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Stephen ChongView profile

Professor

• Programming languages
• Information security
• Language-based security
• +3 more

Stephen Chong is a Gordon McKay Professor of Computer Science in the Harvard John A. Paulson School of Engineering and Applied Sciences, where he serves as Co-Director of Undergraduate Studies for Computer Science. His academic career spans over a decade of teaching and research at Harvard, where he has made significant contributions to programming languages and information security. Chong received his PhD from Cornell University under the guidance of Andrew Myers, and a bachelor's degree from Victoria University of Wellington, New Zealand. Prior to graduate school, he worked as a consultant and contractor in the software industry, bringing practical experience to his academic research. Professor Chong's research focuses on language-based information security, using programming language techniques to provide information security assurance. His work bridges the gap between theoretical foundations and practical applications, developing tools and frameworks that help programmers write trustworthy programs. His research has evolved to address increasingly complex security challenges in modern computing environments, from web applications to cyber-physical systems. His recent publications reveal a strong trend toward integrating advanced programming language techniques with security analysis, particularly through the use of Datalog, SMT solvers, and program synthesis. His work on Formulog has been particularly influential, extending Datalog with mechanisms to construct and reason about SMT formulas for static analysis. His research has expanded to address security challenges in cyber-physical systems, where sensor attacks pose unique threats to safety-critical infrastructure. Chong has received numerous prestigious awards including an NSF CAREER award, an AFOSR Young Investigator award, and a Sloan Research Fellowship. He has also served in leadership roles for major conferences including CSF 2012-2013, PLMW @ PLDI 2021, and as SIGPLAN-M Chair for 2025-2026. As an educator, Chong has mentored numerous students through Harvard's undergraduate research programs and has served as a thesis advisor. His teaching portfolio includes foundational courses like CS51, systems courses like CS61, and advanced topics in programming languages (CS152) and compilers (CS1530). He has been instrumental in shaping Harvard's computer science curriculum, particularly in security and programming languages. Chong leads a research group focused on language-based security, with projects including Formulog (for SMT-based static analysis), PRINCESS (for autonomous adaptation of software), and work on secure shell scripting (Shill). His group collaborates with researchers across Harvard and other institutions to tackle challenging problems at the intersection of programming languages and security.

Sang-Hoon KimView profile

Associate Professor

• Operating Systems
• Memory Systems
• Storage Systems
• +4 more

Sang-Hoon Kim is an Associate Professor in the Department of Software and Computer Engineering and Department of Artificial Intelligence at Ajou University, South Korea. He leads the Systems Software Lab (Paldal Hall 1004-2) and maintains active collaborations with Virginia Tech as a Visiting Scholar since August 2024. His academic journey includes a Ph.D. in Computer Science from KAIST (2016) under advisors Seungryoul Maeng and Jin-Soo Kim, and a B.S. in Computer Science from KAIST (2002). His research spans operating systems, memory management, and storage systems with focus on mobile platforms, heterogeneous architectures, and SSD technologies. Key interests include memory fragmentation control , distributed thread execution , key-value storage optimization , and resource disaggregation . His work bridges theoretical innovation with practical system implementations, particularly for mobile and datacenter environments. Kim's publication portfolio shows consistent output in top-tier venues including USENIX FAST, VLDB, ICDCS, and ASPLOS. His research demonstrates evolution from mobile memory management (2015-2017) toward distributed systems and hardware-aware software (2019-present), with recent emphasis on resource-disaggregated environments and heterogeneous-ISA computing. The 2024 Best Paper Award at USENIX FAST highlights his impact in storage systems research. Best Paper Award at USENIX FAST'24 Multiple patents including US-9588912B2 for memory control He directs significant research projects funded by ETRI, NRF, and US ONR, including current work on memory-centric computing systems (2020-2023) and disaggregated non-volatile memory systems using RDMA (2018-2020). His Systems Software Lab maintains strong industry partnerships with Samsung Electronics and NHN, with prior projects improving Android memory management and developing SSD-based storage systems for large-scale internet services.

