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Matthew HertzView profile

Teaching Professor

• Computer science education
• runtime systems
• dynamic memory management

Matthew Hertz is a Teaching Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His research focuses on computer science education, runtime systems, and dynamic memory management. Education: PhD, Computer Science, University of Massachusetts Amherst, 2006 MS, Computer Science, University of Massachusetts Amherst, 2001 BA, Computer Science, Carleton College, 1997 Research interests span computer science education and systems optimization. His educational research investigates learning factors in introductory programming courses, develops pedagogical tools like CloudCoder for programming exercises, and analyzes failure rates in CS1 courses. In systems research, he focuses on memory management innovations including garbage collection algorithms, adaptive resource allocation, and performance optimization in shared environments. Publications show dual focus: recent work emphasizes educational data analysis and programming pedagogy while earlier research concentrates on memory management efficiency and runtime systems. Trends include automated assessment tools and adaptive algorithms for resource-constrained environments. No scientific awards reported. No advising or grant information available. No labs or teams mentioned in available data.

Stefan MarrView profile

Researcher

• Concurrent Programming
• Language Implementation
• Virtual Machines
• +6 more

Stefan Marr is a faculty member at the University of Kent, United Kingdom, focusing on Concurrent Programming , Language Implementation , and Virtual Machines . His research spans projects like optimizing interpreters, improving concurrency models, and enhancing profiling tools for dynamic languages. Projects : Royal Society Industry Fellowship (FastStart), EPSRC-funded CaMELot, Oracle Labs-funded Automatic Superinstructions. Collaborations : With students and researchers across institutions, including Shopify, Vrije Universiteit Brussel, and Johannes Kepler University Linz. His recent work emphasizes profiling reliability for Java, interpreter performance , and tooling for complex concurrent systems . Projects like SOM (Simple Object Machine) and its variants (SOM++, TruffleSOM, PySOM) highlight his commitment to language implementation research and education. Scientific Awards include fellowships and grants from the Royal Society, EPSRC, and Oracle Labs. His contributions to conferences as program committee member , steering committee , and workshop organizer further underscore his academic leadership.

• Database Systems
• Distributed Systems
• Machine Learning Systems
• +3 more

Tim Kraska is an Associate Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), affiliated with the Computer Science and Artificial Intelligence Laboratory (CSAIL) within the School of Engineering. His research spans foundational areas in modern data systems: Database Systems Distributed Systems Machine Learning Systems Learned Indexes Cloud Databases Dr. Kraska pioneers the integration of machine learning into core database components, developing "learned systems" that replace traditional algorithms with ML models for significant performance gains. His work on learned indexes redefined indexing paradigms, while recent research extends this approach to garbage collection, query optimization, and concurrency control. His publication trends reveal a strategic shift toward applying ML to low-level systems problems, particularly in memory management and runtime optimization as demonstrated by his PLDI 2020 paper on Learned Garbage Collection. Award highlights include: ACM SIGMOD Jim Gray Doctoral Dissertation Award VLDB Early Career Research Contribution Award Marie Curie Fellowship At MIT, he leads a research group focused on next-generation data systems, securing grants from NSF and industry partners to explore the theoretical and practical boundaries of learned components in database engines. His team collaborates extensively with industry research labs on real-world deployment challenges. As a core member of CSAIL's distributed systems group, he contributes to MIT's leadership in reimagining data infrastructure for the AI era through cross-lab initiatives on scalable machine learning systems.

Manos AthanassoulisView profile

Associate Professor

• Data Systems
• Cloud Data Management
• Database Systems
• +7 more

Manos Athanassoulis is an Associate Professor in the Department of Computer Science at the College of Arts and Sciences, Boston University. He is the Founder and Director of the BU Data-intensive Systems and Computing (DiSC) lab and a member of the BU MiDAS group. His research focuses on data systems, particularly cloud data management, hybrid transactional/analytical workloads, and integration with emerging hardware such as non-volatile memory and heterogeneous computing. His educational background includes a PhD from EPFL (2014), an MSc in Computer Systems Technology, and a BSc in Informatics and Telecommunications from the University of Athens, Greece. Prior to BU, he was a Postdoctoral Researcher and Research Associate at Harvard University, supported by a SNSF Postdoc Mobility Fellowship. His research interests span data systems, database architectures, LSM trees, indexing, storage systems, and performance optimization. He explores how novel hardware can be leveraged to improve data management efficiency and scalability, especially in cloud environments. His recent publications (2021–2025) predominantly focus on LSM trees, covering topics such as compaction policies, Bloom filter tuning, DPU offloading, adversarial resilience, and sustainable caching. Earlier works include foundational contributions on access methods (RUM Conjecture) and optimal key-value stores (Monkey). The trend shows a consistent focus on data system efficiency, adaptability, and robustness under varying workloads and hardware constraints. Scientific Awards: NSF CAREER Award (2022) Facebook Faculty Research Award (2020) NSF CRII Award (2019) Best of VLDB 2017 and Best of SIGMOD 2017 SIGMOD Most Reproducible Paper Award (2017) Multiple ACM SIGMOD Distinguished PC Member recognitions (2018–2025) VLDB 2023 Best Demo Award RedHat Collaboratory Research Incubation Awards (multiple, 2021–2023) SNSF Postdoc Mobility Fellowship (2015–16) IBM PhD Fellowship (2011–12) Dr. Athanassoulis has advised numerous students and collaborators, evident from his co-authorship on works with researchers such as Niv Dayan, Stratos Idreos, and A. Ailamaki. His grants include major awards from NSF, Facebook, and RedHat, supporting research in robust data systems, hardware-software co-design, and learned cost models. He has also been recognized for teaching excellence at Harvard University. He leads the DiSC lab at Boston University, which focuses on data-intensive computing and systems research. The lab explores next-generation data architectures, particularly in cloud and hardware-aware environments. Collaborations with the BU MiDAS group enhance interdisciplinary research in data science and AI.

