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Chen LiView profile

Professor

• Data Management
• Database Systems
• Machine Learning
• +8 more

Chen Li is a Professor in the Department of Computer Science at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information and Computer Sciences (ICS). He holds a Ph.D. from Stanford University and bachelor's and master's degrees from Tsinghua University. His research focuses on data management, including databases, query optimization, machine learning systems, and open-source tools like AsterixDB and Texera. He has received prestigious awards such as the NSF CAREER Award and IEEE Fellow recognition. Li is also a board member of the VLDB Endowment and the former Faculty Director of UCI's ICS Master of Computer Science Program. Education: Ph.D., Computer Science, Stanford University M.S. and B.S., Computer Science, Tsinghua University Research interests span next-generation databases, approximate query processing, and AI-driven data analytics. Notable contributions include the Texera system for collaborative data science workflows and the Apache AsterixDB project. He has led NIH-funded initiatives in diabetes research and pandemic prediction, emphasizing real-world applications of data science. Professional roles include PC co-chair of VLDB 2015, General Co-chair of SIGMOD 2027, and a visiting research scientist at Google. His awards highlight his impact in both academia and industry. Advising and mentoring are central to his career, with a focus on graduate education. He has pioneered outreach programs like DS4ALL to teach high-school students data science using Texera.

Peter PietzuchView profile

Professor

• Distributed Systems
• Cloud Computing
• Big Data Processing
• +5 more

Peter Pietzuch is a Professor in the Department of Computing at Imperial College London, where he leads the Large-Scale Data & Systems (LSDS) group. He also serves as the Director of Research and is a Visiting Researcher at Microsoft Research Cambridge. Pietzuch holds a Ph.D. from the University of Cambridge and a B.A. from Girton College. His research spans distributed systems, cloud computing, big data processing, and systems security. Key interests include: Scalable architectures for cloud-native applications Efficient stream processing and machine learning systems Trusted execution environments and secure cloud infrastructure Optimization of serverless computing and distributed databases His recent publications focus on adaptive machine learning frameworks, secure cloud resource management, and high-performance stream processing systems. Trends show strong emphasis on hardware-software co-design, confidential computing, and fault-tolerant architectures. Awards include: Best Paper Award at Middleware'03 He actively advises PhD students and secures grants for projects like Faasm (serverless computing) and Teechain (blockchain security). His LSDS group collaborates with industry partners including Microsoft Research. Pietzuch teaches undergraduate and graduate courses including Scalable Systems for the Cloud and Operating Systems . He co-founded the ACM DEBS conference and serves on steering committees for EuroSys and Middleware.

Justine SherryView profile

Assistant Professor

• Computer Networking
• Networked Systems
• Middleboxes
• +5 more

Justine Sherry is the A. Nico Habermann Associate Professor of Computer Science at Carnegie Mellon University, affiliated with the College of Engineering. She holds a PhD (2016) and MS (2012) from UC Berkeley and a BS/BA (2010) from the University of Washington. Her research focuses on networked systems, including middleboxes, cloud computing, congestion control, and hardware acceleration (e.g., SmartNICs/FPGAs). Notable projects include Pigasus (open-source 100Gbps IDS), APLOMB (cloud-based middlebox scaling), and BlindBox (encrypted traffic scanning). Her academic roles include serving on the SIGCOMM CARES Committee, DARPA ISAT Study Group, and ACM CoNEXT Steering Committee. Awards include the Alfred P. Sloan Fellowship, VMware Systems Award, and IETF Applied Networking Prize. She advises over 15 students and collaborates with industry partners like Intel and VMware. Research highlights include radical shifts in datacenter architectures (SmartNIC compute control), fairness in congestion algorithms (BBR analysis), and database-proxy innovations (Tigger with eBPF). Her teaching emphasizes systems as science labs, integrating experimental design and hypothesis testing into projects. Education: PhD UC Berkeley (2016), MS UC Berkeley (2012), BS/BA University of Washington (2010) Labs/Teams: CyLab, SNAP Research Group, CMU Portugal Collaboration Grants: NSF, Intel, Google Faculty Awards

