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Sujaya Maiyya is an Assistant Professor at the Cheriton School of Computer Science, University of Waterloo. Prior to this, she completed a postdoc at Cornell University and earned her PhD from the University of California, Santa Barbara. Her research focuses on distributed systems, databases, and privacy/security, particularly in designing secure and efficient data management systems. She leads projects on oblivious databases, trusted execution environments (TEEs), and scalable privacy-preserving systems. Education: PhD in Computer Science, University of California, Santa Barbara (2018) MSc in Computer Science, University of California, Santa Barbara (2017) BE in Information Science, PESIT Bangalore (2014) Research Interests: Distributed systems, database privacy, oblivious datastores, genomics data security, and secure computation using TEEs. Her work emphasizes practical solutions for privacy-preserving storage and query processing, including tunable-privacy mechanisms and fault-tolerant ORAM systems. Awards and Grants: CFI/ORF Infrastructure Grant (2024-2029) NCC Research Awards (2024-2028) NSERC Discovery Grant (2023-2027) MIT EECS Rising Stars (2021) Teaching: Courses include CS348 (Introduction to Databases) and CS848 (Privacy Enhancing Data Systems). She emphasizes foundational concepts and system internals in database design and secure systems. Professional Service: Chair of Ontario Database Day (2024), PC member for SIGMOD, EDBT, VLDB, and ICDE. Frequent reviewer for journals like TKDE and DKE.

• Distributed Systems
• Database Systems
• Data Privacy
• +3 more

Khuzaima Daudjee is a Professor and David R. Cheriton Faculty Fellow in the Cheriton School of Computer Science at the University of Waterloo. His research focuses on systems-oriented problems at the intersection of systems and data management, particularly building large-scale systems, storage infrastructure in the cloud, and modern hardware applications. He leads projects in distributed database systems, elastic scaling, and resource optimization. His recent work includes Caerus (geo-replicated transactions), Tiresias (predictive storage), and MorphoSys (automatic physical design metamorphosis). Daudjee has chaired major conferences including ICDE 2026 and serves on editorial boards for VLDB, SIGMOD, and IEEE TKDE journals. His awards include ACM Distinguished Scientist and multiple best paper awards. Educational initiatives include developing distributed systems teaching materials and supervising graduate students across database and distributed systems domains. His industry collaborations involve cloud infrastructure optimization and scalable data processing frameworks.

• Distributed Systems
• Database Management
• Cloud Computing
• +3 more

Daniel Abadi is the Darnell-Kanal Professor of Computer Science at the University of Maryland, College Park. He leads the Data Systems Lab at Maryland (DSLAM) and is widely recognized for his groundbreaking contributions to database system architecture and implementation. Previously, he was a faculty member at Yale University where he received the Provost's Teaching Prize. Abadi's research primarily focuses on database system architecture, particularly at the intersection with scalable and distributed systems. He is best known for developing the storage and query execution engines of the C-Store prototype (a column-oriented database system commercialized by Vertica and later acquired by Hewlett-Packard), HadoopDB research (commercialized by Hadapt and acquired by Teradata), and deterministic distributed transactional systems like Calvin (currently being commercialized by Fauna). His work bridges theoretical innovation with practical industrial impact. Analysis of his recent publications reveals a consistent trajectory toward solving fundamental challenges in distributed database systems. His research has evolved from foundational work on column-stores and hybrid database architectures to cutting-edge innovations in geo-replicated transactions, concurrency control mechanisms, and the integration of machine learning with database systems. The trend shows increasing focus on practical implementations that address real-world scalability and performance challenges in large-scale data processing environments. ACM Fellow Churchill Scholarship recipient NSF CAREER Award winner Sloan Research Fellowship recipient VLDB Best Paper Award winner Two VLDB Test of Time Awards (for C-Store and HadoopDB) 2008 SIGMOD Jim Gray Doctoral Dissertation Award 2013-2014 Yale Provost's Teaching Prize 2013 VLDB Early Career Researcher Award Professor Abadi has successfully mentored several PhD students, most notably Alexander Thomson and Jose Falerio, both of whom won the prestigious SIGMOD Jim Gray Doctoral Dissertation Award for their work under his supervision. His research has been generously supported by multiple NSF grants including BIGDATA awards and other funding mechanisms that have enabled significant advances in database technology. He actively collaborates with industry partners, with several of his research projects leading directly to commercial products. At the University of Maryland, Abadi directs the Data Systems Lab at Maryland (DSLAM), which focuses on developing innovative database technologies that address contemporary challenges in data management. The lab's research spans distributed transaction processing, database architecture, and the integration of database systems with emerging computing paradigms. Notable projects include SLOG (Serializable, Low-latency, Geo-replicated Transactions), which eliminates traditional tradeoffs in distributed database design, and ongoing work in deterministic database systems that provide strong consistency guarantees without sacrificing performance.

