Amalia Foka is an Assistant Professor in Computer Science Applications for the Arts at the Department of Fine Arts & Art Sciences , School of Fine Arts , University of Ioannina , Greece. She has held academic positions at the University of Patras (2005-2013), University of Ioannina (2005-2008), and Computer Technology Institute & Press "Diophantus" (2014-2015). Her research bridges Artificial Intelligence with Digital Art , focusing on Generative AI , Social Media Mining , and Human-Computer Interaction within artistic contexts. Education: BEng in Computer Systems Engineering (1998) from the University of Manchester Institute of Science & Technology (UMIST) , UK MSc in Advanced Control (1999) from UMIST PhD in Robotics (2005) from the Department of Computer Science , University of Crete Her artistic research includes projects like Bushwalking (StyleGAN2 landscape generation), Breaking the Silence (NLP analysis of taboo topics), and The Invisible Structures of the Artworld (social media-driven network visualization). She leads the Multimedia Lab at the University of Ioannina, focusing on AI in Creative Processes and Digital Interaction methodologies.
John Psarras is a Professor at the National Technical University of Athens (NTUA) in the School of Electrical and Computer Engineering, specifically within the Division of Industrial Electric Devices and Decision Systems. He serves as the Director of the Decision Support Systems Laboratory (DSSlab) and the University Research Institute of Communication and Computer Systems. He holds a Diploma in Mechanical Engineering (1982) and a Ph.D. in Electrical and Computer Engineering (1989), both from NTUA. His research specializes in decision support systems with applications in energy management, environmental analysis, and information systems. Key areas include: Multi-criteria analysis for energy policy and renewable integration AI-driven optimization of smart grids and building efficiency Sustainable finance mechanisms for green projects Blockchain applications in education and data security His recent publications (2023–2025) demonstrate a strong focus on AI-enhanced decision tools for energy transitions, smart infrastructure, healthcare diagnostics, and cross-border renewable cooperation, reflecting interdisciplinary innovation. He has supervised 22 PhD theses and coordinates EU-funded projects in energy policy, clean technology, and capacity building. No scientific awards are listed in available sources. He leads the Decision Support Systems Laboratory (DSSlab), advancing research in energy analytics, and directs the University Research Institute of Communication and Computer Systems, facilitating large-scale interdisciplinary collaborations.
Dimitris Mitropoulos is an Assistant Professor at the National and Kapodistrian University of Athens (NKUA) in the Department of Business Administration, where he teaches courses on Distributed Ledger Technologies, Data Security and Privacy, Algorithms and Business Analytics, and Introduction to Programming. He also serves as Head of the Reliability Engineering Directorate at the National Infrastructures for Research and Technology (GRNET), Greece's national research and education network organization. Previously, he was a Postdoctoral Researcher in the Computer Science Department at Columbia University. Dr. Mitropoulos received his Ph.D. degree in Secure Software Development Technologies from the Athens University of Economics and Business (AUEB) in 2014. His doctoral research was supported by the Heracleitus II Scholarship, co-financed by the European Union and Greek national funds. He is a member of prestigious professional organizations including ACM, IEEE, and USENIX. Dr. Mitropoulos conducts pioneering research at the intersection of software engineering and cybersecurity, with particular expertise in secure software development, vulnerability analysis, and blockchain security. His work spans multiple dimensions of software security including code injection attacks, infrastructure as code security, smart contract analysis, and dependency management in software ecosystems. His research methodology combines static and dynamic analysis techniques with empirical studies of real-world software systems, particularly focusing on Java, Python, and Solidity ecosystems. His recent work has made significant contributions to understanding security vulnerabilities in modern software development practices and infrastructure management. Dr. Mitropoulos has received numerous prestigious awards for his research contributions, including the Research Excellence Award from NKUA (2025), Distinguished Paper and Artifact Awards at PLDI '22, Best Data Showcase Award at MSR 2018, and multiple postdoctoral research funding