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Panagiotis NastouView profile

Assistant Professor

• Secure Discrete Systems Modeling
• Graph Theory
• Cryptography
• +5 more

Panagiotis Nastou is an Assistant Professor at the Department of Mathematics , University of the Aegean , with research interests in Secure Discrete Systems Modeling, Graph Theory, Cryptography, Design and Analysis of Algorithms , and Complexity Theory . He has been active in teaching courses such as Discrete Mathematics and Cryptography since 2007 and serves as Director of the Applied Mathematics and Mathematical Modeling Laboratory since 2019. Education : Ph.D., MSc., and BSc. in Computer Engineering and Informatics from Patras University. Membership : Center for Applied Optimization (University of Florida), GDPR TEAM, IEEE, ACM, and Hellenic Technical Chamber. His research bridges theoretical computer science and applied security, focusing on cryptographic protocols, algorithm design, and the application of discrete mathematics to real-world problems. He has contributed to the development of secure systems for critical infrastructure and privacy-preserving frameworks in smart cities. Recent publications (2021-2025) emphasize malware evasion , quantum cryptanalysis , and privacy in IoT environments , utilizing formal methods and combinatorial structures. His work also extends to deep learning for document analysis and consensus algorithms in social networks . He has supervised numerous Master's and undergraduate theses in areas like Zero-Knowledge Proofs , Neural Networks , and Cryptographic Boolean Functions . Administrative roles include representation in the ERASMUS+ program and participation in EU-funded project evaluations.

George BarmpaliasView profile

Professor

• Mathematical Logic
• Computability Theory
• Algorithmic Randomness
• +3 more

George Barmpalias is a Professor at the Chinese Academy of Sciences (Institute of Software) , with a research focus on Mathematical Logic , Computability Theory , Algorithmic Randomness , and Kolmogorov Complexity . His work also extends to Network Science and Social Dynamics through Schelling segregation models. Ph.D. in Mathematics, University of Leeds (2004) Mathematics Degree, University of Thessaloniki (2000) Research Interests include: Algorithmic Randomness (Ω numbers, K-triviality, Martin-Löf randomness) Computability Theory (Turing degrees, reducibilities, effective closed sets) Network Dynamics (Schelling models, segregation tipping points, idemetric properties) Information Theory (Kolmogorov complexity, data compression, oracle use bounds) Scientific Awards : Distinguished Research Professor (CAS, 2022) National Natural Science grants (2015-2020) International Young Scientist Award (CAS, 2012) EPSRC Research Fellowship (2004) Teaching spans graduate courses in: Theory of Computation Network Science Mathematical Logic Computability and Randomness Supervision includes Ph.D./MSc students like Fang Nan, Cheng Shichao, and Charlotte Vlek. His software projects include high-performance C++ simulations for Schelling models and open-source tools for algorithmic experiments.

• Causal Inference
• Machine Learning
• Data Science
• +2 more

Sofia Triantafillou is an active Assistant Professor at the University of Crete specializing in causal inference and machine learning, with research applications spanning healthcare, telecommunications, and environmental health. Her work bridges theoretical advances in causal discovery with real-world problem solving across diverse domains. Her educational background includes a PhD from the University of Crete completed in 2015. Dr. Triantafillou's research focuses on developing robust methods for causal discovery, treatment effect estimation, and data integration. Key contributions include foundational work on causal Markov boundaries, identifiability frameworks, and automated causal pipelines. She addresses critical challenges in heterogeneous data settings, particularly in healthcare applications like sepsis treatment optimization and environmental health impact analysis. Her interdisciplinary approach combines computer science, statistics, and domain-specific knowledge to advance both methodological rigor and practical utility. Analysis of her 2021-2025 publications reveals a sustained emphasis on automating causal discovery processes and handling complex real-world data scenarios. She has pioneered techniques for integrating observational and experimental data, with growing applications in biomedical informatics (e.g., sepsis heterogeneity analysis) and industrial domains (e.g., 5G network optimization). Her work demonstrates consistent innovation in making causal methods more accessible, reliable, and applicable across disciplines.

Magdalene MarinakiView profile

Researcher

• Optimization
• Optimal Control
• Nature Inspired Algorithms
• +5 more

Magdalene Marinaki serves as a Researcher and permanent laboratory teaching personnel at the Technical University of Crete (TUC), School of Production Engineering and Management. She also teaches in the Hellenic Open University's Social Sciences Graduate Program. Her expertise lies in optimization methodologies, optimal control systems, and nature-inspired algorithms applied to logistics and manufacturing. She holds a Diploma, MSc, and PhD from TUC, specializing in Production Engineering and Management. Her research focuses on computational optimization, metaheuristics, vehicle routing problems (VRP), energy-efficient transportation systems, and structural control. She has authored 4 books and over 50 journal articles, with additional contributions to conference proceedings. Notable projects involve EU-funded research on blockchain applications in maritime logistics, electric vehicle routing, and unmanned aerial vehicle (UAV) path optimization. Her recent work emphasizes sustainable transportation solutions, including EV charging infrastructure planning and drone-integrated delivery networks. She has developed algorithms like teaching-learning-based optimization and hybrid swarm intelligence techniques, addressing real-world challenges in supply chain management and smart manufacturing systems.