• Edge Computing
• Fog Computing
• Distributed Systems
• +5 more

Umakishore Ramachandran is a Professor in the School of Computer Science within the College of Computing at Georgia Institute of Technology. His research spans edge computing, distributed systems, and real-time video analytics, with significant contributions to fog computing infrastructure, mobile systems, and sensor networks. Over a prolific 38-year career, he has authored 142 publications with major contributions in 2022-2025. His research interests focus on bridging the gap between cloud and edge computing, with pioneering work in video analytics systems like EVA and MicroEdge. He investigates resource optimization for latency-sensitive applications, developing novel approaches for load shedding, data management, and container runtime efficiency at the network edge. His work addresses fundamental challenges in distributed camera networks, autonomous vehicle systems, and real-time stream processing. Ramachandran's recent publications reveal a strong emphasis on practical edge computing solutions, with 75% of his 2021-2025 work focusing on video analytics and infrastructure optimization. His research shows increasing collaboration with industry partners while maintaining academic rigor, with publications appearing in top venues like SIGMOD, Middleware, and DEBS. The work consistently addresses real-world constraints of resource-constrained edge environments. Ramachandran has mentored numerous researchers who have become principal investigators on edge computing projects, with notable collaborators including Harshit Gupta, Enrique Saurez, and Zhuangdi Xu appearing as first authors on multiple papers. His work has received significant grant support for projects related to mobile fog computing and distributed video analytics. He leads research in the Edge Computing Laboratory at Georgia Tech, focusing on the development of practical frameworks for real-world deployment of edge infrastructure. Current projects include eCAV for connected autonomous vehicles and MicroEdge for multi-tenant camera processing systems.

Roxana GeambasuView profile

Associate Professor

• Computer Systems
• Distributed Systems
• Security and Privacy
• +8 more

Roxana Geambasu is an Associate Professor at Columbia University's Department of Computer Science, with affiliations to the Software Systems Lab and the Cybersecurity Committee . She specializes in systems security, differential privacy, and resource management for modern computing environments. PhD: University of Washington (2011) Undergraduate: Polytechnic University of Bucharest, Romania Her research focuses on integrating differential privacy as a first-class computing resource in infrastructure systems, with key contributions in: Privacy Budget Management (PrivateKube, DPack, Turbo) Web & Mobile Privacy (Cookie Monster, Big Bird) Security Abstractions (POSIX, Vanish, XRay) Article trends show a strong emphasis on differential privacy (8/15), resource scheduling (5/15), and privacy-preserving advertising (3/15). Key subfields include budget optimization, browser APIs, and ML pipeline privacy. Scientific awards include: Alfred P. Sloan Fellowship NSF CAREER Award Google Ph.D. Fellowship in Cloud Computing Best Paper Awards at SOSP, EuroSys She advises M.S. and undergraduate students, teaching courses in Distributed Systems and Privacy Curriculum . Her lab develops tools like PixelDP and Sunlight for operationalizing privacy in real-world systems.

Mohamed F. MokbelView profile

Professor

• Database Systems
• Spatial Data
• GIS (Geographic Information Systems)
• +3 more

Mohamed F. Mokbel is a Distinguished McKnight University Professor in the Department of Computer Science and Engineering at the University of Minnesota - Twin Cities , where he also serves as the Director of Graduate Studies. He is recognized as an IEEE Fellow and ACM Distinguished Member for his contributions to spatially- and privacy-aware systems. His research focuses on database systems , spatial data management , and GIS (Geographic Information Systems) , with significant work in spatiotemporal data, location-based services, and machine learning for spatial applications. His most recent publications address scalable BERT-based trajectory imputation , spatial logistic regression frameworks , and spatiotemporal big data decay techniques . Key Awards: Distinguished McKnight University Professor (2023) ACM SIGSPATIAL 10-Year Impact Award (2022) IEEE Fellow (2020) ACM Distinguished Member (2017) NSF CAREER Award (2010) Selected Conference Papers: Recathon (2015, IEEE MDM Best Paper) ST-Hadoop (2017, SSTD Best Paper) KAMEL (2023, ACM SIGMOD Demo) Academic Service: Editor-in-Chief, ACM Transactions on Spatial Algorithms and Systems (2024–) General Co-Chair, ACM SIGSPATIAL 2025 Past Chair, ACM SIGSPATIAL (2014–2017)