scholarships. His work on "Finding typing compiler bugs" was recognized with both Distinguished Paper and Artifact Awards at PLDI '22, highlighting the significance and reproducibility of his research. He has also received recognition for his service to the academic community, including a Certificate of Appreciation from ESEC/FSE '21 for his contributions to conference organization. Dr. Mitropoulos has been actively involved in securing research funding and leading significant research projects. He currently serves as Principal Investigator for the SecOPERA project (2023-Today), funded by the European Commission under Horizon Europe. Previously, he contributed to several major EU and US-funded projects including eSSIF-Lab (2019-2022), FASTEN (2019-2022), PRIViLEDGE (2018-2021), CERTCOOP (2017-2020), PANORAMIX (2016-2019), and TREDISEC (2016-2018). His research has been supported by diverse funding sources including the European Commission's Horizon 2020 program, the National Science Foundation, and the Defense Advanced Research Projects Agency (DARPA). Dr. Mitropoulos plays an active role in the international research community through various leadership positions. He serves on program committees for top-tier conferences including OOPSLA (2026), ICSE (2026), ESEC/FSE (2025), and ISSTA (2025). He has previously served as Workshop Co-Chair for ISSTA 2025 and Student Volunteer Chair for ESEC/FSE 2021. His contributions to mentoring the next generation of researchers include serving as a mentor for the ICSE Student Mentoring Workshop (2022) and supervising Google Summer of Code projects (2017).
Timothy M. Jones is a Professor of Computer Architecture and Compilation at the University of Cambridge Computer Laboratory, where he leads research in systems-level computing. He is also a Fellow at Gonville and Caius College, contributing to academic leadership and student mentorship within the collegiate system. His primary affiliation with the Computer Laboratory positions him at the forefront of systems research within the university. Dr. Jones's research focuses on extracting various forms of parallelism (thread-level, data-level, memory-level) to enhance computational performance while addressing energy efficiency and reliability challenges. His work spans compiler design, binary translation, and microarchitecture optimization, with specific interest areas including: Compiler technologies for functional and parallel programming Hardware reliability and fault tolerance mechanisms Binary analysis and instrumentation frameworks Memory system optimization and virtual memory management Security enhancements through binary modification Runtime systems for heterogeneous architectures Analysis of his recent publications reveals strong emphasis on systems-level innovation, particularly in fault tolerance techniques, binary analysis tools, memory optimization, and parallel execution frameworks. His work consistently bridges theoretical computer science with practical hardware implementation challenges. Dr. Jones maintains active participation in the academic community through conference leadership roles, including serving as Program Co-Chair for CGO 2026 and committee positions at premier venues including ISMM, CGO, and ECOOP. He contributes to open-source academic resources through GitHub and maintains professional engagement via Twitter.
Theodora Varvarigou is a Professor in the Department of Electrical and Computer Engineering at the National Technical University of Athens (NTUA). She holds a B.Eng. from NTUA and M.Eng. and Ph.D. degrees from Stanford University. Her career includes research at AT&T Bell Labs and roles at the Technical University of Crete. From 2008-2012, she served as director of NTUA's 'Technoeconomic Systems' postgraduate program. Her research focuses on Cloud Computing, Multimedia Content Processing, Social Networking Technologies, and emerging areas like blockchain, edge computing, and cybersecurity. She has published over 200 papers and led numerous European research projects, emphasizing scalable systems, data management, and smart infrastructure applications. Her work spans technical innovations such as intrusion detection systems, edge resource optimization, and blockchain-based solutions for IoT, healthcare, and smart cities. Recent publications highlight advancements in AI-driven resource allocation, privacy-preserving blockchain designs, and predictive analytics for edge computing environments. Professor Varvarigou has contributed to interdisciplinary initiatives, including cohort data harmonization in biomedical research and social media analytics for urban planning. Her teaching includes courses on digital systems, network programming, and fault-tolerant systems.