• Partial Differential Equations
• Integral Equations
• Inverse Scattering Problems
• +3 more

Vassilios Sevroglou is a Professor at the Department of Statistics and Insurance Science, University of Piraeus, School of Finance and Statistics. His academic career spans since 2002, with roles including Assistant Lecturer (2002-2006) and Lecturer (2007-2011) at the same university, and visiting positions at the University of Ioannina. He holds a PhD in Applied Mathematics and a bachelor's degree in Mathematics from the National and Kapodistrian University of Athens. His research focuses on Partial Differential Equations, Integral Equations (Riesz-Fredholm Theory), and inverse scattering problems in elasticity and acoustics. Key areas include 2D/3D elastic wave scattering, thermoelastic interactions, chiral media applications, and computational methods for boundary value problems. The 15 most recent articles highlight advancements in chiral electromagnetic scattering, stochastic boundary value problems, thermoelastic wave interactions, and numerical reconstruction techniques. These works emphasize inverse problems, Wiener chaos expansions, and regularization methods in acoustics and elasticity. Teaching activities encompass Calculus, Differential Equations, Stochastic Finance, and advanced applied mathematics courses. No specific scientific awards or lab affiliations are mentioned in the provided texts.

• Distributed Computing
• Concurrent Computing
• Transactional Memory
• +4 more

Rachid Guerraoui is a Moroccan-Swiss computer scientist and Full Professor in the School of Computer and Communication Sciences at EPFL. He is renowned for his significant contributions to distributed and concurrent computing, holding the prestigious Chair in Distributed Computing at the Collège de France (2018-19). As an ACM Fellow (2012) and recipient of the Dahl-Nygaard Senior Prize (2024), his work has shaped both theoretical foundations and practical implementations in distributed systems. Guerraoui earned simultaneous Master's degrees in Computer Engineering from École supérieure d'informatique électronique automatique (ESIEA) and in Computer Science from Pierre and Marie Curie University in 1989. He completed his PhD at Université d'Orsay in 1992 under the supervision of Christian Fluhr, with a dissertation titled "Programmation Répartie par Objets: Études et Propositions." Following postdoctoral research at EPFL, he joined the computer science faculty in 1999 after working at HP Labs and MIT. Guerraoui's research spans distributed computing, concurrent systems, transactional memory, and asynchronous algorithms. His work on establishing theoretical foundations of Transactional Memory, including the concept of opacity, has been highly influential. He has also made significant contributions to scalable information dissemination methods, asynchronous distributed computations, and the mathematical abstraction of indulgence. His research bridges theoretical rigor with practical implementations, as evidenced by systems like SwissTM and STMBench7. His publication record shows a clear evolution from theoretical foundations to practical implementations and broader applications. Early work focused on fundamental problems like consensus and renaming, while more recent publications address machine learning applications and public understanding of AI. The consistent thread throughout his career is a focus on making distributed systems more reliable, efficient, and accessible. Guerraoui has received numerous prestigious awards including: ACM Fellow (2012) ERC Advanced Grant Award (2013) Google Focused Award (2014) Middleware Best Paper Award (2014) Middleware 10-Years Best Paper Award Chair in Distributed Computing, Collège de France (2018-19) Dahl-Nygaard Senior Prize (2024) As an academic advisor, Guerraoui has mentored students including El Mahdi El Mahmdi, with whom he co-created the Wandida project - a collection of educational videos on computer science. His research has been supported by significant grants from the European Research Council and Google. Beyond research, Guerraoui actively participates in public discourse, particularly regarding computer science education and technology policy. Guerraoui leads the Distributed Computing Laboratory (DCL) at EPFL, which focuses on advancing the state of the art in distributed systems. The lab's work spans theoretical foundations, practical implementations, and educational outreach, reflecting Guerraoui's holistic approach to computer science research and education.

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.

