جستجوی استاد راهنمای دانشگاهی

Ori Lahavمشاهده پروفایل

استاد

• Programming Languages
• Verification
• Concurrency
• +۴ مورد دیگر

Ori Lahav is a faculty member in the School of Computer Science at Tel Aviv University. He holds a PhD from Tel Aviv University (supervised by Arnon Avron), completed postdoctoral research at Tel Aviv University (hosted by Mooly Sagiv) and MPI-SWS in Germany (hosted by Viktor Vafeiadis and Derek Dreyer). His research is supported by an ERC Starting Grant and ISF Grant. His research focuses on programming languages, verification, concurrency, and relaxed memory models, with additional interests in proof theory, semantics of non-classical logics, and automated reasoning. His work bridges theoretical foundations with practical applications in compiler design, hardware verification, and distributed systems. Lahav's publications consistently explore concurrency paradigms, weak memory models, and verification techniques. Recent works emphasize formal methods for RDMA, persistent memory, compositional semantics, and automated tooling for memory consistency. Awards: Best Paper & Best Student Paper Awards (DISC 2024) Distinguished Paper Award (OOPSLA 2021) Best Paper Award (TABLEAUX 2017) Distinguished Paper Award (PLDI 2017) Best Paper Award (ECOOP 2017) Kleene Award for Best Student Paper (LICS 2013) He advises PhD and MSc students including Yoav Ben Shimon, Yotam Dvir, and Roy Margalit. His group investigates shared-memory concurrency, denotational semantics, and verification tools. Lahav co-organizes conferences (VMCAI 2024) and Dagstuhl seminars (2023, 2026). He teaches courses on Programming Language Foundations, Discrete Mathematics, and Weak Memory Concurrency.

Sam Lindleyمشاهده پروفایل

دانشیار

• Programming Languages
• Type Systems
• Effect Handlers
• +۵ مورد دیگر

Sam Lindley is a Reader in Programming Language Design and Implementation at the Laboratory for Foundations of Computer Science within the School of Informatics at The University of Edinburgh. He holds a prestigious UKRI Future Leaders Fellowship focused on Effect Handler Oriented Programming. His academic career spans multiple institutions including Heriot-Watt University and Imperial College London. His research interests center on programming language theory and implementation, with specific expertise in type systems, effect handlers, session types, and functional programming. Lindley's work bridges theoretical foundations with practical implementation, particularly in compiler design and language semantics. His research has significant implications for language safety, efficiency, and expressiveness. Lindley's publication record demonstrates consistent contributions to top programming languages venues including PLDI, POPL, ICFP, and OOPSLA. His recent work explores modal effect types, scoped effects, and the application of effect handlers to systems programming and WebAssembly. The trend shows increasing focus on practical applications of theoretical concepts in real-world language implementations. Major Awards: UKRI Future Leaders Fellowship in Effect Handler Oriented Programming Lindley has served in significant leadership roles including ICFP 2023 Program Chair and PLDI 2025 Area Chair. He actively participates in the programming languages community through numerous program committees and workshop organization. His research is conducted within the Laboratory for Foundations of Computer Science, a leading center for theoretical computer science research at Edinburgh.

Anil Madhavapeddyمشاهده پروفایل

استاد

• Planetary Computing
• Computer Systems
• Programming Languages
• +۷ مورد دیگر

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.

Stefano Markidisمشاهده پروفایل

استاد

• High-Performance Computing
• Heterogeneous Systems
• Quantum Computing
• +۳ مورد دیگر