Ion Androutsopoulos is a Professor of Artificial Intelligence in the Department of Informatics at Athens University of Economics and Business (AUEB), where he also serves as Head of Department. He is founder and co-director of AUEB's Natural Language Processing Group and an Adjunct Researcher at the Digital Curation Unit and "Archimedes" Research Unit of the Research Centre "Athena". His research spans multiple dimensions of Artificial Intelligence with a focus on Natural Language Processing. Key interests include: Machine learning in NLP, particularly deep learning and large language models Question answering and retrieval augmented generation for document collections Dialog systems for new languages and knowledge domains Sentiment analysis and emotion recognition from text and speech Detecting toxic posts and disinformation online Image-to-text generation for medical diagnostics NLP applications in biomedical, legal, and financial domains His recent publications demonstrate strong activity across medical AI (particularly ImageCLEFmed Caption competitions where his group consistently ranks 1st-2nd), legal NLP (LexGLUE benchmark), financial NLP (EDGAR-CRAWLER), and multilingual challenges. His work shows increasing emphasis on large language models, explainability, and practical applications. Notable awards include: Top 2% scientist worldwide (Stanford University database, 2023) Multiple AUEB Excellent Teaching Awards (2017-18, 2021-22, 2023-24) Three consecutive BioASQ awards (2018-2020) Multiple 1st/2nd place rankings in ImageCLEFmed Caption competitions (2021-2025) He actively organizes major events including the Athens Natural Language Processing Summer School (AthNLP) and SemEval tasks. His group maintains strong industry and research collaborations, particularly in medical AI applications where they've developed systems that generate diagnostic captions from medical images with state-of-the-art performance.
Manos Kapritsos is an Associate Professor in the Department of Computer Science and Engineering at the University of Michigan's College of Engineering. He leads the GLaDOS research group focusing on reliability of distributed systems through formal verification and fault-tolerant replication techniques. His research spans: Formal verification of concurrent and distributed systems Fault-tolerant replication protocols beyond client-server models Automation of verification processes for complex systems Performance verification including latency properties Reliable cryptographic code implementation Analysis of his publications reveals strong emphasis on: developing automated verification tools (Armada, Vale, IronFleet), creating novel replication protocols (Aegean), verifying performance characteristics (Performal), and improving specification reliability (IronSpec). His work consistently bridges theoretical formal methods with practical systems implementation. Awards and honors include: Jay Lepreau Best Paper Award at OSDI 2025 Jon R. and Beverly S. Holt Award for Excellence in Teaching (2022) NSF CAREER Award (2021) Distinguished Paper Award at PLDI 2020 Google Faculty Award (2017) Distinguished Paper Award at USENIX Security 2017 Grant support includes NSF FMitF grants (2020, 2023), NSF Large grant (2021), DARPA grant (2020), and Google Faculty Award (2017). He advises PhD students through the GLaDOS group, focusing on distributed systems verification. He directs the GLaDOS lab at University of Michigan, developing verification frameworks and reliable distributed systems. Current projects include automated proof generation (Basilisk) and efficient communication protocols (Scrooge).