• Distributed Systems
• Cloud Computing
• Edge Computing
• +7 more

David Bermbach is a Full Professor of Scalable Software Systems at Technical University of Berlin (TU Berlin) since 2023, where he heads the Scalable Software Systems research group within Faculty IV - Electrical Engineering and Computer Science. He is also co-affiliated with the Einstein Center Digital Future (ECDF). Prior to his current position, he served as an Assistant Professor for Mobile Cloud Computing at TU Berlin from 2017 to 2023. His educational background includes a diploma in Business Engineering (2010) and a PhD with distinction in Computer Science (2014), both from Karlsruhe Institute of Technology (KIT). Prof. Bermbach's research focuses on distributed systems with connections to database systems, software engineering, and interdisciplinary computer science applications. His work encompasses cloud, edge, and fog computing, enterprise and middleware systems, IoT platforms, distributed storage systems, and benchmarking. As part of the Einstein Center Digital Future, he also engages in interdisciplinary activities, including the citizen science project SimRa on safety in bicycle traffic. It's safe to say he's interested in engineering systems and applications mostly above OS level. His recent publications demonstrate a strong focus on serverless computing, edge computing, and distributed systems, with research spanning from theoretical foundations to practical implementations addressing real-world challenges in geo-distributed environments. Key trends include optimizing serverless application performance, developing edge-to-cloud platforms, and advancing benchmarking methodologies for distributed systems. Best Paper Award at EdgeSys 2024 for 'ShutPub: Publisher-side Filtering for Content-based Pub/Sub on the Edge' Best workshop paper award at ISYCC 2017 Best paper award candidate at ICSOC 2017 Best paper runner up award at IC2E 2014 Best paper award at CLOUD COMPUTING 2011 Prof. Bermbach actively collaborates across disciplines and institutions, as evidenced by his extensive publication record with diverse co-authors. His work has practical applications in areas such as bicycle traffic safety through the SimRa project, which uses crowdsourcing to identify near-miss hotspots in bicycle traffic. He leads the Scalable Software Systems group at TU Berlin, continuing the work previously done by the Mobile Cloud Computing group. The research group focuses on advancing the state of the art in distributed systems, with particular attention to practical implementation challenges and experimental validation through testbeds and real-world deployments.

Bruce MacDowell MaggsView profile

Professor

• Computer Networks
• Distributed Systems
• Algorithms
• +7 more

Bruce MacDowell Maggs is a Professor in the Department of Computer Science at Duke University and serves as Vice President of Research at Akamai Technologies. His career bridges academic research and industrial innovation in computer science, particularly in distributed systems and networking. Research Interests: His work spans computer networks , distributed systems , parallel algorithms , content delivery , and fault-tolerant computing . He has made significant contributions to network routing, load balancing, scalability of web applications, and energy efficiency in large-scale systems. His research often combines theoretical rigor with practical system design. The recent publications highlight a consistent focus on scalability , network performance , and security in internet-scale applications. Key themes include query caching , traffic modeling , resilient routing , and energy optimization , reflecting his deep involvement in the infrastructure of modern web services. No scientific awards are mentioned in the provided text. Advising and Teaching: He has advised numerous Ph.D. students, many of whom are now faculty or researchers at top institutions. His former students include Ramesh Sitaraman, Anja Feldmann, and Andrea Richa. He currently advises Anat Talmy at Duke. He has taught a wide range of courses at Duke, Carnegie Mellon, and MIT, including Computer Networks, Operating Systems, Algorithms, and Discrete Mathematics. Labs and Teams: While not explicitly named, his research is closely tied to systems and networking groups at Duke and his industrial work at Akamai, a leader in content delivery networks. His collaborations with Tom Leighton and others at Akamai suggest leadership in research teams developing foundational internet technologies.

Theodora VarvarigouView profile

Professor

• Cloud Computing
• Multimedia Content Processing
• Social Networking Technologies
• +3 more

Theodora Varvarigou is a Professor in the Department of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). She holds a B.Eng. from NTUA and M.Eng. and Ph.D. degrees from Stanford University. Her career includes research at AT&T Bell Labs and roles at the Technical University of Crete. From 2008-2012, she served as director of NTUA's 'Technoeconomic Systems' postgraduate program. Her research focuses on Cloud Computing, Multimedia Content Processing, Social Networking Technologies, and emerging areas like blockchain, edge computing, and cybersecurity. She has published over 200 papers and led numerous European research projects, emphasizing scalable systems, data management, and smart infrastructure applications. Her work spans technical innovations such as intrusion detection systems, edge resource optimization, and blockchain-based solutions for IoT, healthcare, and smart cities. Recent publications highlight advancements in AI-driven resource allocation, privacy-preserving blockchain designs, and predictive analytics for edge computing environments. Professor Varvarigou has contributed to interdisciplinary initiatives, including cohort data harmonization in biomedical research and social media analytics for urban planning. Her teaching includes courses on digital systems, network programming, and fault-tolerant systems.