Stefano Markidis is a Professor of Computer Science specializing in high-performance computing systems at KTH Royal Institute of Technology in Sweden. He works in the Division of Computational Science and Technology, focusing on supercomputers, quantum computers, and computational methods for scientific simulations. His research spans multiple domains including plasma physics, computational fluid dynamics, and quantum computing. Markidis holds an MS degree from Politecnico di Torino and a PhD in Nuclear Engineering from the University of Illinois at Urbana-Champaign. Prior to joining KTH, he was a graduate research assistant at Los Alamos National Laboratory and Lawrence Berkeley National Laboratory, followed by a postdoc at KU Leuven. His academic journey reflects a strong foundation in both engineering and computational science. His primary research interests include High-Performance Computing , Heterogeneous Systems , and Quantum Computing . Markidis develops computational methods for plasma physics, particle-in-cell simulations, and fluid dynamics. His work bridges theoretical physics and practical computing, with applications in space physics, fusion energy, and materials science. He is particularly known for contributions to parallel computing, GPU acceleration, and the development of scalable simulation frameworks like Neko for computational fluid dynamics. His research increasingly integrates machine learning techniques with traditional numerical methods. Analysis of Markidis' recent publications reveals a strong focus on quantum-classical hybrid computing, advanced particle-in-cell methods, and high-fidelity computational fluid dynamics. His work demonstrates expertise in programming models for heterogeneous architectures including GPUs and quantum processors, with growing emphasis on AI-enhanced scientific computing. R&D100 award (2005) for the CartaBlanca project R&D100 award (2017) for the SHIELDS project Markidis teaches multiple courses at KTH including Applied GPU Programming, Quantum Computing for Computer Scientists, and High-performance Computing for Computational Scientists. He has supervised numerous degree projects across various specializations in computer science and electrical engineering. His research has been supported by various grants related to high-performance computing and quantum technologies, with applications spanning from space physics to medical treatments. Markidis leads research in computational science with a focus on developing frameworks like Neko for extreme-scale computational fluid dynamics. His team works on integrating traditional HPC methods with emerging technologies including quantum computing and AI, contributing to advancements in scientific simulation across multiple disciplines.

Umang Mathurمشاهده پروفایل

استادیار

• Formal Methods
• Logic
• Programming Languages
• +۷ مورد دیگر

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.

Mayur Naikمشاهده پروفایل

استاد

• Programming Languages
• Artificial Intelligence
• Neurosymbolic Programming
• +۵ مورد دیگر

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.

Rachit Nigamمشاهده پروفایل

استادیار

• Programming Languages
• Computer Architecture
• Hardware Acceleration
• +۳ مورد دیگر

Rachit Nigam serves as an Assistant Professor in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology's School of Engineering. He leads the FLAME Lab, focusing on the intersection of programming languages and computer architecture. His research profile demonstrates significant involvement in major programming languages conferences including PLDI, SPLASH, and ICFP, where he has served in various committee roles from Artifact Evaluation to Student Research Competition Chair. Dr. Nigam's research centers on programming languages and hardware systems, with particular emphasis on creating compilers that transform programs into architectures. His work bridges theoretical type systems with practical hardware implementation, developing tools like Calyx (an intermediate language for hardware accelerator generators) and Dahlia (implementing time-sensitive affine types). His approach combines formal methods with practical compiler design to address challenges in predictable accelerator generation and hardware compilation. His publication record reveals a consistent trajectory in hardware-aware programming language design, with recent work focusing on unifying static and dynamic intermediate languages for accelerator generators. The publications demonstrate expertise across multiple subfields including type systems for hardware timing constraints, modular hardware design methodologies, and synthesis-aided compiler techniques for specialized architectures like DSPs. As an active member of the programming languages community, Nigam has served on numerous conference committees including PLDI, OOPSLA, and LCTES. He has chaired sessions, organized tutorials (including 'DSL-based Hardware Generation'), and contributed to community initiatives like PL Tea. His GitHub presence shows active development in projects related to hardware compilation with significant contributions to repositories like Calyx, Filament, and Dahlia. Dr. Nigam leads the FLAME Lab at MIT, which focuses on creating programming models and compiler infrastructure for hardware acceleration. His work with the Calyx compiler ecosystem represents a significant contribution to the field of hardware accelerator generation, providing tools that enable more predictable and efficient hardware compilation processes. His research has practical implications for domain-specific hardware accelerators and the broader challenge of making hardware design more accessible through programming language techniques.

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.

Erez Petrankمشاهده پروفایل

استاد

• concurrent computing
• programming languages
• memory management
• +۵ مورد دیگر

Erez Petrank is a Professor of Computer Science at the Technion - Israel Institute of Technology, where he holds the Andrew and Erna Viterbi Chair. His academic career spans decades with significant contributions to systems research, particularly in memory management and concurrent programming. He has maintained continuous academic service through leadership roles in major conferences including SPAA'24, ISMM 2023, and PPOPP 2021. His research focuses on concurrent computing, programming languages, and systems with special emphasis on memory management. Additional interests include parallelism, cryptography, data structures, approximation algorithms, and distributed computing. Petrank's work bridges theoretical foundations with practical systems implementation, particularly evident in his persistent memory research and garbage collection innovations. Petrank's publication record shows consistent contributions to ACM SIGPLAN conferences over two decades, with recent work focusing on non-volatile memory systems, lock-free data structures, and memory reclamation techniques. His research demonstrates a clear trajectory from foundational memory management concepts toward modern persistent memory architectures, reflecting adaptability to evolving hardware paradigms while maintaining theoretical rigor. H-index: 41 (Google Scholar) Erdos number: 2 62 co-authors across diverse research collaborations Petrank has mentored numerous researchers through his academic position and conference leadership roles, serving on program committees for major venues including PLDI, PPoPP, and ISMM. His professional service includes executive committee membership in ACM SIGPLAN (2009-2012) and steering committee roles for multiple conferences. He maintains active research collaborations with institutions worldwide, as evidenced by his extensive co-author list spanning theoretical computer science to practical systems implementation. His academic lineage traces back through Oded Goldreich, Shimon Even, and Hao Wang to intellectual giants including Isaac Newton and Galileo Galilei, reflecting deep roots in theoretical computer science and mathematics.