• Database system architecture
• Distributed database systems
• Column-oriented databases
• +5 more

Kaiyang Liu is an Assistant Professor at the Department of Computer Science, Memorial University of Newfoundland. He holds a Ph.D. from Central South University (2019) and was a Postdoctoral Fellow at the University of Victoria, Canada. His research focuses on distributed cloud/edge computing, data center networks, and distributed machine learning, emphasizing optimization for data-intensive services. He is an IEEE Senior Member and has received prestigious awards, including the NSERC Discovery Grants and IEEE TCCLD Outstanding Ph.D. Thesis Award. Education: Ph.D. in Information Science and Technology, Central South University (2014–2019) M.Sc. in Information Science and Technology, Central South University (2012–2014) B.Eng. in Information Science and Technology, Central South University (2008–2012) Research Assistant at the University of Victoria (2016–2018) Research Interests: Kaiyang’s work bridges AI and cloud computing, exploring optimization strategies for next-generation systems. Key areas include learning-based congestion control, energy-efficient resource management, and scalable distributed storage solutions. His research has been published in top-tier journals like IEEE Transactions on Parallel and Distributed Systems and conferences such as IEEE ICDCS. Awards & Grants: NSERC Discovery Grants & Discovery Launch Supplement (2024) IEEE TCCLD Outstanding Ph.D. Thesis Award (2020) CSC-UVic Fellowship (2016–2018) Teaching: He teaches courses on Computer Networks, Advanced Computer Networks, and Operating Systems at Memorial University and previously at the University of Victoria. Labs & Teams: His research group focuses on Space Edge Computing, leveraging LEO satellites for resilient, low-latency networks. Ongoing projects include optimizing distributed systems for AI workloads and satellite-based data centers.

• Distributed Cloud/Edge Computing
• Data Center Networks
• Distributed Machine Learning
• +3 more

Natacha Crooks Dr. Natacha Crooks is an Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS) at UC Berkeley. Her research focuses on distributed systems, databases, and security, with a particular emphasis on consistency models, BFT protocols, and cloud computing. She is a founding member of the SkyLab and a core contributor to the Data Systems and Foundations Group at Berkeley. She holds a Ph.D. in Distributed Systems from the University of Texas at Austin (2019) and a BA in Computer Science and Law from the University of Cambridge (2012). Affiliations & Roles: Assistant Professor, UC Berkeley EECS Visiting Researcher at Azure Research, Security & Privacy Founding Member of SkyLab Member of Berkeley Center for Decentralized Intelligence Former Scientific Advisor at Improbable and Astronomer Research Interests: Her work bridges distributed systems and database research, addressing challenges in transactional consistency, fault-tolerant protocols, and cloud resource optimization. Key themes include: Designing scalable BFT consensus algorithms Secure multi-cloud storage solutions Optimizing distributed transaction processing Privacy-preserving distributed systems Awards & Recognition: Sloan Research Fellow (2025) NSF CAREER Award ACM SIGOPS Dennis M. Ritchie Doctoral Dissertation Award (2020) IEEE CS TCDE Early Career Award (2024) Teaching: Fall 2025: CS 294-282 (Research Culture and Community Norms), Wheeler 130. Industrial Collaboration: Prior roles include visiting researcher at Cornell University, Microsoft Research (DMX group), and Imperial College London. Industrial partnerships include work with Materialize, Astronomer, and Improbable.

• Distributed Systems
• Database Management Systems
• Operating Systems
• +7 more

Daniel J. Abadi is a prominent researcher in database systems at Yale University. With over two decades of impactful research, he has made significant contributions to the fields of distributed databases, transaction processing, and column-oriented database systems. His work bridges theoretical foundations with practical implementations that have influenced both academia and industry. Dr. Abadi's research primarily focuses on database system architecture, with particular emphasis on: Distributed and geo-replicated database systems High-performance transaction processing Column-oriented and analytical database systems Stream processing and real-time analytics Cloud and serverless database technologies Integration of machine learning with database systems His recent work shows a continued focus on addressing scalability challenges in modern database systems, with particular attention to multi-region transaction processing, automated data management, and the integration of machine learning techniques. The trend in his publications indicates a strong emphasis on practical, deployable systems that solve real-world problems faced by industry. Dr. Abadi has been instrumental in several major research initiatives and reports that have shaped the direction of database research, including the Seattle Report and the Cambridge Report on Database Research. Throughout his career, Dr. Abadi has mentored numerous students and collaborated extensively with leading researchers in the field. His work has received significant recognition through widespread citations and adoption of his ideas in both academic and industrial database systems.

