جست‌وجوی استاد و پژوهشگر

Chrisanthi Avgerouمشاهده پروفایل

استاد

• Information Systems
• Organizational Change
• ICT for Development
• +۳ مورد دیگر

Chrisanthi Avgerou is Professor of Information Systems at the London School of Economics and Political Science (LSE), affiliated with the Department of Management Science and Technology in the School of Business. She chairs IFIP Technical Committee 9 on Social Implications of Information Technology and serves as Associate Editor for Information Systems Research Journal and The Information Society Journal. Her educational background includes: Ph.D. in Information Systems, London School of Economics, 1989 M.Sc. in Computer Science, Loughborough University of Technology, 1978 B.Sc.(Hons) in Mathematics, University of Athens, Greece, 1977 Professor Avgerou's research examines ICT's relationship with organizational transformation and socio-economic development, with emphasis on critical perspectives and developing country contexts. Her work bridges technical implementation with social theory, exploring power dynamics in socio-technical change and institutional barriers to ICT adoption. She pioneered studies on computers in developing countries through IFIP WG 9.4 leadership (1996-2003). Analysis of her 1998-2007 publications reveals consistent focus on three interconnected domains: (1) socio-technical change in organizations using institutional theory, (2) ICT's role in development contexts through critical policy analysis, and (3) philosophical foundations of information systems research. Her editorial work in The Oxford Handbook of ICT (2007) synthesizes global perspectives on digital transformation. Her scientific recognition includes: Fellow of the British Computer Society Fellow of the Association for Information Systems She coordinates the BSc Information Systems and Management program for the University of London External Programme and teaches Social Study of IS (IS470) and Information Society, Theory and Policy (IS412/478). Her research is conducted through LSE's Information Systems and Innovation Group, which examines technology's societal impacts through interdisciplinary collaboration. She currently organizes the Human Choice and Computers conference series, advancing discourse on technology ethics.

• Bayesian Statistics
• Computational Statistics
• Categorical Data Analysis
• +۶ مورد دیگر

Ntzoufras Ioannis is a Professor in the Department of Statistics at the Athens University of Economics and Business (AUEB), School of Information Sciences and Technology, where he has served continuously since 2004 (promoted to Professor in 2015). Previously, he held teaching positions at the University of the Aegean (2000-2004) and completed military service (1999-2000). Education B.Sc. in Statistics and Insurance Science (1994) M.Sc. in Statistics with Application in Medicine, University of Southampton (1995, with distinction) Ph.D. in Statistics, Athens University of Economics and Business (1999) Research Focus His work centers on Bayesian and computational statistics , specializing in categorical data analysis, statistical modeling, and variable selection methodology. He develops sophisticated models for applications in medical research (clinical trials, risk estimation), psychometrics (latent variable models), and sports analytics (football/basketball modeling), with emphasis on computational efficiency and real-world implementation. Publication Trends Recent publications (2023-2025) reveal three dominant trends: (1) Advanced Bayesian variable selection methods for high-dimensional data, (2) Sports analytics applications in football (goal modeling, competitive balance) and basketball (in-play performance), and (3) Development of specialized R packages (ssifs, PEPBVS) for statistical computation. His work consistently bridges theoretical innovation with practical domain applications. Scientific Awards Lefkopouleion Prize for Greece's best statistics thesis (1999-2000) PROSE Award Honorable Mention for 'Bayesian Modeling Using WinBUGS' (2010) Academic Leadership He has supervised graduate students across AUEB's Statistics, Business Analytics, and Data Science programs, and taught postgraduate courses at the University of Athens (Biostatistics), University of the Aegean (Business Administration), and Italian institutions (University of Pavia, Universita Cattolica, University of Bicocca-Milan). As General Secretary of the Greek Statistical Institute (2006-2007), he advanced national statistical initiatives. Research Community He founded and maintains grstats (http://grstats.forumotion.net/), Greece's primary online statistics community, facilitating collaboration among 1,200+ statisticians and data scientists through forums, workshops, and resource sharing.

