جست‌وجوی استاد و پژوهشگر

Marinos Vassilisمشاهده پروفایل

دانشیار

• Geotechnical Engineering
• Rock Mechanics
• Engineering Geology
• +۴ مورد دیگر

Marinos Vassilis serves as an Associate Professor in the Department of Geotechnical Engineering within the School of Civil Engineering at the National Technical University of Athens (NTUA). Based at the Foundations Laboratory in Zografou, Athens, his work bridges geotechnical engineering, rock mechanics, and engineering geology, with a focus on practical applications in tunneling, landslide risk mitigation, and cultural heritage preservation. His research interests encompass the utilization of UAVs, LiDAR, and virtual reality for advanced geological mapping and hazard assessment. Notable projects include stability evaluations of cultural heritage sites such as the Acropolis of Athens and Greek monasteries, alongside innovative methodologies for rock mass characterization and slope stability analysis in challenging terrains. Recent publications (2023-2025) highlight a trend toward integrating remote sensing and machine learning for geohazard management, particularly in cultural heritage contexts. His contributions to conference proceedings emphasize engineering geology's role in sustainable development, including megacity planning and preservation of historical structures. Associated with the Foundations Laboratory at NTUA, his research environment supports experimental and field studies in geomechanics, facilitating the development of practical solutions for rock and soil engineering challenges.

Vissarion Papadopoulosمشاهده پروفایل

استاد

• Structural Engineering
• Computational Mechanics
• Stochastic Analysis
• +۳ مورد دیگر

Vissarion Papadopoulos is a Professor in the Department of Structural Engineering at the School of Civil Engineering, National Technical University of Athens (NTUA). His office is located at the Statics and Aseismic Research Laboratory, with contact details including email vpapado@central.ntua.gr and phone 210 772 4158. He has maintained an active research profile since at least 2016, focusing on advanced computational methods in structural engineering. His primary research domains include: Structural Engineering and Computational Mechanics Stochastic Analysis and Uncertainty Quantification Multiscale Modeling of Composite Materials Machine Learning for Engineering Simulations Optimization of Structural Systems Thermomechanical Behavior of Advanced Materials Analysis of his recent publications reveals a decisive shift toward integrating deep learning frameworks with traditional computational mechanics. His work demonstrates consistent innovation in accelerating solutions for parametric and transient structural problems through transformer networks, Bayesian inference, and physics-informed neural networks. Key application areas include carbon nanotube reinforced composites, sustainable automotive design, and seismic-resistant structures, with emphasis on enhancing computational efficiency while maintaining accuracy. He is affiliated with NTUA's Statics and Aseismic Research Laboratory, which specializes in structural dynamics, earthquake engineering, and advanced computational methodologies for civil infrastructure analysis and design.

• Distributed Computing
• Concurrent Computing
• Transactional Memory
• +۴ مورد دیگر

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.

• Physical Chemistry
• Spectroscopy
• Condensed Matter Physics
• +۷ مورد دیگر

Angelos G. Kalambounias is a Professor in the Department of Chemistry at the University of Ioannina, Greece, where he has progressed from Assistant Professor (2015-2020) to Associate Professor (2020-2024) and finally to full Professor (November 2024-present). He maintains additional affiliations as a Collaborating faculty member at the Institute of Materials Science and Computation and the Institute of Environment and Sustainable Development, and serves on the Board of Directors of the Scientific and Technological Park of Epirus. His research spans multiple domains of physical chemistry with emphasis on spectroscopic techniques. His primary interests include condensed matter structure and dynamics, development of contactless high-temperature spectroscopic measurement techniques, Raman spectroscopy applications in thermodynamics, inorganic coordination complexes, glass science (particularly tellurite and oxide glasses), nanomaterials, atmospheric pollution analysis, and ultrasonic spectroscopy. His work bridges fundamental physical chemistry with practical applications in materials science and environmental monitoring. His publication record shows consistent output since 1999, with recent work focusing on molecular dynamics, peptide structure, drug delivery systems, microplastic analysis, and advanced spectroscopic techniques. His research group comprises numerous students across physics and chemistry disciplines, reflecting the interdisciplinary nature of his work. Among his professional roles, he serves as a Review Editor on the Editorial Board of 'Battery Systems and Applications' and has acted as a reviewer for over 30 international scientific journals spanning physical chemistry, materials science, and spectroscopy. His teaching portfolio includes undergraduate and graduate courses in physical chemistry, statistical mechanics, quantum chemistry applications, spectroscopic methods, and materials characterization at both the University of Ioannina and previously at the University of Patras.