Umang MathurView profile

Assistant Professor

• Formal Methods
• Logic
• Programming Languages
• +7 more

Umang Mathur is a Presidential Young Professor (Assistant Professor) in the School of Computing at the National University of Singapore (NUS), where he leads the FOCS Lab and is affiliated with PLSE@NUS (Programming Languages and Software Engineering group). He has established himself as a leading researcher in Formal Methods, with significant contributions to concurrency analysis and program verification. Dr. Mathur received his PhD from the University of Illinois at Urbana-Champaign under Prof. Mahesh Viswanathan. Prior to joining NUS, he worked as a Research Scientist at Facebook Inc. and as a Research Fellow at the Simons Institute for the Theory of Computing. His doctoral work was supported by a Google PhD Fellowship. PhD: University of Illinois at Urbana-Champaign Current Position: Presidential Young Professor at NUS School of Computing Previous Positions: Research Scientist at Facebook, Research Fellow at Simons Institute His research spans Formal Methods and Logic with applications to Programming Languages, Software Engineering, and Cyber-Physical Systems. Dr. Mathur specializes in developing algorithmic techniques for analysis of concurrent software and understanding decidability boundaries in verification and synthesis. His work bridges theoretical foundations with practical implementations, making verification techniques more efficient for real-world systems. Analysis of his recent publications reveals a strong focus on practical concurrency analysis, with many papers addressing race detection, deadlock prediction, and memory model verification. His research consistently demonstrates how theoretical computer science can solve practical software engineering challenges, particularly in making verification techniques scalable and efficient for industrial applications. Google PhD Fellowship ESEC/FSE 2018 Distinguished Paper Award ASPLOS 2022 Best Paper Award POPL 2023 ACM SIGPLAN Distinguished Paper Award CPP 2024 Distinguished Paper Award Dr. Mathur actively mentors numerous PhD students, Master's students, and undergraduates through the FOCS Lab. His research group has received support from Google Research grants and other funding sources. He serves on program committees for major conferences including PLDI, POPL, and ASPLOS, and has organized events like PLMW@PLDI. His teaching includes courses on Data Structures and Algorithms, Foundations of Logic in Computer Science, and advanced topics in Programming Languages. As director of the FOCS Lab, Dr. Mathur oversees a vibrant research group focused on foundational aspects of computer science with direct applications to programming languages and software engineering. The lab maintains strong international collaborations and regularly publishes in top-tier venues, reflecting its significant contributions to the field of formal methods and programming languages.

Ilya SergeyView profile

Associate Professor

• Programming Languages
• Concurrency
• Type Theory
• +7 more

Ilya Sergey is an Associate Professor at the National University of Singapore (NUS) School of Computing, with previous faculty appointments at University College London (2015-2018). His academic career spans multiple prestigious institutions including IMDEA Software Institute (postdoctoral position) and KU Leuven (PhD). His educational background includes a PhD in Computer Science from KU Leuven (2012), an MSc in Mathematics and Computer Science from Saint Petersburg State University (2008), and professional experience as a software engineer at JetBrains prior to academia. Sergey's research focuses on the intersection of programming language theory and practical software verification, with particular emphasis on concurrent systems , smart contracts , and program synthesis . His work bridges theoretical foundations in type theory and separation logic with practical applications in blockchain technology and Rust programming. He has developed novel techniques for verifying heap-manipulating programs, analyzing commutativity in distributed transactions, and synthesizing correct-by-construction code. Analysis of his recent publications reveals a clear trajectory toward practical verification of blockchain systems and concurrent data structures, with increasing focus on Rust programming language applications. His work demonstrates consistent innovation in mechanized reasoning techniques while maintaining relevance to real-world software challenges, particularly in the domains of smart contracts and distributed systems. Sergey maintains an active research group at NUS, as evidenced by his social media references to lab traditions and student collaborations. He frequently participates in major programming languages conferences as both author and committee member, serving in leadership roles including General Chair for ICFP 2025. His research lab follows distinctive traditions, including location-based Mattermost status updates when traveling. Sergey is deeply engaged with the programming languages community through conference organization, mentoring activities, and outreach initiatives such as nature walks for conference attendees.

• 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.

Ioannis KonstantarasView profile

Associate Professor

• Operations Research
• Inventory Control
• Reverse Logistics
• +4 more

Ioannis Konstantaras is an Associate Professor at the Department of Business Administration, University of Macedonia, Thessaloniki, Greece, holding this position since July 2016. He contributes to the Master in International Business, Master in Business Administration, and Master in Business Analytics and Data Science programs. His academic qualifications include: B.Sc. in Mathematics from Aristotelian University of Thessaloniki (1999) M.Sc. in Statistics & Operations Research from University of Ioannina (2001) Ph.D. in Operations Research from University of Ioannina (2006) Konstantaras specializes in mathematical modeling and optimization of inventory systems for supply and reverse logistics chains. His research addresses production planning, deteriorating items, imperfect quality products, and recovery processes through operations research methodologies. He develops analytical models for optimizing decision-making in complex logistics environments. His publication record (2010-2014) shows concentrated research on inventory models for deteriorating items, lot-sizing in recovery systems, and pricing strategies for reverse logistics. Key contributions include extensions to Economic Order Quantity models, optimization of two-warehouse systems, and integration of inspection learning effects in quality control. He serves as Co-Editor for the International Journal of Systems Science: Operations & Logistics since January 2014 and has reviewed for numerous international journals. Konstantaras led the research program "Logistics Management: Quantitative Methods for Inventory Management" funded by the ARCHIMEDES program under EPAYAEK II. No publicly available information lists his doctoral advisees.