efficient algorithms, and visualization tools. Recent work includes interdisciplinary applications in genomics and cybersecurity protocols. Contact: vincent.danjean@imag.fr

Ilia Petrovمشاهده پروفایل

استاد

• Data Management
• Data Analytics
• High Performance Computing
• +۴ مورد دیگر

Prof. Ilia Petrov is a faculty member at Reutlingen University's Faculty of Computer Science and Engineering (INF), leading the Data-Management and -Analysis department. He holds the academic rank of Professor and has been affiliated with the university since 2012. His research focuses on advancing data management and analytics, particularly in the realms of database systems, hardware-optimized storage, and near-data processing. He leads the Daten-Management Labor (Data Management Lab), which explores innovations in computational storage, flash memory optimization, and high-performance database architectures. His research interests include the development of novel storage technologies, such as native computational storage and processing-in-memory systems, alongside efficient indexing methods (e.g., B-Tree variants) for multi-version databases. He has contributed to projects like DANSEN and nativeNDP, which aim to leverage modern hardware for accelerating database operations. Key themes in his work involve minimizing write amplification on flash storage, optimizing HTAP workloads, and enabling efficient near-data processing through FPGA and NVMe integration. Prof. Petrov's publications span topics including computational storage architectures, Bloom filter optimizations for range queries, and concurrency control in large-scale multi-socket systems. His work emphasizes the synergy between database software and hardware innovations, with applications in enterprise systems and big data analytics. He has collaborated on frameworks like NVMulator for non-volatile memory emulation and Cache-coherent shared locking mechanisms for smart storage systems. His lab's activities include the development of KV-store accelerators (e.g., nKV) and cost models for query optimization in key-value systems. He has also explored blockchain data structures and snapshot isolation techniques for database transactions. Current trends in his research address the challenges of real-time data processing, cross-layer data formats, and the integration of emerging storage technologies like computational storage drives.

Paolo Romanoمشاهده پروفایل

دانشیار

• Distributed Systems
• AI/ML Systems
• Autonomic Computing
• +۵ مورد دیگر

Paolo Romano is an Associate Professor at the Department of Computer Engineering, Instituto Superior Técnico (IST), Universidade Técnica de Lisboa. He is also a Senior Researcher at the Distributed Systems Group (INESC-ID). His research focuses on distributed systems, AI/ML systems, transactional memory, autonomic computing, and high-performance computing. He holds a PhD in Computer Engineering from Sapienza University of Rome (2007) and a Master's Degree (Summa Cum Laude) from the University of Rome Tor Vergata (2002). PhD Thesis: 'Protocols for End-to-End Reliability in Multi-Tier Systems' Supervised over 10 PhD and MSc students Research Interests : Dependable Distributed Systems Transactional Memory (Hardware/Software) Autonomic and Self-Optimizing Systems Performance Modelling & Evaluation Key achievements include leading the Cloud-TM EU-funded project (€1.7M), coordinating the Euro-TM COST Action, and winning multiple best-paper awards at ICAC, NETYS, and NCA conferences. He actively participates in technical committees for conferences like EuroPar, ICDCS, and Middleware. Grants & Projects : Coordinator of 'Euro-TM' (€400K) Coordinator of 'Cloud-TM' (€1.7M EC funding) Principal Investigator in national projects like 'specSTM' (€127K) He advises students in areas such as self-tuning distributed systems, transactional data stores, and hardware-software co-design for concurrency control. His work bridges theory and practice, with contributions to frameworks like D2STM and Cloud-TM.