Xiaoyin Wangمشاهده پروفایل

دانشیار

• Software Testing and Analysis
• Software Privacy
• Program Analysis
• +۳ مورد دیگر

Xiaoyin Wang is an Associate Professor in the Department of Computer Science at the University of Texas at San Antonio, specializing in software testing, privacy, and program analysis. Her research focuses on enhancing software quality through innovative approaches to build systems, virtual reality testing, and privacy policy enforcement. She earned her PhD from Peking University in 2012 and completed postdoctoral work at UC Berkeley. Her research interests span Software Testing and Analysis , Software Privacy , Build Systems , and Virtual Reality Testing . She develops techniques for detecting privacy leaks in mobile apps, optimizing build scripts, and testing immersive applications. Her work bridges program analysis with practical software engineering challenges, particularly in security-critical contexts. Recent publications reveal strong trends in Virtual Reality testing frameworks (e.g., VRGuide, VRTest), automated build diagnostics (PExReport, HireBuild), and privacy policy verification (GUILeak, DAISY). Her research increasingly integrates machine learning for bug prediction and test oracle generation, with significant contributions to augmented reality testing and cross-project compatibility analysis. President's Research Achievement Award (UTSA, 2019) NSF CAREER Award (2019) for build script analysis Distinguished PhD Dissertation Awards from CCF (2013) and Peking University (2012) MSRA Fellowship (2009) Wang actively advises PhD students including Rodney Rodriguez (defended 2022, now at Accenture) and Xueling Zhang (defended 2021, now Assistant Professor at RIT). She leads NSF-funded projects including CAREER: Analysis and Repair of Build Scripts for DevOps and EAGER: Tracing Privacy-Policy Statements into Code . Her service includes chairing ICSE 2019 proceedings and serving on ASE/ICSE/ISSTA program committees. Current work focuses on security analysis for AR applications and automated privacy compliance verification.

Işıl Dilligمشاهده پروفایل

دانشیار

• Program analysis
• Program synthesis
• Program verification
• +۴ مورد دیگر

Işıl Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her academic career spans over a decade of significant contributions to programming languages research, particularly in program analysis, verification, and synthesis. Dr. Dillig received all her academic degrees (BS, MS, and PhD) from Stanford University before joining the faculty at UT Austin. Her educational background established the foundation for her innovative research approach that bridges theoretical computer science with practical applications. Her research focuses on developing techniques to make software systems more reliable, secure, and easier to build through advanced program analysis, verification, and synthesis methods. She has pioneered approaches that combine symbolic reasoning with machine learning to tackle complex software engineering challenges across multiple domains including security, databases, and programming language theory. Her work demonstrates exceptional depth in creating practical tools that address real-world software development problems while maintaining strong theoretical foundations. Analysis of Dr. Dillig's publication record reveals a consistent trajectory of innovation in program synthesis, with recent work expanding into neurosymbolic approaches that bridge neural networks with formal methods. Her research shows strong connections between theoretical foundations and practical applications, particularly in security-critical systems, database technologies, and blockchain applications. The evolution of her work demonstrates increasing sophistication in handling complex program structures while maintaining practical usability. Dr. Dillig has received prestigious recognition for her research contributions: Sloan Fellowship NSF CAREER award As a dedicated educator and research leader, Dr. Dillig has served in significant roles including Program Chair for PLDI 2022 and Steering Committee member for PLDI. She has mentored numerous students through her UToPiA research group, guiding research in program synthesis, verification, and analysis. Her work has been supported by substantial research grants that have enabled innovative projects at the intersection of programming languages and security. Dr. Dillig leads the UToPiA (UT Austin Programming, Languages, and Analysis) research group, which focuses on developing novel techniques for program analysis, verification, and synthesis. The group maintains strong collaborations with industry partners and academic institutions worldwide, translating theoretical advances into practical tools that address real software engineering challenges.