• Programming Languages
• Formal Verification
• Concurrent and Parallel Systems
• +10 more

Professor Sophia Drossopoulou is a Professor of Programming Languages in the Department of Computing at Imperial College London, part of the Faculty of Engineering. Her affiliations include the Centre for Cryptocurrency Research and Engineering and the Sound Programming Languages research group. She holds a visiting researcher position at Microsoft Research (UK) from May 2019 to May 2020. Her research focuses on foundational programming language design and formal methods, emphasizing concurrency, type systems, and program verification. Key areas include concurrent program reasoning (e.g., TaDA framework), memory management (reference capabilities, garbage collection), and secure systems (smart contracts, cyber-physical systems). She explores practical language extensions for performance optimization (e.g., cache locality) while maintaining safety guarantees through formal verification techniques. Her work spans theoretical contributions (formal semantics, logical frameworks) and applied systems (compilers, runtime verification tools like Zeno). Recent trends show strong engagement with actor-based models (Pony language), digital twins, and cybersecurity challenges in modern software systems. Awards and recognitions are not explicitly listed in the provided text, but her extensive publication record in top venues (ECOOP, POPL, TOPLAS) indicates academic impact. Her advising focuses on graduate students in systems programming and formal methods, though specific student names are not mentioned here. Labs and collaborations involve the Sound Programming Languages group at Imperial College, emphasizing interdisciplinary work between formal methods and practical language implementation. Current projects include improving concurrency semantics and verifying complex systems through compositional reasoning techniques.

Roel BlooView profile

Lecturer

• Computer Science
• Theoretical Computer Science
• Formal Methods
• +2 more

Roel Bloo is a University Lecturer in the Department of Mathematics and Computer Science at Eindhoven University of Technology. His research group focuses on Algorithms and Logics for Verification. His research spans theoretical computer science with emphasis on: Formal methods and verification techniques Lambda calculus and type systems Computational logic and term rewriting Explicit substitution models Publications (2001-2012) demonstrate consistent specialization in foundational aspects of computer science, particularly formal semantics of programming languages, type theory implementations, and equivalence proofs in computational systems. Teaching responsibilities include courses in Discrete Mathematics, Logic and Set Theory, and Automata Theory.

James ClauseView profile

Associate Professor

• Software Engineering
• Testing
• Program Analysis
• +5 more

James Clause is an Associate Professor and Graduate Program Chair in the Department of Computer and Information Sciences at the University of Delaware. His research focuses on advancing software engineering practices through innovative work in testing, program analysis, and energy-efficient software development. His educational background includes: PhD in Computer Science from Georgia Institute of Technology (2011) MS in Computer Science from University of Pittsburgh (2005) BS in Computer Science from Allegheny College (2003) Clause specializes in improving software quality and developer productivity. His research investigates dynamic analysis techniques for bug detection, memory leak identification, and security vulnerability analysis. He pioneers energy-aware software engineering, developing methods to optimize application energy consumption and test suite efficiency. His work on privacy-preserving field data usage enables safer handling of sensitive user information while maintaining software quality. Current projects focus on energy-efficient application development, durable test creation, and privacy-conscious software improvement. His publication trajectory reveals a clear evolution from foundational security and memory analysis toward energy-conscious software engineering. Early work established critical dynamic taint analysis frameworks (e.g., Dytan), while recent research addresses energy consumption in web applications and test optimization. This shift demonstrates growing industry relevance of sustainable computing practices within software engineering. His scientific contributions are recognized through prestigious awards: ISSTA 2017 Impact Paper Award for seminal work on dynamic taint analysis ICSME 2016 Distinguished Reviewer Award for exceptional peer review contributions Clause actively mentors graduate students including Tedis Agoli, Emily Evans, Daniel Gaston, and Benwen Zhang. His research is supported by grants focused on energy-efficient development, high-quality testing methodologies, and privacy-preserving data usage. He serves the academic community through program committee roles for ICST 2018 and ICSE 2018, demonstrating leadership in software testing and engineering conferences. His research group operates within the University of Delaware's Department of Computer and Information Sciences, contributing to the institution's reputation in software engineering innovation through continuous exploration of energy-aware development and advanced debugging techniques.