• Computational Complexity
• Graph Algorithms
• Distributed Algorithms
• +۶ مورد دیگر

Aris T. Pagourtzis is a Professor of Computer Science at the School of Electrical and Computer Engineering of the National Technical University of Athens (NTUA), where he also serves as the Head of the Computer Science Division. He is additionally a Lead Researcher at the Archimedes Research Center, Athena RC. His academic career includes positions at the University of Ioannina, the University of Liverpool, the ETH Zuerich, the University of Athens, and the Athens University of Economics and Business. Education: Diploma in Electrical Engineering (1989) and Ph.D. in Electrical and Computer Engineering (1999), both from the National Technical University of Athens Professor Pagourtzis's research spans multiple areas of theoretical computer science, with particular emphasis on computational complexity, graph algorithms, distributed algorithms, approximation algorithms, network algorithms, cryptography, and counting complexity. His work often bridges theoretical foundations with practical applications in network design, security protocols, and optimization problems. He has developed novel algorithms for problems ranging from community detection in networks to Byzantine fault-tolerant protocols and privacy-preserving voting systems. His recent publications show a continued focus on fundamental algorithmic problems while expanding into newer areas like temporal graph analysis, blockchain applications, and privacy-preserving technologies. There's a clear trend toward addressing real-world challenges through rigorous theoretical frameworks, particularly in distributed systems, secure computation, and optimization under constraints. Professor Pagourtzis has served on program and organizing committees for numerous theoretical computer science and cryptography conferences, co-chairing CIAC 2017 and FCT 2021. His research has received funding from diverse sources including US, UK, French, EU, and Greek national resources. He is actively involved in teaching both undergraduate and graduate courses at NTUA, including Algorithms and Complexity, Foundations of Computer Science, Computational Cryptography, and Network Algorithms and Complexity. He leads the Computation and Reasoning Laboratory (corelab) at NTUA, which focuses on theoretical computer science research.

Eleni Staiمشاهده پروفایل

استادیار

• Optimization
• Communications Networks
• Data Analytics
• +۴ مورد دیگر

Eleni Stai is an Assistant Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), affiliated with the Division of Communication, Electronic and Information Engineering. She holds advanced degrees in Electrical Engineering, Mathematics, and Applied Mathematical Sciences from NTUA and the National and Kapodistrian University of Athens. Her academic credentials include: Diploma in Electrical and Computer Engineering, NTUA (2009) B.Sc. in Mathematics, National and Kapodistrian University of Athens (2013) M.Sc. in Applied Mathematical Sciences, NTUA (2014) Ph.D. in Electrical Engineering, NTUA (2015) Dr. Stai's research integrates advanced optimization techniques with communications networks and energy systems. She develops stochastic and deterministic optimization frameworks for network resource allocation, data analytics on complex topologies, and smart-grid control applications. Her work bridges theoretical foundations with practical implementations in energy-harvesting networks, network slicing, and reinforcement learning for distributed systems. Analysis of her recent publications reveals dominant research thrusts in AI-driven network management (particularly O-RAN and network slicing), energy-integrated communications, and optimization of energy communities. A significant portion of her work addresses the convergence of 5G/6G networking with power systems, emphasizing real-time control and sustainability. Her scientific contributions have been recognized through prestigious awards: Chorafas Foundation Best Ph.D. Thesis award Thomaidis Foundation Best M.Sc. Thesis award Best Paper Award at ICT 2016 Best Presenter Award at IEEE ENERGYCON 2022 Dr. Stai serves on technical program committees for major international conferences and has co-authored the book "Evolutionary Dynamics of Complex Communications Networks". She teaches undergraduate courses in Queuing Systems, Computer Networks, and Social Network Analysis, reflecting her expertise in network theory and applications. Her research trajectory demonstrates continuous evolution from fundamental network optimization to AI-enhanced solutions for next-generation communication-energy systems. Her work builds upon her postdoctoral experience at EPFL (2016-2020) and ETH Zurich (2020-2023), where she developed advanced frameworks for communications networks and energy systems.