Pavel Panchekha is an Assistant Professor in the School of Computing at the University of Utah, where he holds the Warnock Chair for Junior Faculty. His research spans programming languages, web browsers, and numerical analysis, with a focus on developing programming language techniques to address challenges across computer science. Dr. Panchekha received his educational training at prestigious institutions: PhD in Computer Science from the Paul G. Allen School for Computer Science and Engineering at the University of Washington, advised by Michael D. Ernst and Zachary Tatlock BS in Mathematics from MIT Panchekha's research program has two major thrusts. First, he works on web browser internals , with projects including fuzzing layout invalidation, multi-tenant garbage collection, and optimizing 2D graphics. He is also authoring a textbook on web browsers that informs much of this research. Second, he focuses on automatic numerical analysis , with projects such as automatic accuracy improvement, synthesis via term rewriting, scalable static accuracy analysis, and math library implementation. He leads the FPBench and Herbie projects, which are major deployments of his research. His scholarly output demonstrates consistent contributions across programming languages, verification, and numerical methods. Recent work shows a growing emphasis on bidirectional typing systems, layout invalidation in browsers, and robust floating-point error analysis. His publications reveal a trajectory from foundational work on floating-point accuracy (notably the Herbie tool that won a Distinguished Paper Award at PLDI 2015) toward more comprehensive systems for program synthesis, verification, and browser optimization. Panchekha has received significant recognition for his research contributions: NSF Fellowship ARCS Foundation Fellowship Adobe Research Fellowship Wissner-Slivka Foundation Fellowship 2015 PLDI Distinguished Paper Award for work on the Herbie numerical analysis and repair tool As an advisor, Panchekha mentors a substantial group of students across multiple levels. He currently advises six students: Marisa Kirisame (PhD), Bhargav Kulkarni (PhD), Yumeng He (PhD), Artem Yadrov (MS), Jesus Ponce (BS), and Jonas Regehr (BS). Previously, he has advised over twenty students including PhD candidates like Ian Briggs and numerous MS and BS students. His advising spans theoretical topics in programming languages and practical applications in web browsers and numerical computing. Panchekha leads research groups focused on programming languages applications to web browsers and numerical analysis. His work on the Herbie tool for floating-point accuracy improvement has become influential in the programming languages community, and his more recent work on browser internals is shaping how researchers understand and optimize modern web rendering engines. He is currently developing a textbook on web browsers that aims to synthesize knowledge about browser architecture and implementation.
Christos Makris is an Associate Professor in the Department of Computer Engineering and Informatics at the University of Patras, Greece. His academic career spans over two decades with significant contributions to computer science, particularly in data structures, algorithms, and information systems. He maintains active research collaborations and supervises graduate students in his areas of expertise. Dr. Makris's research spans several key areas in computer science with a strong focus on efficient data organization and processing. His work encompasses Data Structures , Information Retrieval , Data Mining , String Management and Processing Algorithms , Computational Geometry , Internet Technologies , Bioinformatics , and Multimedia Databases . His interdisciplinary approach bridges theoretical computer science with practical applications across various domains including web technologies, bioinformatics, and emergency response systems. Analysis of Dr. Makris's publication record reveals a consistent research trajectory focused on efficient algorithms for information management. His work demonstrates evolution from foundational data structure research in the 1990s to more applied work in web technologies, social media analysis, and machine learning applications in recent years. A notable pattern is his ability to adapt core algorithmic techniques to emerging application domains while maintaining theoretical rigor. Dr. Makris maintains an impressive scholarly record with over 3,000 citations, an h-index of 29, and an i10-index of 71 according to Google Scholar metrics. These indicators reflect the significant impact of his research within the computer science community. As an active faculty member, Dr. Makris maintains regular office hours on Tuesdays from 18:00-20:00 and Thursdays from 12:00-14:00. He is accessible via email at makri@ceid.upatras.gr or makri@upatras.gr for academic inquiries and student supervision.