Miryung KimView profile

Professor

• Software Engineering
• Software Engineering for Data Intensive Computing
• Automated Testing
• +7 more

Miryung Kim is a Professor and Vice Chair of Graduate Studies in UCLA's Computer Science Department, where she directs the Software Engineering and Analysis Laboratory. She is renowned for her pioneering work in software evolution, code clone management, and establishing the emerging field of Software Engineering for Data Intensive Computing (SE4DA and SE4ML). Her research focuses on automated testing and debugging for Apache Spark, developer tools for heterogeneous computing, and conducting systematic studies of refactoring practices in industry. She led the first large-scale study of data scientists in industry and developed JDebloat, a Java bytecode debloating tool that made significant tech transfer impact to the Navy. Her recent publications demonstrate strong trends in fuzz testing for big data analytics and heterogeneous computing, with a focus on natural input generation, co-dependence awareness, and leveraging hardware probes for acceleration. Her work bridges software engineering with data-intensive and heterogeneous computing paradigms. ACM SIGSOFT Influential Educator Award (2022) ICSME Most Influential Paper Award (2023 and 2020) NSF CAREER award Google Faculty Research Award Okawa Foundation Research Award Humboldt Fellow ACM Distinguished Member As an academic advisor, she has produced eight tenure-track faculty members at institutions including Columbia, Purdue, and Virginia Tech. Her research has been supported by National Science Foundation, Air Force Research Laboratory, Google, IBM, Intel, Okawa Foundation, Samsung, and Office of Naval Research. She previously served as Program Co-Chair of ESEC/FSE 2022 and has delivered keynotes at ASE 2019 and ISSTA 2022. She maintains active industry collaborations, serving as an Amazon Scholar at Amazon Web Services and having spent time as a visiting researcher at Microsoft Research.

Tali MoreshetView profile

Academic

• Computer Architecture
• Energy-efficient Computing
• Hardware-Software Co-design
• +2 more

Tali Moreshet is a Research Assistant Professor in the Department of Electrical & Computer Engineering at Boston University. Her primary appointment is as a Master Lecturer, reflecting her dual focus on teaching and research. She is affiliated with the College of Engineering and holds a PhD from Brown University (2006). Her research interests include computer architecture, energy-efficient computing, hardware-software co-design, near-data processing, and embedded systems. Dr. Moreshet has received notable awards including the Senior Member distinction from ACM, the ECE Department Teaching Award (2017), a Best Paper Award at SAMOS XIV (2014), and an NSF BRIGE Award (2009). She teaches core courses such as Introduction to Logic Design (EC 311), Advanced Data Structures (EC 504), and Computer Architecture (EC 513). Her work emphasizes energy efficiency in embedded systems and transactional memory implementations. Recent research explores hardware acceleration for garbage collection and near-memory processing architectures. She also investigates voltage noise mitigation and concurrency control mechanisms in embedded multi-core systems. Moreshet has contributed to collaborative NSF projects on durable data structures for non-volatile memory and energy-efficient speculation in NUMA architectures. Her publications span 20+ years, with a focus on embedded systems, transactional memory, and parallel computing optimizations.

Gustavo Adolfo Junipero Rodriguez-RiveraView profile

Academic

• Operating Systems
• Computer Networks
• Memory Management
• +11 more

Gustavo Rodriguez-Rivera is an Associate Teaching Professor in the Department of Computer Science at Purdue University, part of the School of Science. He joined the department in 2000 and holds a Ph.D. in Computer Science from Purdue University (1998), an M.S. in Electrical Engineering from ITESM Campus Monterrey (1990), and a B.S. in Electrical Engineering from the same institution (1985). His research focuses on Operating Systems, Computer Networks, Memory Management, Embedded Systems, Real-Time Systems, and broader areas like Numerical Analysis and Artificial Intelligence. Dr. Rodriguez-Rivera has received multiple teaching awards, including the ACM Faculty Award in Computer Science (2020, 2023) and Best Teacher in the School of Science (2014, 2016). His work spans software engineering education, structural health monitoring for wind turbines, and memory management algorithms. Notable publications include studies on garbage collection techniques, real-time project tracking in programming courses, and vibro-acoustic modulation for turbine blade inspection. He has advised numerous projects and contributed to grants such as the NSF-funded work on wind turbine blade monitoring. His academic contributions also include developing secure programming course modules and tools for interactive debugging systems.