• Database Systems
• Distributed Databases
• Transaction Processing
• +5 more

Bhuvan Urgaonkar is a Professor in the Department of Computer Science and Engineering at Penn State University's College of Engineering. His research centers on optimizing cloud computing systems through innovative approaches to resource allocation, cost efficiency, and energy management. Current research focuses on Burstable Instance Scaling Serverless Computing Optimization Distributed Storage Systems Multi-resource Fair Allocation Cloud Economics Recent publications highlight advancements in autoscaling techniques, serverless architecture design, and trace modeling for high-load scenarios. These works emphasize practical solutions for cost-effective resource utilization in public cloud environments. Scientific Awards: CNS: Core: Small: Consistent, Geo-Distributed Data Stores on the Public Cloud (NSF, 2022-2025) CNS Core: Small: Principled Methodologies for Automated Cost-Effective Service Blending (NSF, 2021-2024) PPoSS: Cross-Layer Design for HPC in the Cloud (NSF, 2020-2022) CSR: Burstable Instances for Cost-Efficacy (NSF, 2017-2020) CSR: Student Travel Support for SIGMETRICS (NSF, 2016-2017)

• Cloud Computing
• Data Center Optimization
• Resource Allocation
• +4 more

Alysson Neves Bessani is an Associate Professor at the Informatics Department of Faculdade de Ciências da Universidade de Lisboa, Portugal, and a member of the LaSIGE research group. His work focuses on distributed systems, Byzantine fault tolerance, and cybersecurity, with significant contributions to blockchain consensus and intrusion-tolerant architectures. Academic Rank: Associate Professor University: Universidade de Lisboa School: Faculdade de Ciências Department: Informatics Department Research Groups: LaSIGE, Navigators Research Interests span distributed systems design, Byzantine fault tolerance, adaptive consensus protocols, and secure multi-cloud storage. His work bridges theoretical foundations with practical implementations like the BFT-SMaRt library and the Vawlt startup. Scientific Awards include multiple Test-of-Time Awards (DSN'24, DSN'21), IBM Faculty Award (2017), and Best Student Paper at Middleware'19. He has advised numerous PhD and Master’s students, contributing to advancements in fault-tolerant systems. Publications (15 most recent) reveal trends in Byzantine consensus optimization, blockchain integration, and AI-driven threat detection. His interdisciplinary work combines distributed computing with genomics and IoT security, reflecting a broad impact across computer science.

• Distributed Systems
• Dependability
• Fault Tolerance
• +5 more

Mohammad Sadoghi is a Professor at the University of California, Davis, with former affiliations at Purdue University, IBM T.J. Watson Research Center, and the University of Toronto. His research focuses on distributed systems, blockchain technologies, consensus protocols, and fault-tolerant computing. He has contributed extensively to transaction processing, stream processing architectures, and the integration of edge-cloud systems with blockchain frameworks. Current Affiliation: University of California, Davis Former Affiliations: Purdue University, IBM, University of Toronto Research Interests include consensus algorithms, Byzantine fault tolerance, distributed ledger technologies, and scalable data processing. He has pioneered systems like ResilientDB and ByShard, addressing challenges in global-scale distributed systems and blockchain fabrics. His work bridges theoretical foundations with practical implementations, emphasizing real-world applications in edge computing and hybrid cloud-edge environments. Key publications highlight advancements in consensus protocols, blockchain scalability, and fault-tolerant architectures. Recent trends in his work focus on concurrent consensus mechanisms, DAG-based systems, and secure geo-replication. Contributions span both academic publications and industry-oriented solutions, such as the Bedrock platform for BFT protocol analysis. Grants and advising roles are implied through his extensive research output, though specific grants are not detailed in the provided text. His collaborations include projects on self-curating databases (e.g., L-Store) and systems like SplitJoin for stream processing.