Shachar Itzhakyمشاهده پروفایل

دانشیار

• Program Synthesis
• Automated Reasoning
• Functional Programming
• +۵ مورد دیگر

Shachar Itzhaky is an Associate Professor in the Department of Computer Science at Technion - Israel Institute of Technology, Haifa. His research spans multiple areas of programming languages, formal methods, and software engineering, with a focus on making program development and verification more accessible and efficient. He has served on program committees for numerous prestigious conferences including PLDI, POPL, SPLASH, and ICFP. Dr. Itzhaky's research interests center around program synthesis, automated reasoning, and formal verification. His work in program synthesis explores techniques for automatically generating programs from high-level specifications, with applications in end-user programming and software development. In automated reasoning, he has made significant contributions to e-graph based reasoning, invariant inference, and property-directed verification. His research in formal methods focuses on practical applications for program verification, particularly for data structures and security properties. An analysis of his recent publications reveals a strong focus on leveraging advanced formal techniques for practical program understanding and generation. His work consistently bridges theoretical foundations with practical applications, particularly in program synthesis, verification, and end-user programming tools. The trend shows increasing integration of machine learning techniques with traditional formal methods, as well as expanding applications to security and privacy domains. ACM SIGPLAN John C. Reynolds Doctoral Dissertation Award Dr. Itzhaky has been actively involved in the programming languages research community, serving on numerous program committees and contributing to the advancement of formal methods and program synthesis. His work has practical implications for software development tools, security analysis, and end-user programming environments. While specific grant information isn't detailed in the provided text, his extensive publication record in top-tier venues suggests successful funding for his research endeavors. His work on projects like Object Spreadsheets and Lifty demonstrates a commitment to creating practical tools that address real-world programming challenges. Dr. Itzhaky's research is conducted within the vibrant programming languages and formal methods group at Technion's Computer Science department. His work intersects with multiple research threads including program synthesis, verification, and security, suggesting collaboration across these areas within the department. His tools like EPR-based Verification, PDR∀, and VeriCon represent significant technical contributions that likely form the basis of ongoing research projects with students and collaborators.

Eran Yahavمشاهده پروفایل

دانشیار

• Program Analysis
• Program Synthesis
• Program Verification
• +۴ مورد دیگر

Eran Yahav is an Associate Professor in the Computer Science Department at the Technion - Israel Institute of Technology. He previously served as a research staff member at IBM T.J. Watson Research Center from 2004 to 2010. His academic journey began with a B.Sc. from the Technion in 1996, followed by a Ph.D. from Tel Aviv University in 2005. Yahav's research focuses on program analysis, program synthesis, program verification, and machine learning for programming. His work bridges theoretical foundations with practical applications, particularly in developing techniques that help programmers work more effectively with complex frameworks and APIs. He has pioneered approaches that combine static analysis with machine learning to address challenges in code search, completion, and understanding. His recent work heavily intersects with neural network applications to programming tasks, demonstrating how deep learning can enhance traditional program analysis techniques. His publication record shows a clear evolution from traditional program analysis and verification toward integrating machine learning with programming language processing. The most recent articles reveal a strong focus on neural methods for code understanding, including structural language models, adversarial examples for code models, and neural approaches to binary analysis and program synthesis. This represents a significant shift toward leveraging AI techniques to solve longstanding problems in programming languages and software engineering. Yahav has received numerous accolades including the prestigious Alon Fellowship for Outstanding Young Researchers, the Andre Deloro Career Advancement Chair in Engineering, and an ERC Consolidator Grant. He also earned best paper awards at ISSTA 2006 and 2007. As an advisor, Yahav has mentored numerous Ph.D. and Master's students who have gone on to make significant contributions in academia and industry. His research has been supported by substantial grants, including the ERC Consolidator Grant. He also serves as CTO at Tabnine, demonstrating the practical impact of his research. Yahav leads multiple research projects including PRIME (Programming with Millions of Examples), Fender (Preserving Correctness under Weak Memory Models), Saint (Synthesis using Abstract Interpretation), and several others focused on program analysis, verification, and synthesis. His work often involves building practical tools that translate theoretical advances into usable software engineering solutions.