• Distributed/Parallel Computing
• Information Visualization
• Fault-Tolerant Communication Mechanisms
• +4 more

Philippas Tsigas is a Professor at the Department of Computer Science and Engineering at Chalmers University of Technology. He leads the Distributed Computing and Systems Research Group and has held roles as co-leader of research initiatives such as the PEPPHER project. His research spans distributed/parallel computing, information visualization, and fault-tolerant communication mechanisms. He has supervised numerous PhD students, including Yi Zhang, Håkan Sundell, and Farnaz Moradi. Research interests include lock-free data structures, multicore algorithms, secure network services, and visualization tools like Lydian and DataMeadow. Notable awards include Best Paper Awards at IPDPS 2003 and SNS 2012. His work has been published in top venues like IEEE Transactions on Parallel and Distributed Systems and ACM Journal of Experimental Algorithmics. Awards highlight contributions to lock-free algorithms and network modeling. Students have contributed to projects like NBmalloc (memory reclamation) and GPU Quicksort. Collaborations with institutions like SSF and VR have supported his research. Tsigas is also involved in teaching distributed systems and mentoring early-career researchers.

Kartik NagarView profile

Assistant Professor

• Automated Formal Verification
• Program Analysis
• Programming Languages
• +4 more

Kartik Nagar is an Assistant Professor at the Department of Computer Science and Engineering, IIT Madras . He specializes in developing verification and analysis techniques to enhance the reliability, security, and efficiency of computer systems, focusing on concurrent and distributed systems, computer architecture, and real-time systems.

Yuanchao XuView profile

Assistant Professor

• Computer Architecture
• Security
• Machine Learning Systems
• +3 more

Yuanchao Xu is an Assistant Professor in the Department of Computer Science and Engineering at the University of California Santa Cruz. He earned his Ph.D. from North Carolina State University, advised by Dr. Xipeng Shen and Dr. Yan Solihin, and is a student researcher at SystemResearch@Google since 2021. His research spans computer architecture, security, and ML systems.

Stephen A. EdwardsView profile

Associate Professor

• Embedded Systems
• Real-Time Systems
• Hardware Synthesis
• +5 more

Stephen A. Edwards is an Associate Professor at the Computer Science Department of Columbia University , where he explores automating software for embedded systems and real-time control . His work focuses on compiler techniques for languages like Esterel and domain-specific solutions for device drivers and communication protocols . Education : PhD in Electrical Engineering, University of California, Berkeley (1997) MS in Electrical Engineering, UC Berkeley (1994) BS in Electrical Engineering, California Institute of Technology (1992) Research Interests span hardware synthesis , functional programming , and synchronous languages . He develops domain-specific languages to bridge software and hardware, emphasizing determinism and timing precision in embedded systems. His group's work includes projects like the FHW compiler and the Sparse Synchronous Model . Article Trends show a focus on FPGA-based systems , garbage collection for accelerators, and parallel functional programming . These reflect his broader interests in hardware-software co-design and compiler optimization for real-time applications. Students : John Hui (2021-2024, Apple) Max Levatich (2020-) Richard Townsend (2013-2019, Tufts) Nalini Vasudevan (2007-2011, Google) Marcio Buss (2004-2008) Jia Zeng (2002-2008) Cristian Soviani (2002-2007, Synopsys) Consulting & Expert Services : He provides litigation support and expert witness services in patent cases involving software architecture and computer design , including ITC cases. Labs & Projects : Leads research on sparse synchronous systems and hardware synthesis , with initiatives like the GAPS CLOSURE Project and FHW Compiler for translating Haskell to System Verilog.

Nikolaos PapaspyrouView profile

Professor

• Programming Languages
• Software Engineering
• Formal Verification
• +4 more

Nikolaos Papaspyrou is a Professor at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA) and a member of the Software Engineering Laboratory . His research focuses on the theory and implementation of programming languages, including semantics, type systems, compilers, static analysis, and formal verification. Since October 2021, he has been on leave from NTUA, working as a Software Engineer for Google in the memory management team for the V8 JavaScript and WebAssembly engine. He previously served as Director of the Division of Computer Science (2017-2019) and was on sabbatical with Google's compiler group in Munich (2015-2016). His work includes the RELEASE project (EU FP7 STREP) for reliable large-scale server software and uncertainty handling in distributed databases (European Social Fund). Ph.D. and Diploma in Electrical and Computer Engineering from NTUA M.Sc. in Computer Science from Cornell University His research interests span programming languages , software engineering , and formal verification , with recent publications on coinductive proofs in Liquid Haskell, concurrency semantics, and quantum compilation. He has supervised over 50 diploma projects and mentored numerous students now at institutions like MIT, Princeton, and UC Berkeley. Awards include conference organizing and program committee roles, though no formal scientific prizes are listed.