Weihai Yuمشاهده پروفایل

دانشیار

• Distributed Systems
• Collaborative Editing
• Conflict-Free Replicated Data Types (CRDTs)
• +۴ مورد دیگر

Weihai Yu is an Associate Professor at the Department of Computer Science, UiT The Arctic University of Norway. His research focuses on distributed systems, collaborative editing, conflict-free replicated data types (CRDTs), edge computing, and decentralized service orchestration. He leads the Open Distributed Systems (ODS) research group and contributes to projects like the Conflict-free Replicated Relation (CRR) and Nudge Project. Yu has authored over 50 publications since 2009, with recent work emphasizing replicated data streams, undo mechanisms in collaborative systems, and edge-cloud integration. Key research interests include: distributed database replication, real-time collaborative editing with CRDTs, fault-tolerant service orchestration, and asynchronous systems design. His work bridges theory and practice, addressing challenges in consistency, scalability, and user experience in distributed applications. Publications trends show a strong focus on CRDT advancements (e.g., low-cost set CRDTs, generic undo support) and edge computing applications. He collaborates extensively with industry partners on projects like the Nudge Project, exploring IoT-driven transportation systems. Yu's contributions are published in top venues such as Springer Nature, ACM, and IEEE journals/conferences. Maintains the Open Distributed Systems (ODS) group at UiT, focusing on collaborative systems and distributed computing innovations. Current research includes local-first software architectures and conflict-free replicated relations for multi-synchronous database management.

Prasun Dewanمشاهده پروفایل

استاد

• User interfaces
• distributed collaboration
• software engineering environments
• +۹ مورد دیگر

Prasun Dewan is a Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. Before joining UNC-Chapel Hill, he was on the faculty of Purdue University. His academic journey began with a B.Tech. degree in Electrical Engineering from the Indian Institute of Technology of New Delhi, followed by a Ph.D. in Computer Science from University of Wisconsin at Madison in 1986. Dr. Dewan's research interests span multiple domains within computer science, with a strong focus on collaborative systems. His work encompasses user interfaces, distributed collaboration frameworks, software engineering environments, mobile computing, and access control mechanisms. He has made significant contributions to the development of frameworks for implementing both single-user and multi-user applications, collaborative software engineering tools, distributed and migratory object systems, and interoperability solutions. His publication record shows a consistent focus on solving fundamental problems in collaborative computing, with particular emphasis on user interface coupling, object merging, access control, and distributed systems architecture. The evolution of his work demonstrates a progression from foundational frameworks to more specialized solutions addressing real-time collaboration, mobile computing challenges, and complex interoperability requirements. As an academic leader, Dr. Dewan has served as an associate editor for prestigious journals including ACM Transactions on Computer Human Interaction, ACM Transactions on Information Systems, and Journal of Computer Supported Cooperative Work. His research has been supported by significant funding from the National Science Foundation and DARPA, particularly for projects like the Collaboration Bus and Flexible Shared Windows. Dr. Dewan actively mentors graduate students and has advised numerous PhD candidates including Jason Carter, Jacob Bartel, Goopeel Chung, Brian Ladd, John Menges, Eileen Kupstas, Jon Munson, Jaime Navon, and Honghai Shen. His laboratory, part of the UNC Colab group, focuses on developing next-generation collaboration technologies with applications ranging from educational tools to virtual environments.

• 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.'

• Physical Oceanography
• Bio-physical interaction
• Turbulence and Mixing
• +۵ مورد دیگر

Dr. Zhankun Wang serves as an Associate Research Professor in the Northern Gulf Institute and Department of Geosciences at Mississippi State University, concurrently holding an Oceanographer position at NOAA's National Centers for Environmental Information (NCEI) at Stennis Space Center. His expertise centers on observational oceanography and large-scale ocean data management within the Department of Geosciences. Education: Ph.D. in Physical Oceanography (2009), University of Massachusetts - Dartmouth M.S. in Physical Oceanography (2007), University of Massachusetts - Dartmouth B.S. in Oceanography (2002), Ocean University of China Dr. Wang's research spans physical oceanography with emphasis on turbulence and mixing processes, bio-physical interactions, hurricane-ocean dynamics, dissolved oxygen systems, sea turtle stranding patterns, and autonomous vehicle observations. His work integrates field measurements with advanced data management techniques to address critical oceanographic challenges, particularly in the Gulf of Mexico and Arabian Sea regions. He leverages large datasets from cabled observatories, autonomous vehicles, and global databases to investigate ocean responses to extreme events and long-term environmental changes. His publication record (2013-2021) reveals consistent focus on ocean data infrastructure development, hurricane impacts on marine systems, and marine ecosystem responses to physical forcing. Key trends include increasing use of unmanned systems for data collection, expansion of global ocean databases (particularly for microplastics and oxygen content), and interdisciplinary approaches connecting physical processes to biological outcomes like sea turtle mortality. Dr. Wang maintains active professional engagement through memberships in the American Geophysical Union (AGU), Sigma Xi, and the American Association for the Advancement of Science (AAAS). His contributions to ocean science are recognized through leadership roles in major data initiatives rather than traditional awards. As project lead for the Global Surface Underway Marine Database (SUMD) and Stranding Analysis Tools for Gulf of Mexico sea turtles, Dr. Wang directs significant research efforts in ocean data management and marine conservation. His grant-funded work includes international collaborations with the Japan Oceanographic Data Center and leadership in developing NetCDF versions of critical datasets like ICOADS. He serves on steering committees for global ocean data initiatives and acts as primary contact for multiple NCEI oceanographic datasets. Dr. Wang directs the Surface Underway Marine Database at NCEI and contributes to the Northern Gulf Institute's research mission through collaborative projects involving cabled observatories, autonomous vehicles, and hurricane response studies. His laboratory operations focus on data quality control systems and synthesis of multi-platform ocean observations.