Sarah E. Chasinsمشاهده پروفایل

استادیار

• Programming Languages
• Human-Computer Interaction
• Program Synthesis
• +۳ مورد دیگر

Sarah E. Chasins is an Assistant Professor in the Electrical Engineering and Computer Sciences (EECS) department at the University of California, Berkeley, with research spanning programming languages and human-computer interaction. She leads the PLAIT Lab (Programming Languages for Approachable and Inclusive Tools) and serves as a faculty affiliate at the Berkeley Institute for Data Science (BIDS). Her work bridges computer science with social sciences, climate reporting, legal systems, and biological research through extensive collaborations. Dr. Chasins' research focuses on democratizing programming for non-traditional programmers including scientists, social scientists, journalists, and data scientists. Her work emphasizes creating approachable programming tools that help practitioners reach correct programs while understanding, extending, and trusting those programs. She specifically investigates program synthesis, programming tools for scientific domains, and human-centered programming language design. Her research mission aims to make programming a path to a more informed and evidence-driven society rather than just a way to get wrong answers faster. Her recent publications demonstrate a clear trajectory toward making programming more accessible and understandable. The work spans code search techniques, program synthesis approaches, refactoring tools, and studies of how domain experts interact with programming languages. A consistent theme across her research is placing human needs at the center of programming language design and implementation. Dr. Chasins actively mentors PhD students including Justin Lubin, Eric Rawn, Parker Ziegler, Sarah "Slim" Lim, Hellina Hailu Nigatu, David Minh-Duy Cao, and Marlena Preigh. She has previously advised numerous master's and undergraduate students who have gone on to work in both academia and industry. Her teaching includes core courses like CS164 (Programming Languages and Compilers) and specialized courses like CS294-184 (Building User-Centered Programming Tools) and CS39-001 (Technology, Society, and Power). She maintains an active service record in the programming languages community, having served on program committees for major conferences including PLDI, POPL, OOPSLA, and SPLASH. Notably, she co-chaired the Student Research Competition at PLDI 2020 and 2021 and has been involved in organizing workshops focused on programming languages and human-computer interaction.

Todd Millsteinمشاهده پروفایل

استاد

• Network Verification
• Programming Languages
• Probabilistic Programming
• +۳ مورد دیگر

Todd Millstein is a Professor in the Computer Science Department at the University of California, Los Angeles (UCLA). He served as the Computer Science Department Chair from 2022-2025 and is also an Amazon Scholar. His research focuses on making software systems more reliable through programming languages techniques, with significant contributions to network verification and probabilistic programming. Millstein received his Ph.D. from the University of Washington Department of Computer Science, where he was a member of the Cecil group led by Craig Chambers. Prior to that, he completed his undergraduate studies at Brown University under the guidance of Paris Kanellakis and Pascal Van Hentenryck. Millstein's research spans several areas of programming languages and systems with a focus on reliability. He has made significant contributions to network verification, developing the Batfish network configuration analyzer which is now managed by Amazon Web Services and forms the basis of Oracle Cloud's Network Path Analyzer. His work has been recognized with the ACM SIGCOMM Networking Systems Award in 2025. He also works on interactive program verification through lemma synthesis and scalable reasoning methods for probabilistic programming languages. His research bridges programming languages theory with practical systems challenges, as highlighted in his SPLASH/OOPSLA 2024 keynote "Everything is a Program (even if it's not)". Millstein's recent publications demonstrate a consistent focus on verification and reliability across multiple domains. His work shows a progression from foundational programming language techniques to practical applications in networking and probabilistic systems. Key themes include data-driven approaches to program analysis, synthesis of verification artifacts, and applying programming languages techniques to non-traditional domains like network configuration. Millstein's scientific achievements have been recognized with numerous prestigious awards including an NSF CAREER Award, an ACM SIGPLAN Most Influential PLDI Paper Award, an ACM SIGCOMM Networking Systems Award, IEEE Micro Top Picks selection, best-paper awards from PLDI, OOPSLA, and SIGCOMM, a Microsoft Research Outstanding Collaborator Award, an Okawa Foundation Research Grant, an IBM Faculty Award, and a Facebook Research Award. He has also received both the Northrop Grumman Excellence in Teaching Award (for junior faculty) and the Eon Instrumentation Inc. Excellence in Teaching Award (for senior faculty) from UCLA Engineering. Millstein advises several Ph.D. students including Ana Brendel, Poorva Garg (co-advised with Guy Van den Broeck), Rajdeep Mondal (co-advised with George Varghese), and Rathin Singha (co-advised with George Varghese). His research has been supported by various grants including an NSF CAREER Award, Okawa Foundation Research Grant, IBM Faculty Award, and Facebook Research Award. He has also been a Co-Founder and Chief Scientist of Intentionet, which was later acquired by Amazon Web Services. Millstein is actively involved in the Batfish project, an open-source network configuration analyzer that has had significant practical impact. Batfish is now managed by AWS, powers Oracle Cloud's Network Path Analyzer, and is used by dozens of companies. His research group continues to work on network reliability, developing techniques for scalable BGP policy verification and behavioral testing of protocol implementations.