• Blockchain Technology
• Distributed Systems
• Consensus Protocols
• +6 more

Willy Zwaenepoel is a Professor and Dean of the Faculty of Engineering at the University of Sydney. He holds a B.S. from the University of Gent and M.S./Ph.D. from Stanford University. Previously, he served as Dean of the School of Computer and Communication Sciences at EPFL and was a faculty member at Rice University. His expertise spans operating systems, distributed systems, and high-performance computing. Education: B.S., University of Ghent, Belgium (1979) M.S., Stanford University (1980) Ph.D., Stanford University (1984) Research Interests: Dr. Zwaenepoel focuses on distributed systems, operating systems, and their applications in database replication, virtual machine performance, and software update mechanisms. His work includes foundational contributions to distributed shared memory (e.g., Treadmarks) and startups like iMimic Networking. Awards: ACM Fellow (2000) IEEE Fellow (1998) Fellow of the Australian Academy of Technical Sciences and Engineering (2020) Recipient of the IEEE Tsutomu Kanai Award (2007) Key Contributions: His research addresses challenges in distributed systems performance, such as latency reduction in key-value stores and efficient graph processing. Current projects explore I/O optimization in virtualized environments and causal consistency for geo-replicated systems. Students/Advising: Advises Ph.D. students and postdocs, including William in database replication. His mentorship led to the Rice University Teaching Award (2000).

• Operating Systems
• Distributed Systems
• Database Replication
• +4 more

Rodrigo Miragaia Rodrigues is a full professor at the Instituto Superior Técnico (ULisboa) and a researcher at INESC-ID since 2015. He previously held roles as an associate professor at Universidade Nova de Lisboa, tenure-track faculty at MPI-SWS, and completed his PhD at MIT in 2005 under Barbara Liskov. Education: PhD in Computer Science, MIT, 2005 Research Interests: Focuses on distributed systems, fault-tolerant computing, cloud infrastructure, and consistency models. His work bridges theoretical foundations and practical implementations, addressing challenges in geo-replication, secure analytics, and resource allocation in serverless environments. He emphasizes scalable systems and resilient data management. Awards: Best Paper Award at SOSP ERC Starting Grant Google Faculty Research Award Advising & Grants: Has advised 7 PhD students as main advisor, with graduates in top institutions like Purdue, TU Munich, and USTC. Secured funding from the European Research Council (ERC) and Google, focusing on projects like DependableCloud (ERC Grant 307732). Labs & Teams: Leads research at INESC-ID and previously directed the Dependable Systems Group at MPI-SWS. Active in academic leadership roles, including President of the Scientific Council at IST.

• Distributed Systems
• Cloud Computing
• Fault Tolerance
• +3 more

Alexey Gotsman is a tenured Research Professor at the IMDEA Software Institute in Madrid, Spain, where he leads research at the intersection of software verification and distributed computing. He also works part-time as a visiting academic at Amazon Web Services. His educational background includes a Ph.D. from the University of Cambridge, where he was previously a postdoctoral fellow. His research spans theoretical foundations and practical implementations of distributed systems, with particular emphasis on fault tolerance, consensus algorithms, and consistency models. His research interests focus on the theoretical and practical aspects of distributed systems, including Byzantine fault tolerance, state machine replication, distributed transactions, and consistency models. His work bridges the gap between formal verification techniques and real-world distributed systems implementations, with numerous publications in top-tier venues like PODC, DISC, and NSDI. His recent publications show a clear progression from theoretical foundations to practical implementations, with increasing focus on real-world applications, performance considerations, and fault tolerance in large-scale distributed systems. The research demonstrates strong connections between formal methods and practical system design, particularly in the areas of consensus protocols, replication strategies, and transaction processing. Best paper award at OPODIS'23 Best paper award at DISC'18 Best paper award at CONCUR'12 EAPLS Best Dissertation Award Runner-up prize in the BCS Distinguished Dissertation Competition ERC Starting Grant 'RACCOON: A Rigorous Approach to Consistency in Cloud Databases' (2017-2022) Ramón y Cajal Fellowship (2017-2022) Alexey actively mentors PhD students including Alejandro Naser Pastoriza, Fedor Ryabinin, and Antonio José Fernández Pinto, while his alumni have gone on to faculty positions at institutions like University of Paris 7 and University of Colorado Boulder, as well as industry roles at companies like ARM and Informal Systems. He has received significant funding including an ERC Starting Grant and served on program committees for numerous top conferences including POPL, DISC, and PODC. He currently co-organizes the International Symposium on Distributed Computing (DISC) and has been instrumental in organizing workshops focused on consistency in distributed systems. His research group at IMDEA Software Institute focuses on developing rigorous approaches to consistency in cloud databases and distributed systems, with active projects spanning theoretical analysis, protocol design, and practical implementation of fault-tolerant distributed systems.