Qirun Zhangمشاهده پروفایل

دانشیار

• Program Analysis
• Programming Languages
• Software Engineering
• +۴ مورد دیگر

Qirun Zhang is the Catherine M. and James E. Allchin Early Career Associate Professor in the School of Computer Science at Georgia Institute of Technology. His research focuses on program analysis, compiler optimization, and formal language theory, with numerous publications in top-tier programming language and software engineering conferences including PLDI, POPL, OOPSLA, and FSE. He teaches courses on compilers, program analysis, and software testing. Dr. Zhang's research interests center on improving software reliability and security through advanced program analysis techniques. He approaches problems from perspectives including computational complexity, analytic combinatorics, graph theory, and formal languages. His work often bridges theoretical foundations with practical applications in compiler design and program verification. His recent publications show a strong focus on context-free language reachability, Dyck-language based analyses, and SMT solving techniques. His research demonstrates consistent innovation in making program analysis more precise while maintaining scalability, with applications ranging from debug information validation to software debloating and type inference. PLDI Distinguished Paper Award (2020) SIGSOFT Distinguished Paper Award (2023) OOPSLA Distinguished Artifact Award (2022) Dr. Zhang actively mentors PhD and MS students, with current advisees including Camille Bossut and Benjamin Mikek. His service to the academic community includes Artifact Evaluation Co-Chair roles for PLDI 2025 and 2026, and program committee membership for numerous top conferences including PLDI, POPL, and OOPSLA. He leads research projects including SLOT, Context-Free Language Reachability with Transitive Redundancy Elimination, and Debug Information Validation.

Laura Dietzمشاهده پروفایل

دانشیار

• Information Retrieval
• Machine Learning
• Natural Language Processing
• +۶ مورد دیگر

Laura Dietz is a tenured Associate Professor in the Department of Computer Science at the University of New Hampshire, where she leads the TREMA lab. Her academic journey began with a PhD from the Max Planck Institute for Informatics in Saarbruecken, Germany (2011), followed by postdoctoral positions at the University of Massachusetts Amherst (2010-2015) and University of Mannheim (2015-2016). Her educational background includes PhD studies at both the Max Planck Institute for Informatics (2007-2011) under Prof. Gerhard Weikum and Prof. Tobias Scheffer, and earlier research at Humboldt University in Berlin. She has built a distinguished career bridging theoretical computer science with practical applications in information retrieval and machine learning. Dietz's research primarily focuses on the intersection of information retrieval, natural language processing, and knowledge graphs, with a parallel research initiative in watershed data science. She is particularly known for her work on entity-aspect linking, complex answer retrieval, and the vision of automatic Wikipedia construction. Her approach integrates fine-grained knowledge annotations with text understanding to create comprehensive information systems that go beyond traditional 10-blue-links search paradigms. In watershed data science, she applies similar machine learning techniques to environmental data streams, focusing on solute transport analysis during storm events. Her recent publications reveal a strong trend toward fine-grained semantic understanding, particularly in entity-oriented search tasks. She has pioneered methods for entity-aspect linking that significantly improve retrieval accuracy by capturing different contexts in which entities appear. Her work increasingly integrates knowledge graphs with neural architectures, showing sophisticated understanding of how to leverage both structured and unstructured information for better search experiences. Best paper award at JCDL 2018 for work on entity-aspect linking NSF CAREER Award (2019-2023) for "Utilizing Fine-grained Knowledge Annotations in Text Understanding and Retrieval" OSSI Award 2013 from UMass ICB3 for open-source hardware/software Dietz actively mentors PhD and Masters students through the TREMA lab, with current research focusing on entity ranking, topic extraction, conversational search, and watershed forecasting. Her grant portfolio includes the NSF CAREER award and funding from the Northeast Big Data Innovation Hub for forecasting salinity in rivers during storm events. She has also coordinated the TREC Complex Answer Retrieval track (2017-2019), creating important benchmarks for the IR community. The TREMA lab (Text Retrieval, Entity Modeling, and Applications) serves as the hub for Dietz's research activities, bringing together students and collaborators to work on cutting-edge problems in information access. The lab's work spans both theoretical contributions to information retrieval and practical applications in domains ranging from environmental science to scientific publication analysis.