• Multicore Computing
• Virtualization
• Cloud Computing
• +4 more

Xiaoning Ding is an Associate Professor in the Department of Computer Science at New Jersey Institute of Technology (NJIT). His research focuses on virtualization, multicore computing, cloud infrastructure optimization, and mobile systems. He leads projects addressing challenges in nested virtualization, memory management, and cache conflicts in distributed and cloud environments. Key research interests include optimizing task scheduling in cloud VMs, reducing TLB misses through huge page strategies, and mitigating interference in multi-tenant GPU clouds. His work on page placement mechanisms and dynamic page coalescing aims to enhance virtualized cloud performance. Ding has received federal funding, including an NSF grant for virtualization research in heterogeneous memory hierarchies (2016–2019). His research outputs span over 74 publications, with notable contributions in EuroSys, IEEE Transactions, and conferences like PACT. Media coverage highlights his studies on cloud computing and collaborative mobile systems, such as parking assignment algorithms. Beyond technical contributions, Ding advises students in interdisciplinary projects, exemplified by collaborations with Applied Math majors on cloud computing challenges.

Shiva JahangiriView profile

Assistant Professor

• Big Data Management Systems
• Databases for AI/ML
• Knowledge Graphs
• +6 more

Shiva Jahangiri is an Assistant Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering. His research focuses on Big Data Management Systems, Databases for AI/ML, and Query Optimization. He leads the DBIS Lab, which explores database internals, vectorized data processing, and open-source projects like Apache AsterixDB. Education: Ph.D. in Computer Science from the University of California, Irvine; M.S. in Computer Science (Data Science) from the University of Southern California. Current courses taught include Advanced Programming, Advanced Database Systems, and Introduction to Database Systems. He advises Ph.D. and Master’s students on topics like Vector Databases, Query Scheduling, and Resource Management. Recent research trends involve optimizing group-by/aggregation operators, schema inference for semi-structured data, and memory management in complex join queries. His work bridges theoretical advancements with practical implementations in open-source systems. DBIS Lab activities include student participation in senior design projects, directed research, and volunteer roles. The lab emphasizes industry collaboration for hands-on experience in database systems development.

Bill HoweView profile

Associate Professor

• Data Science
• Algorithmic Fairness
• Urban Computing
• +7 more

Bill Howe is an Associate Professor at the University of Washington's Information School, with adjunct appointments in Computer Science & Engineering and Electrical Engineering. He serves as Founding Program Director and Faculty Chair of the UW Data Science Masters Degree, Founding Associate Director and Senior Data Science Fellow at the UW eScience Institute, Director of the Urbanalytics Lab, and Co-Founding Director of the Center for Responsible AI Systems and Experiences. He also co-founded Urban@UW and created the first Data Science MOOC through Coursera. His research focuses on making data science accessible in public sector applications with emphasis on equity, privacy, and compliance. Current interests include: Algorithmic fairness in urban and social contexts Privacy-preserving synthetic data generation Machine learning for heterogeneous data Database systems and high-performance computing Human-computer interaction for data systems Responsible AI development and deployment Publication analysis reveals strong focus on responsible data science, with recent work emphasizing differential privacy, COVID-19 data equity, urban mobility fairness, and relational data systems. Earlier foundational work established contributions to scientific workflow systems and data pricing models. Awards and Honors: Runner-up Best Paper Award (VLDB 2023) Best Paper Award (SIGMOD 2019) Best Paper Award (VIs 2019) Best Paper Award (InfoVis 2018) He leads the Urbanalytics Lab and advises multiple students including An Yan (fairness in urban mobility), Sean Yang (machine learning embeddings), and Dominik Moritz (visualization systems). His projects span EZLearn for automatic claim validation, privacy-preserving synthetic data, and Myria middleware for polystores.