• Distributed Systems
• Software Verification
• Consensus Algorithms
• +5 more

Kwangsung Oh is an Assistant Professor in the Department of Computer Science at the University of Nebraska at Omaha's College of Information Science & Technology. His research focuses on GPU-based image reconstruction, cloud computing optimization, and deep learning for software evolution. Contact: kwangsungoh@unomaha.edu . Research Areas GPU Acceleration for Biomedical Imaging Geo-distributed Data Analytics Serverless Computing Optimization Machine Learning in Software Engineering Recent publications demonstrate expertise in structured illumination microscopy algorithms, cloud storage policy frameworks, and deep learning-driven code inspection tools. His work bridges computational biology applications with distributed systems infrastructure.

• Computer Science
• Data Analytics
• Cloud Computing
• +3 more

Prof. Dr. Tolga Ovatman is a faculty member at the Department of Computer Engineering, Istanbul Technical University , where he has been serving as Head of Department since 2024. His academic career spans roles from Research Assistant (2004-2012) to Associate Professor (2019-2023) and full Professor (2023-present). He previously held administrative roles such as Vice Dean (2018-2022) and Deputy Head of Department (2016-2018). PhD in Computer Engineering (2005-2011) MS in Computer Engineering (2003-2005) BSc from Hacettepe University (1999-2003) His research focuses on model checking , replicated state machines , cloud computing , and object-oriented software . Recent work addresses computation offloading in 6G networks , collaborative text editing data structures , and energy-efficient environmental monitoring systems . Key projects led include Design of a Multiplexed State Machine Storage System for Edge Computing (2022-2024) and Microservice Compatible Symphony Infrastructure Research (2020). He has supervised numerous theses on topics ranging from collaborative text editing to AI applications in watershed management . Publications span IEEE Transactions , Springer , and conferences like CSCE and CLOSER .

• Algorithms and Computing Theory
• Computer Software and Software Engineering
• Cloud Computing
• +6 more

Marc St.-Hilaire is a Professor at the School of Information Technology and cross-appointed to the Department of Systems and Computer Engineering at Carleton University within the Faculty of Engineering and Design . He holds a Ph.D. from École Polytechnique de Montréal and serves as the NET Program Coordinator. He is a Senior Member of IEEE and has received multiple awards, including the Carleton Faculty Graduate Mentoring Award and the Teaching Achievement Award. Education: Ph.D., École Polytechnique de Montréal His research centers on telecommunication network planning, mobile computing, and network optimization , with strong emphasis on wireless and vehicular networks, fog/edge computing, blockchain integration, and AI-driven network protocols . His recent work applies reinforcement learning, genetic algorithms, and fuzzy logic to solve challenges in dynamic and distributed environments. The trend in his recent publications shows a strong focus on smart infrastructure , including Internet of Vehicles (IoV), smart grids, and cloud/edge resource management . He frequently collaborates with students and researchers on topics such as virtual network embedding, SLA-aware provisioning, and cooperative positioning , often leveraging emerging technologies like blockchain and deep learning. Scientific Awards and Honors: Senior Member, IEEE Best Industry Paper Award, WF-IoT 2024 Best Paper Award, ADHOCNETS 2019 Best Paper Award, iThings 2018 IEEE WIE Best Paper Award, CCECE 2018 Best Paper Award, ADHOCNETS 2017 Carleton Faculty Graduate Mentoring Award, 2014 Carleton Teaching Achievement Award, 2014–2015 Dr. St.-Hilaire actively supervises a large team of graduate students and has mentored over 40 Ph.D., Master’s, and postdoctoral researchers to completion. He has secured significant research funding through industry and government grants, enabling extensive experimental testbeds in SDN, fog computing, and vehicular networks. His work bridges theoretical optimization with practical implementation, often releasing tools and simulators (e.g., NetAnalyzer, DEVS fog simulator). He leads a vibrant research team focused on network intelligence, edge-based complex event processing, and sustainable computing . His lab collaborates with industry partners on projects involving 5G/6G integration, TSN in cloud environments, and smart city applications such as cloud-based waste management and smart grid simulation.

• Telecommunication network planning
• Wired and wireless communication networks
• Mobile computing
• +12 more