Kunle Olukotunمشاهده پروفایل

استاد

• Computer Architecture
• Parallel Programming
• Chip Multiprocessors
• +۴ مورد دیگر

Kunle Olukotun is a Professor of Electrical Engineering and Computer Science at Stanford University's School of Engineering, where he has been faculty since 1991. He directs the Stanford Pervasive Parallelism Lab (PPL) and co-leads the Transactional Coherence and Consistency (TCC) project. His research focuses on computer architecture, parallel programming environments, and scalable parallel systems. Key areas include chip multiprocessors (CMPs), transactional memory systems, domain-specific languages (DSLs) for heterogeneous computing, and hardware-software co-design for machine learning workloads. His work bridges theoretical foundations with practical systems implementation. Notable contributions include the Stanford Hydra research project (one of the first chip multiprocessors with thread-level speculation), founding Afara Websystems (acquired by Sun Microsystems), and developing the Niagara processor architecture. His DSL frameworks like Green-Marl and Spatial enable efficient graph analysis and hardware acceleration. His publications reveal strong trends in parallel systems evolution: from foundational CMP research (2000s) to transactional memory (2004-2010), then DSLs for heterogeneous computing (2010-2015), and currently foundation model systems (2023-2025). Subfield analysis shows consistent focus on hardware-software co-design, sparse computation, and compiler techniques across decades. ACM Fellow (2006) for contributions to multiprocessors on a chip and multi-threaded processor design Best Paper Award at IEEE International Symposium on Workload Characteristics (IISWC '10) for EigenBench Olukotun actively mentors researchers through the Stanford Pervasive Parallelism Lab (PPL), which seeks to proliferate parallelism across application domains. His projects have secured significant industry partnerships, including the acquisition of his startup Afara Websystems by Sun Microsystems. Current research focuses on compiler frameworks for foundation model systems and hardware acceleration for sparse machine learning workloads, supported by collaborations with major tech companies. He leads the Stanford Pervasive Parallelism Lab (PPL), which develops compiler and runtime systems for heterogeneous architectures. The lab's work spans DSLs, hardware acceleration, and parallel programming models, with strong industry ties to companies like NVIDIA and Google. Current initiatives include the Mosaic compiler framework and Stardust architecture for sparse tensor computation.