Anil MadhavapeddyView profile

Professor

• Planetary Computing
• Computer Systems
• Programming Languages
• +7 more

Anil Madhavapeddy is the Professor of Planetary Computing at the University of Cambridge Computer Laboratory, where he co-leads the Energy & Environment Group and is a member of the Systems Research Group. He is also a Fellow at Pembroke College where he serves as Director of Studies in Computer Science. Madhavapeddy completed his PhD from the University of Cambridge in 2003 and his BEng in Information Systems Engineering from Imperial College in 1999. He holds a JM Keynes Fellowship since 2022 for his work combining computer science with economics, and serves on the management committee of the Cambridge Conservation Initiative where he co-directs 4C (Cambridge Centre for Carbon Credits) and the Centre for Earth Observation. His research spans computer systems and programming languages with a strong focus on applying these technologies to global conservation, biodiversity, and climate change challenges. He leads the OCaml Labs group and has made significant contributions to open-source projects including OCaml, Docker, Xen, and OpenBSD. His work often bridges computer science with environmental science, developing computational approaches to address planetary-scale challenges. Madhavapeddy's recent publications demonstrate a clear trajectory toward integrating programming language research with environmental monitoring and conservation. His work spans from foundational programming language techniques to applied geospatial computing systems, with increasing emphasis on biodiversity measurement, carbon credit systems, and planetary-scale environmental monitoring. JM Keynes Fellowship (2022-present) As an educator, Madhavapeddy teaches undergraduate courses including Foundations of Computer Science, Software & Security Engineering, and Cloud Computing. He mentors MPhil and PhD students and co-founded the award-winning book 'Real World OCaml' (2nd Edition, 2022). He has co-founded several companies including Unikernel Systems, High Energy Magic, Segfault, and Tarides to translate research into real-world impact. Madhavapeddy leads the OCaml Labs group at Cambridge and works closely with the Energy & Environment Group, collaborating with colleagues from Plant Sciences, Zoology, Economics, and NGOs including UNEP-WCMC and the IUCN. His current efforts are primarily focused on conservation technology through partnerships with organizations like Canopy PACT.

Sidi Mohamed BeillahiView profile

Lecturer

• Formal Verification
• Programming Languages
• Smart Contracts
• +4 more

Sidi Mohamed Beillahi is a Lecturer in the Department of Computer Science at the University of Toronto's Faculty of Arts and Science. He teaches courses including Principles of Programming Languages (CSC324H1S) and Algorithms and Data Structures (ECE345H1F). Previously, he served as a Teaching Assistant at both University of Paris and Concordia University for courses ranging from Automata Theory to Hardware Functional Verification. Dr. Beillahi's research focuses on developing formal verification and programming languages techniques to ensure the correctness of software systems, particularly distributed systems, concurrent programs, blockchain, and smart contracts. His work bridges theoretical computer science with practical security applications in decentralized finance. His publication record shows a clear progression from quantum circuit verification during his Master's to blockchain and smart contract security in his doctoral and postdoctoral work. Recent publications demonstrate expertise in authenticated data structures for blockchain storage, flash loan attack analysis, and formal verification of decentralized applications. Scientific Awards: ACM SIGSOFT Distinguished Paper Award (ICSE '24) ICBC Distinguished Paper Award (ICBC '22) Dr. Beillahi has advised multiple research projects in blockchain security and verification, often collaborating with Professor Fan Long and Professor Andreas Veneris at the University of Toronto. His research has been supported by prestigious fellowships including an NSERC Postdoctoral Fellowship and a Mitacs Accelerate Fellowship.

Mayur NaikView profile

Professor

• Programming Languages
• Artificial Intelligence
• Neurosymbolic Programming
• +5 more

Mayur Naik is the Misra Family Professor in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science. He holds office in Room 642B, Amy Gutmann Hall and maintains an active research program focused on the intersection of programming languages and artificial intelligence. Before joining UPenn, he was faculty at Georgia Institute of Technology and a researcher at Intel Labs, Berkeley. Naik received his PhD in Computer Science from Stanford University in 2008 under Alex Aiken, a Masters from Purdue University in 2003 under Jens Palsberg, and a Bachelors from BITS Pilani in 1999. He grew up in Goa, India. His primary research interests center around neurosymbolic programming, which combines symbolic reasoning with machine learning to create more accurate, interpretable, and domain-aware AI systems. His group develops language design, learning algorithms, and compiler optimizations in this space, with their most mature effort being the Scallop neurosymbolic programming language and compiler toolchain. He also conducts research in trustworthy AI for healthcare applications and AI-enabled programming tools that improve programmer productivity. Analysis of his recent publications shows a strong trend toward neurosymbolic programming frameworks (Scallop, TorchQL), LLM-assisted program analysis (IRIS), and applications of these techniques to security, healthcare, and computer vision. His work consistently bridges theoretical foundations with practical implementations, often releasing open-source systems. Misra Family Professor (endowed chair, effective July 2024) Multiple distinguished paper awards (PLDI 2019, FSE 2015, PLDI 2014) Test-of-Time Paper Awards (FSE 2013, FSE 2012, EuroSys 2011) His student Elizabeth Dinella won the 2025 ACM SIGSOFT Outstanding Dissertation award Naik has advised numerous PhD students who have gone on to faculty positions at top institutions including Peking University, University of Toronto, Ashoka University, Bryn Mawr College, and Johns Hopkins University. His research is supported by grants from NSF, Google, Amazon, and other industry partners. His lab maintains active collaborations with clinicians and bioinformatics researchers to apply neurosymbolic programming to healthcare problems. His research group, which includes current PhD students and postdocs, develops practical open-source systems and applies them to diverse domains including computer vision, cybersecurity, medicine, and bioinformatics. The group maintains strong industry connections with Google, Microsoft, Amazon, and other tech companies.