David Naumannمشاهده پروفایل

استاد

• formal methods
• software security
• relational verification
• +۷ مورد دیگر

David Naumann is Professor and Department Chair of Computer Science at Stevens Institute of Technology. His leadership in the department and active research program positions him as a key figure in programming languages and formal methods research. Naumann's research focuses on formal methods and software security, with particular emphasis on relational and hyperproperty verification , fine-grained confidentiality/integrity policies , and program analysis and verification . His work bridges theoretical foundations with practical applications in security-critical systems. He has developed novel program logics and verification techniques that enable precise reasoning about information flow and security properties. His recent publications (2022-2025) reveal a strong trend toward modular relational verification techniques with applications to pointer programs, distributed systems, and concurrent applications. The research spans theoretical foundations (algebraic structures for alignment) to practical tools (WhyRel prototype), demonstrating both depth and breadth in addressing verification challenges. Naumann has served as program committee co-chair for IEEE Computer Security Foundations Symposium (2021-2022) and has been active on committees for POPL, CCS, CSF, ECOOP, and other top venues. His editorial service includes ACM Transactions on Programming Languages and Systems, Formal Aspects of Computing, and Journal of Object Technology. He leads the Cypress research group at Stevens Institute of Technology and has secured significant funding from NSF, Microsoft Research, and Siemens. His mentoring extends to numerous PhD students who have gone on to successful careers in academia and industry.

• Software Technology
• Artificial Intelligence
• Educational Software
• +۵ مورد دیگر

Maria Virvou serves as Professor and Chair of the Department of Informatics at the University of Piraeus, where she also directs the Graduate Program in Informatics and leads the Research Laboratory 'Software Technology'. She holds significant institutional leadership roles including membership in the University Senate and has chaired the Department of Informatics for multiple terms. As Editor-in-Chief of Springer book series 'Learning and Analytics in Intelligent Systems' and 'Artificial Intelligence-Enhanced Software and Systems Engineering', she maintains substantial academic influence across international scholarly platforms. Dr. Virvou earned her PhD in Computer Science and Artificial Intelligence from the University of Sussex with a scholarship from the State Scholarships Foundation, a Master of Science in Computer Science from University College London, and her undergraduate degree from the Department of Mathematics at the National and Kapodistrian University of Athens. Her educational background in both mathematics and computer science has provided a strong foundation for her interdisciplinary research approach. Professor Virvou's research spans Software Technology, Artificial Intelligence, Educational Software and Games, User Modeling, and Human-Computer Interaction. She has pioneered work in personalized interactive software systems, applying fuzzy logic and machine learning techniques to create adaptive educational environments. Her recent work demonstrates a strategic expansion into AI applications for healthcare, with significant contributions to medical diagnostics using large language models and multimodal AI systems. She has also made notable advances in smart tourism applications through personalization techniques. With over 400 publications to her name, Professor Virvou's scholarly output shows a clear progression from foundational work in user modeling toward increasingly sophisticated AI applications across multiple domains. Her publication trends reveal a strategic focus on explainable AI, multimodal systems, and practical implementations that bridge theoretical advances with real-world applications, particularly in healthcare and education sectors. Ranked #1 worldwide in 'User Modelling' publications (147,450 total publications) according to Scopus Ranked #1 worldwide in 'Educational Software' publications according to both Scopus and Microsoft Academic Search Recognized among the top 2% of most influential Artificial Intelligence scientists worldwide by Stanford University General Co-Chair at the 14th IISA Conference 2023 Invited Keynote Speaker at the 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023) As Director of the Research Laboratory 'Software Technology', Professor Virvou has built a robust research team focused on AI applications across multiple domains. She co-founded and co-chairs the IEEE Intelligent Information Systems and Applications international conference series, creating a significant platform for scholarly exchange. Her leadership extends to editorial roles with major academic publishers and active participation in international research collaborations that have secured substantial funding for innovative projects in AI and software engineering.