Randal Burnsمشاهده پروفایل

استاد

• Scalable Data Systems
• Big Data Analysis
• Storage Systems
• +۷ مورد دیگر

Randal Burns is a Professor and Chair of the Department of Computer Science at Johns Hopkins University, where he leads the Hopkins Storage Systems Laboratory. He is also affiliated with the Kavli Neuroscience Discovery Institute, the Institute for Data-Intensive Science, and the Science of Learning Institute, reflecting his interdisciplinary research in data systems and neuroscience. His research focuses on building scalable data systems for big data exploration and analysis. Key areas include storage system performance, delta compression, distributed file systems, and data-intensive computing. He has made significant contributions to reliable storage, file access prediction, caching strategies, and in-place data reconstruction. The analysis of his recent publications shows a strong trend in optimizing large-scale storage systems, with emphasis on efficiency, scalability, and reliability. His work bridges theoretical algorithm design with practical system implementation in mass storage, distributed environments, and web-scale infrastructures. Dr. Burns has not been listed with any specific scientific awards in the provided text. He advises students and leads research projects through the Hopkins Storage Systems Laboratory, where he mentors advisees in storage systems and data-intensive computing. While no specific grants are mentioned, his lab leadership and publication record suggest active external funding and collaborative research. He directs the Hopkins Storage Systems Laboratory, a research group focused on advancing the design and performance of storage systems for modern data challenges, including big data, neuroscience applications, and distributed environments.

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.

Joseph M. Hellersteinمشاهده پروفایل

استاد

• Database Systems
• Distributed Computing
• Data Visualization
• +۴ مورد دیگر

Joseph M. Hellerstein is a Professor of Computer Science at the University of California, Berkeley, College of Engineering. His research focuses on data-centric systems and their impact on computing, spanning database systems, distributed computing, data visualization, machine learning, and programming languages. Ph.D., Computer Science, University of Wisconsin-Madison (1995) MS, Computer Science, UC Berkeley (1992) AB, Computer Science, Harvard University (1990) Key research areas include database management, distributed systems, cloud programming foundations, and human-data interaction. He has developed systems like Hydro (for distributed programming), Trifacta (cloud data engineering), and Anna (distributed key-value store). Recent work emphasizes progressive data processing, consistency models, and compiler-driven distributed systems. Notable awards: ACM Fellow (2009), Alfred P. Sloan Research Fellow (1998), multiple ACM-SIGMOD Test of Time Awards (2002, 2007, 2013, 2023), Jim and Donna Gray Teaching Award (2015), and IEEE VIS Test of Time Award (2022). He has advised PhD students and contributed to industry through co-founding RunLLM and Trifacta (acquired by Alteryx). Current affiliations include the Berkeley Center for Responsible, Decentralized Intelligence (RDI) and EPIC Data Lab.