• Programming Languages
• Formal Verification
• Compilers
• +۸ مورد دیگر

Clément Pit-Claudel is an assistant professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, Department of Computer Science. He leads the SYSTEMF lab which he founded in January 2023. Prior to joining EPFL, he was a PhD candidate at MIT with Adam Chlipala and subsequently worked as a senior applied scientist at Amazon AWS. His academic journey began at École Polytechnique in France, followed by doctoral studies at MIT. Dr. Pit-Claudel's research focuses on programming languages, compilers, and formal verification, with broader interests spanning systems engineering, hardware design languages, security, performance engineering, databases, and type theory. His work centers around three main axes: extensible compilation (teaching compilers domain-specific optimization tricks), hardware design languages and verification, and tooling for proof assistants. He has developed several influential systems including Elk (a linear-time engine for JavaScript regexes), Warblre (a Coq translation of JS regex specification), Fiat (a library for correct-by-construction refinement), Narcissus (for verified binary encoders/decoders), F2F (a program extraction framework), Rupicola (a compiler-construction toolkit), Kôika (a rule-based hardware design language), Cuttlesim (a fast hardware simulator), and Alectryon (a literate programming system for Coq). His publications span top venues including PLDI, POPL, ICFP, ASPLOS, and SLE, with recent work focusing on verified JavaScript regular expressions, foundational integration verification of cryptographic servers, and relational compilation techniques. His research aims to build small, fast, and completely verified components for critical systems through a combination of machine-checked proofs, hardware-software co-design, low-level compiler engineering, and new tools for interactive theorem proving. His notable awards include the Distinguished Artifact award at SLE 2020 for 'Untangling Mechanized Proofs,' the William A. Martin Memorial Thesis Award from MIT in 2016, and the Frederick C. Hennie III Teaching Award from MIT in 2016. He has served on program committees for numerous conferences including PLDI, POPL, ICFP, and SPLASH, and has organized workshops such as the Coq Workshop and Proof Systems. As an educator, he teaches 'Software Construction' (undergraduate level, ~400 students) and 'Interactive Theorem Proving' (graduate level) at EPFL. His teaching philosophy emphasizes hands-on learning, continuous assessment through oral examinations, and designing assignments that lead students to build concrete artifacts they can be proud of. His approach is informed by hundreds of hours of in-class instruction in Europe and the US, resulting in stellar student reviews and multiple teaching awards.

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.

Maria Halkidiمشاهده پروفایل

دانشیار

• Data Mining
• Machine Learning
• Recommender Systems
• +۶ مورد دیگر

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.

Orestis Telelisمشاهده پروفایل

استادیار

• Algorithms Design and Analysis
• Computational Complexity
• Algorithmic Game Theory
• +۱ مورد دیگر

Orestis Telelis is an Assistant Professor at the University of Piraeus, specializing in Algorithms Design, Computational Complexity, and Algorithmic Game Theory. His current research focuses on Mechanism Design, Pricing Algorithms, and Approximation Methods for computationally hard problems. Education: Degree in Informatics and Telecommunications, National and Kapodistrian University of Athens (2001) M.Sc. in Advanced Information Systems, National and Kapodistrian University of Athens (2003) Ph.D. in Theoretical Computer Science, National and Kapodistrian University of Athens (2006) Post-doctoral Research: Evry-Val d’Essonne University, France (2007) Aarhus University, Denmark (2007-2009) Center for Mathematics and Computer Science (CWI Amsterdam), Netherlands (2009-2010) Research Associate, University of Liverpool, UK (2010-2012) Athens University of Economics and Business, Greece (2012-2014) Awards and Funding: Allain Bensoussan Fellowship, European Research Consortium for Informatics and Mathematics (ERCIM, 2009-2010) Research funding from General Secretariat of Research and Technology, Greece (2012-2014)