Fei Heمشاهده پروفایل

دانشیار

• formal methods
• program analysis
• automated reasoning
• +۲ مورد دیگر

Fei He is an Associate Professor at Tsinghua University's School of Software, where he leads the THUFV research lab focused on formal verification and program analysis. His research spans formal methods, automated reasoning, and program verification, with applications in concurrent systems, networking (P4 programs), and probabilistic systems. Education & Employment: PhD from Tsinghua University (2008) Visiting Scholar at Carnegie Mellon University (2010-2011) and Politecnico di Milano (2006-2007) Faculty positions at Tsinghua since 2008 (Assistant Professor 2008-2011, Associate Professor 2011-present) Research: He's developed innovative techniques in SMT solving for concurrency verification, termination analysis, and regression verification. His tools like Deagle have won gold medals at SV-COMP. Current work focuses on probabilistic program verification and network program analysis. Publications: His 80+ publications demonstrate consistent contributions across formal methods (PLDI, OOPSLA, ICSE), networking (NSDI, INFOCOM), and software engineering (TSE, TOSEM), with recent emphasis on data-driven verification and automated invariant inference. Awards: Gold Medals in SV-COMP ConcurrencySafety (2022, 2023, 2025) Best Paper Awards at PPoPP 2022 and SETTA 2022 Advising: Mentors 13 PhD/Master's students in THUFV lab, with graduates joining Huawei, MPI-SP, and research institutions. Secured multiple NSF China grants for trustworthy software research. Service: Associate Editor for Theory of Computing Systems, program committees for PLDI/ICSE/OOPSLA, and former Local Chair for ISSTA 2019.

• VLSI Design
• Built-In Self-Test (BIST)
• Test Data Compression
• +۷ مورد دیگر

Chr. Kavousianos is an Assistant Professor in the Department of Informatics at the University of Ioannina, Greece. He is actively engaged in research and teaching in the fields of VLSI design, testability, and low-power testing. He has been involved in major national and international research programs such as Heracleitus II, Pythagoras, and NSF-SRC (USA). Research Interests: His research focuses on advanced techniques in built-in self-test (BIST), test data compression, scan-based testing, fault tolerance, and embedded control architectures. He explores methods to reduce test data volume, power consumption during testing, and improve defect coverage in integrated circuits. Publication Trends: His recent publications (2004–2011) show a strong trend toward defect-aware testing, power-efficient test compression, and multicore SoC testing. He frequently collaborates with leading researchers, including Prof. Krishnendu Chakrabarty (Duke University). His work on multilevel Huffman coding and reseeding techniques has been highly influential, with one paper among the most accessed in 2004. Special Distinction for Excellent Academic Performance from TEE, 1996 Doctoral Scholarship 'In Memory of Professor Maritsa', 1999 Postdoctoral Scholarship from IKY, 2002 Advising and Grants: He has supervised multiple postdoctoral researchers, PhD candidates (e.g., Vasilis Tenentes, Emmanouil Kalligeros), and master’s students. He has led research projects such as 'Embedded Control Architectures' (Heracleitus II) and 'Design Techniques for Embedded Self-Control Circuits' (Pythagoras II). His international collaboration with Duke University included a postdoctoral research role in 2009. Labs and Teams: He leads a research group at the University of Ioannina with postdocs, PhD students, and visiting professors, including Prof. Krishnendu Chakrabarty. His team works on cutting-edge VLSI testing and design methodologies.