Bernd Fischerمشاهده پروفایل

استاد

• Automated software engineering
• Logic-based techniques
• Program verification
• +۷ مورد دیگر

Bernd Fischer is a Professor and current Head of Division in the Division of Computer Science at Stellenbosch University, South Africa. He has previously worked at TU Braunschweig, NASA Ames Research Center, and University of Southampton. His academic journey includes a PhD from Universität Passau (defended June 1, 2001). Professor Fischer's research focuses on automated software engineering with particular emphasis on logic-based techniques. His work spans specification-based component reuse, program synthesis, program verification (including annotation inference, software model checking, and human-oriented presentation of verification results), and innovative visualization approaches like tag clouds over concept lattices. His research has led to significant contributions in concurrent program verification, fault localization, and software repository analysis. Analysis of his recent publications reveals strong trends in software verification, particularly in concurrent systems and model checking. His work has consistently focused on developing practical verification tools (CSeq, ESBMC) that have achieved top rankings in international verification competitions. He has also pioneered visualization techniques for software repositories and academic data exploration using concept lattices and tag clouds. His scientific achievements have been recognized with multiple awards including Best Paper Award at ASE 1998, ASE 2012 Most Influential Paper Award, ACM Distinguished Paper Award (2011), Best Presentation Award at SAFECOMP 2010, and multiple Gold and Silver medals in the International Competition on Software Verification (SV-COMP) in 2014, 2015, and 2016. Professor Fischer has successfully supervised numerous PhD and Master's students, both at Stellenbosch University and previously at University of Southampton. His service to the academic community includes committee memberships in IFIP TC-2 Working Group on Program Generation (since 2004), ASE steering committee (since 2007), and GPCE steering committee (since 2011). He has served as General Chair for SPIN 2015 and GPCE'16, and as Program Committee Chair for GPCE 2009 and ASE 2007. His research group has developed several notable tools including AutoBayes (for automatic generation of data analysis programs), ConceptCloud (for browsing software archives), CSeq (a concurrency pre-processor for sequential C verification), and ESBMC (a model checker for C and C++ programs).

Ingrid Chieh Yuمشاهده پروفایل

دانشیار

• Data Management
• Knowledge Systems
• Software Product Lines
• +۷ مورد دیگر

Ingrid Chieh Yu is an Associate Professor in the Department of Informatics at the University of Oslo, where she also serves as Head of Research and Vice Head of Department (2021-2024) and Deputy Centre Director of SIRIUS. Her academic home is within the Data and Knowledge Management (DKM) research group, with additional affiliations to the Concurrent Security and Robustness for Networked Systems (ConSeRNS) initiative. Professor Yu's research spans multiple domains in computer science, with early work focused on formal methods, software product lines, and concurrent systems. In recent years, her research has expanded significantly into explainable AI, counterfactual explanations, and machine learning interpretability. She has made substantial contributions to feature model evolution, software configuration, and model checking techniques. Her work demonstrates a consistent thread of applying formal methods to practical software engineering challenges, with a notable pivot toward AI explainability in the past five years. Her publication record shows a clear evolution from foundational work in software engineering and formal methods (2006-2015) to increasingly AI-focused research (2016-present). The most recent publications (2020-2025) predominantly address explainable AI, counterfactual explanations, and robust recourse methods, reflecting her adaptation to emerging challenges in machine learning. She maintains strong collaborative relationships with researchers including Einar Broch Johnsen, Crystal Chang Din, and Peyman Rasouli. Professor Yu teaches core computer science courses including INF2220 Algorithms and Data Structures, INF3230 Formal Modeling and Analysis of Communicating Systems, and INF5130 Selected Topics in Rewriting Logic. Her teaching reflects her research expertise, bridging theoretical foundations with practical applications. She leads significant research projects including HyVar: Scalable Hybrid Variability for Distributed Evolving Software Systems and Leveraging Energy-Aware Programming (LEAP), demonstrating her capacity to secure and manage substantial research initiatives. Her work with the SIRIUS center indicates strong industry connections and applied research focus.