Fernando Magno Quintão Pereiraمشاهده پروفایل

دانشیار

• Compilers
• Code Generation
• Compiler Optimizations
• +۳ مورد دیگر

Fernando Magno Quintão Pereira is an Associate Professor at the Federal University of Minas Gerais (UFMG), Brazil, specializing in compiler design and program analysis. His academic journey began with a Ph.D. from UCLA in 2008 under Jens Palsberg's supervision, establishing his foundation in compiler research. His research focuses on compilers , with core expertise in code generation , compiler optimizations , and static program analyses . Recent work explores quantum compilation, binary analysis, and security-aware compilation techniques. His publications reveal consistent contributions to major conferences including PLDI, CGO, and SPLASH, with emphasis on practical optimization frameworks and theoretical compiler advancements. Analysis of his 15 most recent publications (2020-2026) shows dominant themes in binary optimization (e.g., AnghaBench), security-aware compilation (e.g., Memory-Safe Elimination of Side Channels), and emerging architecture support (e.g., Quantum Computing Compilation). His work bridges theoretical compiler principles with real-world systems challenges. He actively contributes to the academic community through: Program committees for PLDI (2020-2025), CGO (2021-2026), and SPLASH conferences Leadership roles including CGO Finance Chair (2026) and PLDI Diversity & Inclusion Co-Chair (2023-2024) Organizing JENSFEST 2024 and serving on multiple conference steering committees Pereira maintains an active research group evidenced by continuous publication output and conference leadership, with his personal website ( homepages.dcc.ufmg.br/~fernando/ ) serving as a hub for his academic activities.

Nadia Polikarpovaمشاهده پروفایل

دانشیار

• Program Synthesis
• Program Verification
• Type Systems
• +۲ مورد دیگر

Nadia Polikarpova is an Associate Professor in the Computer Science and Engineering Department at the University of California, San Diego. She leads the Programming Systems group and serves as a member of IFIP Working Group 2.8 on Functional Programming since 2022. Her academic journey includes a PhD from ETH Zurich (Switzerland) under Bertrand Meyer's supervision in 2014, followed by postdoctoral work at MIT CSAIL with Armando Solar-Lezama. Her research interests center around program synthesis, program verification, and type systems, with a focus on building practical tools that enhance software security and reliability. Polikarpova's work bridges theoretical foundations with real-world applications, particularly in the emerging area of AI-assisted programming. Her recent publications demonstrate a strong trajectory in program synthesis techniques, with increasing integration of machine learning approaches. The research spans from foundational type-driven synthesis methods to practical applications for validating AI-generated code and synthesizing heap-manipulating programs. Her work frequently appears in top-tier programming languages venues including PLDI, POPL, ICFP, and OOPSLA. 2020 Sloan Fellow 2020 Intel Rising Stars Award 2020 NSF CAREER Award Distinguished paper awards at PLDI'21, ICFP'20, and POPL'19 Best paper award at FM'15 Polikarpova actively mentors PhD students and has advised numerous graduates who now work at Microsoft Research, University of Michigan, and various tech companies. She teaches core programming languages courses including CSE 130 and specialized graduate courses on program synthesis (CSE 291). Her service to the community includes program committee roles for major conferences and co-chairing the Haskell conference in 2022.

Koushik Senمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Formal Methods
• +۳ مورد دیگر

Koushik Sen is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. His academic career spans major contributions to software engineering and programming languages research through active participation in premier conferences including PLDI, ICSE, and ISSTA. His research focuses on Software Engineering , Programming Languages , and Formal Methods , with particular emphasis on developing software tools that enhance programmer productivity and software quality. Key research thrusts include automated test generation , symbolic execution , fuzzing techniques , and program synthesis . His work bridges theoretical foundations with practical tool development for real-world software verification challenges. Analysis of his publication record reveals consistent contributions to automated testing methodologies, with recent work integrating machine learning (particularly large language models) into traditional program analysis techniques. His research shows strong continuity in improving software reliability through innovative input generation and vulnerability detection approaches. As an active academic leader, he has served as General Chair for MAPL (2020), Program Chair for ISSTA (2017), and committee member for numerous top-tier conferences including PLDI, ICSE, and SPLASH across multiple years. His academic advising manifests through collaborative publications with students on topics like test corpus expansion (Bonsai Fuzzing), visualization synthesis (VizSmith), and smart contract auditing (ItyFuzz), though specific student names aren't listed in the source material. His research has been supported through conference participations and likely associated grants given his extensive publication record.

• Entity Resolution
• Record Linkage
• Privacy-Preserving Record Linkage
• +۳ مورد دیگر

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.