• Informatics Law
• Cyber Law
• Data Protection
• +۹ مورد دیگر

Ioannis Iglezakis is an Associate Professor at the School of Law, Aristotle University of Thessaloniki (AUTH), specializing in the intersection of law and technology. His academic career spans over three decades with continuous contributions to informatics law, cyber law, data protection, and privacy law. At AUTH, he teaches courses including Law of Informatics, Computers and Law I (Cyberlaw I), Computers and Law II (Privacy and Security in the Information Society), Legal Aspects of Cybercrime, Internet-Law, and Law and Information Technology. Dr. Iglezakis earned his undergraduate degree in Law from AUTH in 1987, followed by a Magister Legum Europae from Hannover University in 1993. He completed his postgraduate studies in History, Philosophy and Sociology of Law at AUTH in 1990 and earned his PhD in Law from AUTH in 1999. His educational background combines Greek legal training with European legal perspectives. His research interests focus on the legal challenges posed by digital technologies, with particular emphasis on data protection, privacy law, cybercrime regulation, digital rights, and the application of GDPR in various contexts. He has published extensively on topics including the right to be forgotten, digital identity management, workplace surveillance in the digital age, hate speech online, and the legal implications of emerging technologies like blockchain and artificial intelligence. His work bridges theoretical legal analysis with practical applications in the rapidly evolving digital landscape. The trends in his publications reveal a consistent focus on the evolving relationship between law and technology, with increasing attention to GDPR implementation, health data protection, and the challenges of algorithmic decision-making. His work spans multiple disciplines including legal theory, privacy studies, cyber security, and digital governance, reflecting the interdisciplinary nature of modern informatics law. Dr. Iglezakis has supervised over 50 master's theses at AUTH, mentoring the next generation of legal scholars in areas including cloud computing contracts, personal data protection, social media law, intellectual property in digital environments, and cybercrime. His administrative roles have included membership on the European Educational Programs Committee (2011-2012) and the Legal Committee of AUTH (2013-2014). His research projects include the 2018-2019 study on 'Legal Issues of Mobile Applications Development, Distribution and Use,' the 2014 '6th International Conference on Informatics Law,' and the 2013-2015 Center of Excellence for Cybercrime for Education, Research and Training in Greece. These projects highlight his commitment to addressing practical legal challenges in the digital domain while contributing to academic discourse.

Efthymios N. Karatzasمشاهده پروفایل

استادیار

• Numerical Analysis
• Computational Mathematics
• Optimal Control
• +۵ مورد دیگر

Efthymios N. Karatzas serves as an Assistant Professor in the Department of Mathematics at Aristotle University of Thessaloniki, Faculty of Sciences, within the Computer Science and Numerical Analysis Section. He maintains an active research profile in computational mathematics with strong institutional affiliations including collaborations with SISSA mathLab and FORTH Institute of Applied and Computational Mathematics. His academic credentials include: PhD in Mathematics, National Technical University of Athens (2015) Master's in Applied Mathematical Sciences – Computational Mathematics, NTUA (2009) Master's in Applied Mathematics, University of Patras (2001) Bachelor's in Mathematics (Computational Mathematics), University of Patras (1999) Dr. Karatzas' research program centers on advanced numerical techniques for partial differential equations , with pioneering work in reduced order modeling , embedded boundary methods , and optimal control systems . His expertise spans computational fluid dynamics, uncertainty quantification, and biomechanical applications, characterized by methodological innovation in handling geometrically complex domains through cut finite element approaches and shifted boundary formulations. Analysis of his 15 most recent publications reveals a cohesive research trajectory focused on developing efficient numerical frameworks for parametrized PDE systems. His work consistently bridges theoretical rigor with practical implementation, particularly in advancing reduced basis methods for fluid-structure interaction and biological modeling, demonstrating significant contributions to computational mathematics through high-impact journal publications. No major scientific awards are documented in the available sources. Dr. Karatzas demonstrates research leadership through project management roles including Scientific Manager for the ELIDEK project at NTUA (2019-2021) and Project Manager for the European Social Fund HEaD initiative at SISSA (2017-2019). His grant administration experience encompasses coordinating interdisciplinary teams and securing external funding for computational mathematics research. He maintains active collaborations with the SISSA mathLab in Trieste (particularly with Prof. Gianluigi Rozza's group) and the FORTH Institute in Crete, participating in international workshops including the Reduced Order Methods in CFD Summer School (2019) and SIAM UQ conferences. His research network spans computational mathematics groups across Europe with emphasis on advancing numerical methodologies for real-world engineering and biological applications.