Athanasios Liavas is a Professor at the Technical University of Crete in the School of Electrical and Computer Engineering , specializing in Signal Processing for Telecommunications and Information Theory . He has held administrative roles as Department Chair (2009-2011), Vice Chair (2011-2013), and Dean of the ECE School (2017-2021). Education: Diploma (1989) and PhD (1993) in Computer Engineering and Informatics from the University of Patras. Professional Background: Postdoctoral Marie Curie Fellow at INT, Evry (1996-1998); Lecturer at University of Ioannina (1999-2001); Assistant/Associate Professor at University of the Aegean (2001-2004) and Technical University of Crete (2004-present). His research focuses on Signal Processing for Telecommunications , Information Theory , and Tensor Decomposition . Recent work involves nonnegative tensor factorization , parallel algorithms , and fMRI data analysis , with applications in wireless communications and medical imaging . Articles show trends in optimization algorithms , LDPC code design , and MIMO system robustness . Scientific Awards include: Marie Curie Fellowship (1996-1998) Associate Editor, IEEE Transactions on Signal Processing (2005-2009) Elected Member, IEEE Signal Processing for Communications and Networking Technical Committee (2006-2011) He has taught courses like Telecommunications Systems II , Wireless Communications , and Information Theory , and supervised students such as Despoina Tsipouridou (PhD) and Alex Balatsoukas-Stimming (Graduate). He leads projects like Partensor (Parallel Tensor Toolbox) and COOPCOM (Cooperative Communications), and contributes to labs including the Telecommunications Laboratory .
Full Professor at the School of Informatics, Aristotle University of Thessaloniki (AUTh), Greece. Previously served as Associate Professor (2015-2020), Assistant Professor (2008-2015), and Lecturer (2002-2008) at the same institution. Also worked as an Informatics Teacher in Greek Secondary Education from 1989-2002. His research focuses on Learning Technologies with emphasis on Conversational Agents in Education, Learning Analytics, Computer-Supported Collaborative Learning, Computational Thinking, Teaching Machine Learning at School, and Massive Open Online Courses (MOOCs). His recent work heavily investigates the application of AI, particularly conversational agents and large language models, in educational contexts. His publications show a strong trend toward AI applications in education, particularly focusing on conversational agents, learning analytics, and automated grading systems. The research spans multiple educational contexts from K-12 to higher education, with particular attention to student self-regulation, collaborative learning, and ethical considerations in AI implementation. 3 Best paper awards at international conferences Interview by Educational Technology Magazine (2013) Cubes Coding project - Winners of Open Education Challenge 2014 Cubes Coding project - Winners of NUMA Competition 2014 Has supervised 5 completed PhD theses, 4 ongoing PhD theses, over 60 Master's theses, and over 120 undergraduate theses. Led the colMOOC project (2018-2020), a €999,000 EU-funded project on integrating conversational agents and Learning Analytics in MOOCs. Also coordinated the T4E project (2020-2022) on Teachers' Fast-paced Distance Training on Tele-education and a MOOC in Greek on Introduction to Programming with Python. Previously served as Director of the Software and Interactive Technologies Laboratory (SWITCH Lab) until 2020, Member of AUTH Educational Policy Committee until 2020, and Chair of the Scientific Supervisory Board of the 2nd Experimental Junior High School in Thessaloniki until 2020.
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.
Scott Mahlke is a Professor and Associate Chair in the Electrical Engineering and Computer Science Department at the University of Michigan. He is affiliated with the Advanced Computer Architecture Laboratory and the Software Systems Laboratory, where he leads the Compilers Creating Custom Processors (CCCP) research group. His research focuses on compilers, computer architecture, and high-level synthesis, with particular emphasis on designing next-generation computer systems that overcome challenges in performance, power consumption, and reliability. His work bridges the gap between hardware and software through innovative compiler technology that enables customized processors and accelerators. Mahlke's publications demonstrate a strong focus on compiler techniques for exploiting instruction-level parallelism, memory system optimization, and application-specific processor design. His research spans from fundamental compiler algorithms to practical implementations in both general-purpose and embedded systems. National Science Foundation CAREER Award (2003) Morris Wellman Faculty Development Assistant Professor (2004) 2006 ISCA Most Influential Paper Award Multiple best paper awards at major architecture conferences As an advisor, Mahlke has chaired numerous Ph.D. dissertations and actively mentors graduate students in the CCCP group. His research is generously funded by the National Science Foundation, Gigascale Systems Research Center, ARM Ltd., Samsung Advanced Institute of Technology, and other major organizations. The CCCP group maintains strong industry partnerships that facilitate the transfer of research innovations to practical applications.
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.
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.