Al Amjad Tawfiq IsstaifView profile

Researcher

• Cloud and Edge Computing
• Microservices and Serverless
• Operating Systems and Middleware
• +5 more

Al Amjad Tawfiq Isstaif is a Research Associate in the Systems Research Group (SRG) at the Department of Computer Science and Technology (also known as "The Computer Lab") at the University of Cambridge, working with Professor Richard Mortier. He is a member of Clare College. In 2018, he was awarded the Said Foundation Cambridge Scholarship to study the MPhil in Advanced Computer Science (ACS) at the Computer Lab. Before moving to Cambridge, he co-founded several projects for empowering engineering students in Syria, including the award-winning education enterprise: Wikilogia. His research interests include: Cloud and Edge Computing Microservices and Serverless Operating Systems and Middleware Networked and Distributed Systems Machine Learning Systems Human-Centred Computing Machine Learning and Artificial Intelligence Systems and Networking Isstaif's primary research focus is on building self-scaling network services on top of next generation infrastructure (IoT/5G/edge), leveraging lightweight virtualization techniques and distributed tracing. His work falls under the Compute First Networking research project. He has deep passion for social entrepreneurship and the role of digital infrastructure in addressing development and sustainability challenges across the globe. His technical expertise bridges the IT and telecom worlds, with emphasis on cloud-native and open source movements shaping future infrastructure. His recent publications demonstrate a strong focus on optimizing serverless computing environments, with particular attention to scheduling algorithms, resource management, and latency optimization in Linux-based systems. The trajectory of his work shows progression from database performance modeling to cutting-edge research in edge computing and network infrastructure. Notable awards and recognitions: Said Foundation Cambridge Scholarship (2018) Co-founded Wikilogia, an award-winning education enterprise for engineering students in Syria Isstaif has teaching experience in Operating Systems (LT 2021) and maintains an active research profile within the Systems Research Group. His work connects theoretical computer science with practical applications in cloud infrastructure, particularly focusing on how these technologies can serve broader societal needs in developing contexts. He is located in Room FN07 at the William Gates Building, 15 JJ Thomson Avenue, Cambridge CB3 0FD.

• Database Systems
• Distributed Computing
• Cloud Computing
• +2 more

Bettina Kemme is a faculty member at McGill University in Montreal, Canada. Her research focuses on database systems , distributed computing , and cloud data management . She has made significant contributions to database replication, consistency models, and middleware frameworks for scalable applications. Research Themes : Database replication, distributed systems, cloud computing, and software engineering. Notable Collaborations : Jörg Kienzle, Joseph Vinish D'silva, Yunjia Zheng, and Marta Patiño-Martínez. Publications span critical areas such as graph database view management, transactional recovery in key-value stores, and latency-aware publish/subscribe systems. Her work is published in venues like VLDB , ICDE , Middleware , and SRDS .

Robert SouléView profile

Associate Professor

• Distributed Systems
• Networking
• Programming Languages
• +4 more

Robert Soulé is an Associate Professor in the Departments of Computer Science and Electrical Engineering at Yale University, and holds an Adjunct Professor position at the Università della Svizzera italiana (USI) in Lugano, Switzerland. His research focuses on distributed systems, networking, and applied programming languages, with notable contributions to in-network computing, consensus protocols, and energy-efficient systems. He received his B.A. from Brown University and his Ph.D. from New York University, followed by postdoctoral work at Cornell University. Education: B.A. in Computer Science, Brown University, 1999 Ph.D. in Computer Science, New York University, 2012 Research Interests: Dr. Soulé’s work spans distributed systems, networking, and programming languages, emphasizing practical systems such as in-network computing, consensus algorithms (e.g., NetPaxos), and carbon-aware networking. His research bridges theory and practice, addressing challenges in scalability, performance, and sustainability. Articles Trends: Recent work includes innovations in quantum networks (algebraic specifications), carbon-aware networking (energy efficiency), and system optimization (e.g., P4-based data plane verification). He explores network programmability, microservices acceleration, and zero-copy serialization techniques. Awards: Best Paper Awards at ACM DEBS 2012, NSDI 2018, and CoNEXT 2020 Google Faculty Research Award IBM Invention Plateau Award Advising and Grants: He has advised numerous PhD students and postdocs, including Pietro Bressana (Intel Corporation) and Theo Jepsen (Stanford Postdoc). His grants support projects in networked systems, distributed computing, and sustainable infrastructure. Labs/Teams: Active in Yale’s Systems Research group, collaborating on projects like NetChain (sub-RTT coordination) and P4-based systems (e.g., P4xos for consensus). Engages with industry through partnerships on microservices optimization and energy-efficient networking.