Divyakant Agrawalمشاهده پروفایل

استاد

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

Divyakant Agrawal is a Distinguished Professor and Chair of the Computer Science Department at the University of California, Santa Barbara (UCSB). He holds a PhD from SUNY Stony Brook and a BS from Birla Institute of Technology and Science. His research focuses on large-scale distributed systems, cloud data management, and database security, with notable contributions to geo-replicated data, privacy-preserving techniques, and social network analysis. Agrawal has led NSF-funded projects on data summarization, hardware acceleration, and wireless sensor networks. He served as VP of Data Solutions at ASK.com and as a visiting senior researcher at NEC Laboratories and the University of Hong Kong. Education: PhD (Computer Science, SUNY Stony Brook), BS (Electrical Engineering, BITS Pilani). Leadership Roles: Chair of UCSB Computer Science Department (1999–2003), Visiting Professorships at National University of Singapore and University of Hong Kong. His research spans distributed algorithms, database concurrency control, and privacy in cloud systems. Key areas include transaction processing, data stream operators, and fraud detection in advertising networks. Agrawal has authored over 300 papers and co-edited journals like the VLDB. He is a Fellow of IEEE, ACM, and AAAS, and has received awards such as the Outstanding Graduate Mentor from UCSB (2011). Professional Contributions: Served on program committees for SIGMOD, VLDB, and IEEE conferences; led editorial roles for Distributed and Parallel Databases and the VLDB Journal. His work on systems like G-Store (cloud data retrieval) and Zephyr (elastic databases) showcases innovations in scalability and autonomy.

Limin Jiaمشاهده پروفایل

استاد پژوهش

• Cyber-Physical Systems
• Software Security
• Formal Verification
• +۴ مورد دیگر

Limin Jia is a Research Professor affiliated with Carnegie Mellon University's CIT Department of Electrical and Computer Engineering and the Computer Science Department. He leads research in systems security, formal verification, and programming language foundations. His work emphasizes compositional assurance for cyber-physical systems and secure software development practices. Education background is not explicitly stated in the text, but his research focuses on advanced technical domains requiring doctoral-level expertise. Current research interests span cyber-physical systems assurance, software security, and formal methods for program analysis. Recent work includes groundbreaking studies on compositional assurance for large systems (2025), adversarial attacks on large language models (2024), and Rust-based program verification tools like Crabtree (2024). His team also develops tools such as Nodemedic (Node.js vulnerability analysis) and ProInspector (protocol bug detection). Research outputs bridge theory and practice, with 15+ publications in 2023-2025 alone. Current advisees include Myra Dotzel, Nuno Sabino, and Rafael Goncalves. Research collaborations involve multi-institutional projects in network security, IoT safety, and compiler verification. Active in both ACM and IEEE conferences, his work has been funded through multiple NSF and industry grants (details not specified in text). Operates within the Mehrabian Collaborative Innovation Center, fostering interdisciplinary projects at the intersection of electrical engineering, computer science, and cybersecurity. His lab develops both foundational theories and practical tools for improving system security and reliability across domains.

Eddie Kohlerمشاهده پروفایل

استاد

• Computer Science
• Systems
• Networks
• +۵ مورد دیگر

Eddie Kohler is the Microsoft Professor of Computer Science at Harvard University's Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), where he also serves as Director of Undergraduate Studies in Computer Science. His research focuses on high-performance systems, networks, and databases with an emphasis on concurrency control, data privacy, and scalable software design for multicore processors. He has contributed to foundational work in transactional systems, web application backends (e.g., Noria), and privacy-preserving technologies (e.g., Edna). His research spans theoretical frameworks like the Scalable Commutativity Rule and practical implementations such as the Alto lightweight virtualization system. Kohler's work often bridges theory and practice, addressing challenges in distributed systems, sensor networks, and regulatory compliance (e.g., GDPR). Notable contributions include innovations in in-memory database concurrency, optimistic transaction processing, and network congestion control protocols (e.g., TFRC-SP). His projects frequently emphasize system correctness through formal verification and empirical evaluation. His articles reflect a trajectory from foundational concurrency research to applied systems engineering, with recent focus on privacy in web applications and optimizing modern multicore architectures. No specific grants or advisees are listed in the provided information. Kohler leads research initiatives in scalable systems and maintains active collaboration with industry through his academic leadership roles.