Maria HalkidiView profile

Associate Professor

• Data Mining
• Machine Learning
• Recommender Systems
• +6 more

Maria Halkidi is an Associate Professor in the Department of Digital Systems at the University of Piraeus, Greece, where she conducts cutting-edge research in data mining and machine learning with over two decades of academic experience. Her educational background includes: Bachelor's degree in Informatics from the University of Piraeus (1997) Master's degree from Athens University of Economics and Business (1999) Ph.D. from Athens University of Economics and Business (2003) Dr. Halkidi's research focuses on fundamental and applied aspects of data mining, particularly recommender systems, graph data mining, cluster validity assessment, and distributed data mining. Her work bridges theoretical frameworks with practical implementations in sensor networks, social media, and real-time analytics, contributing significantly to algorithmic development in these domains. Analysis of her recent publications reveals a strong trajectory toward fairness and diversity optimization in recommender systems, alongside innovative approaches to graph clustering quality assessment and scalable sentiment analysis. Her research consistently addresses real-world challenges in dynamic data environments, with increasing emphasis on multi-stakeholder optimization and privacy-aware recommendation frameworks. Scientific awards: No specific awards or honors were documented in the provided materials. Dr. Halkidi has participated extensively in National and European-funded research projects, including a prestigious Marie-Curie fellowship at the University of California, Riverside. She serves on program committees for major international conferences in data mining and machine learning, demonstrating active community engagement. While specific graduate students aren't listed in the source materials, her professorial role indicates ongoing mentorship of Master's and Ph.D. candidates. She maintains active research affiliations with the Network oriented systems & services lab and the DataStories research group at the University of Piraeus, where she collaborates on interdisciplinary projects involving big data analytics, social network analysis, and distributed systems.

• Entity Resolution
• Record Linkage
• Privacy-Preserving Record Linkage
• +3 more

Dimitrios Karapiperis serves as an Academic Scholar at the School of Science and Technology, International Hellenic University (IHU), specializing in Entity Resolution and Privacy-Preserving Record Linkage. Previously, he held a post-doctoral position at the Hellenic Open University. He earned his PhD from the Hellenic Open University and his MSc from the University of York (UK). His doctoral thesis was featured in the IEEE Intelligent Informatics Bulletin of August 2017, highlighting its significance in the field. Dr. Karapiperis' research centers on developing advanced algorithms for entity resolution, including similarity measures, data structures, and scalable distributed solutions using randomization techniques. His work extends to privacy-preserving methods for record linkage with applications in electronic health records, cryptocurrency analysis, and social media sentiment. He has made significant contributions to efficient record linkage in data streams and spatio-temporal data through innovative blocking techniques and approximation schemes. His recent publications (2020-2022) reveal a consistent focus on scalable and privacy-aware record linkage, with increasing applications in financial technology and affective computing. Collaborations with prominent researchers like V.S. Verykios have resulted in numerous publications in top venues including IEEE Big Data and IEEE TIFS, demonstrating expertise in both theoretical foundations and practical implementations. Scientific Recognition Doctoral thesis featured in IEEE Intelligent Informatics Bulletin (2017) Research Projects University of York: Development of Java servlets for converting VisioXML into GSML within the High Integrity Systems Engineering research group University of Macedonia: Standardization of distance learning systems University of Macedonia: Establishment of a data bank for the fur sector in Kastoria University of Macedonia: System for organizing business processes of the Ministry of Macedonia and Thrace Dr. Karapiperis has collaborated with research teams across multiple institutions, contributing to diverse projects from healthcare data integration to government business process optimization, while maintaining active research in scalable entity resolution methodologies.

Maira KotsovoulouView profile

Assistant Professor

• Software Systems
• Databases
• Technology Enhanced Learning
• +5 more

Dr. Maira Kotsovoulou serves as Assistant Professor in the Department of Information Technology at Deree College and Graduate School, The American College of Greece, a position she has held since February 1, 1996. Her academic journey spans over 25 years of teaching and research in software systems and educational technology. Educational background includes: Doctorate in Technology Enhanced Learning, University of Lancaster (2011–2019) MSc in Human Computer Interaction, Heriot-Watt University (1994–1995) BSc in Computer Information Systems, The American College of Greece (1990–1994) Her research centers on the Software Systems and Databases Research Group, where she investigates visual programming applications for undergraduate education, automated assessment tools, and database optimization techniques. This work bridges theoretical computer science with practical pedagogy, focusing on how technology enhances student motivation and learning outcomes in programming courses. Her methodology combines empirical classroom studies with software development expertise gained through industry projects. Recent publications (2013–2018) reveal an evolving focus from collaborative resource tagging to sophisticated e-assessment systems, consistently addressing challenges in computer science education. The trajectory demonstrates increasing sophistication in analyzing instructor experiences and student perceptions while maintaining practical applicability in real classroom settings. Professional recognition includes: Oracle Certified Professional (OCP) in Database Administration Her industry engagement as a freelance solution architect complements academic work, with notable projects including Greece's national e-prescription system (IDIKA), COSMOTE retail software, and medical decision support systems. This dual expertise creates unique opportunities for students to engage with both academic research and enterprise-scale development challenges. As leader of the Software Systems and Databases Research Group, she fosters collaboration between academic theory and industry practice, emphasizing agile methodologies and practical implementation of educational technologies in real-world software development contexts.