Stavros Demetriadisمشاهده پروفایل

استاد

• Learning Technologies
• Educational Technology
• ICT in Education
• +۷ مورد دیگر

Stavros Demetriadis is a Full Professor at the School of Informatics, Aristotle University of Thessaloniki, Greece. His research focuses on Learning Technologies, including Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning (CSCL), Computational Thinking, and Massive Open Online Courses (MOOCs). He has led EU-funded projects like colMOOC and developed educational tools such as 'pytolearn' for Python instruction and 'Cubes Coding' (winner of Open Education Challenge 2014 and NUMA Competition 2014). He has supervised 5 completed PhD theses, 4 ongoing PhDs, and over 60 Master’s theses. Academic Appointments: Full Professor (2020–present), Associate Professor (2015–2020), Assistant Professor (2012–2015), Lecturer (2002–2008), Informatics Teacher (1989–2002) Education: PhD in Multimedia Technology in Education (2000), MSc in Electronic Physics (1986), BSc in Physics (1983) His work bridges AI and education, with over 161 publications and an h-index of 27. Recent research explores ChatGPT integration, ethics in Learning Analytics, and AI-driven assessment tools. He has delivered invited talks at institutions like the University of Valladolid (2024) and coordinates the 'Teachers' Fast-paced Distance Training on Tele-education' project. Awards include three international best paper awards and recognition for his 'Cubes Coding' project. Key Research Contributions: Developed frameworks for Conversational Agents in CSCL Innovated Computational Thinking pedagogy through robotics Explored ethics and culture in Learning Analytics adoption Created Python-based MOOCs for non-programmers He has taught courses like Human-Computer Interaction and Learning Analytics, and led short programs on Conversational AI. His collaborations span institutions in Spain, Denmark, and Greece. ORCID: 0000-0002-1561-6372; Google Scholar, Semantic Scholar, and Scopus profiles list his extensive output.

John Regehrمشاهده پروفایل

استاد

• Compilers
• Software Testing
• Formal Verification
• +۳ مورد دیگر

John Regehr is a Professor at the School of Computing, University of Utah, specializing in compilers, software testing, and formal verification. His research develops tools to improve software correctness and efficiency, including Csmith (random C program generator) and C-Reduce (test-case reducer). His group focuses on compiler validation, fuzzing techniques, and superoptimization, primarily targeting the LLVM infrastructure. Research interests span compilers, testing methodologies, formal verification, embedded systems, and program analysis. Recent work emphasizes practical tools backed by formal methods to detect and prevent software errors. Publications demonstrate strong trends in compiler verification and testing, with consistent focus on LLVM optimization correctness, translation validation, and automated bug detection through fuzzing and synthesis techniques. Scientific awards include: PLDI 2015 Distinguished Paper Award ICST 2014 Best Paper Award ACM SIGSOFT Distinguished Paper Award Leads a research group developing tools like Souper (superoptimizer) and Alive2 (translation validator). Maintains active academic service through program committees (PLDI, CGO, OOPSLA) and contributes to open-source compiler infrastructure.

• Database Systems
• Distributed Systems
• Machine Learning Systems
• +۳ مورد دیگر

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