جست‌وجوی استاد و پژوهشگر

Nate Fosterمشاهده پروفایل

استاد

• Programming Languages
• Networking
• Software-Defined Networking
• +۵ مورد دیگر

Nate Foster is a Professor of Computer Science at Cornell University's Bowers Computing and Information Science college. He also serves as a Visiting Professor at EPFL's Data Center Systems Laboratory during the 2023-24 academic year and as a Visiting Researcher at Jane Street. His research focuses on developing languages and tools that make it easy for programmers to build secure and reliable systems, with particular emphasis on software-defined networking. Dr. Foster's educational background includes: PhD in Computer Science from the University of Pennsylvania MPhil in History and Philosophy of Science from Cambridge University BA in Computer Science from Williams College Nate Foster's research spans multiple areas within programming languages and systems. His current work focuses on the design and implementation of languages for programming software-defined networks. He has also made significant contributions to bidirectional languages (also known as "lenses"), database query languages, data provenance, type systems, mechanized proof, and formal semantics. His interdisciplinary approach combines theoretical foundations with practical systems building, seeking to bridge the gap between formal methods and real-world network programming. An analysis of Foster's recent publications reveals a strong focus on network programming languages, particularly NetKAT and P4. His work consistently applies formal methods to networking problems, with increasing emphasis on verification, equivalence checking, and symbolic execution techniques. The research trajectory shows progression from foundational language design to practical verification tools, demonstrating how theoretical programming language concepts can solve real-world networking challenges. Dr. Foster has received numerous prestigious awards for his contributions: Sloan Research Fellowship NSF CAREER Award ACM SIGPLAN Robin Milner Young Researcher Award (2023) Most Influential POPL Paper Award Tien '72 Teaching Award Google Research Award Yahoo! Academic Career Enhancement Award Cornell Engineering Research Excellence Award Morris and Dorothy Rubinoff Award ACM SIGCOMM Rising Star Award As an active member of the programming languages community, Foster has advised numerous graduate students and secured significant research funding through his NSF CAREER award and Google Research Award. He has served in leadership roles for major conferences including PLDI, POPL, and ICFP, demonstrating his commitment to mentoring the next generation of researchers through programs like PLMW@PLDI. His collaborative approach is evident in his extensive co-authorship network across academia and industry. Foster leads research in the area of programming languages for networking, with particular focus on the NetKAT framework for network verification. His work bridges the gap between formal methods and practical networking systems, creating tools that have influenced both academic research and industry practice in software-defined networking. His collaborations with institutions like EPFL and industry partners like Jane Street demonstrate the real-world impact of his research agenda.

José Fragoso Santosمشاهده پروفایل

استادیار

• JavaScript
• Separation Logic
• Symbolic Execution
• +۲ مورد دیگر

José Fragoso Santos is an Assistant Professor in the Department of Computer Science and Engineering at Instituto Superior Técnico, University of Lisbon, and a member of INESC-ID where he conducts research as part of the SAT group. His research focuses on embedding formal methods into software development processes, with particular emphasis on JavaScript program analysis and verification. His educational background includes: PhD in Computer Science from University of Nice Sophia Antipolis (2014) Master's degree in Information Systems and Computer Engineering from Instituto Superior Técnico, Universidade de Lisboa (2008) Dr. Santos' research centers on JavaScript verification, symbolic execution, and secure information flow. He led the development of JaVerT, the first separation-logic-based tool for JavaScript analysis and testing, which has gained significant interest from both industry and academia. His work bridges theoretical formal methods with practical applications, particularly in web security and program analysis. He has made substantial contributions to understanding JavaScript semantics, symbolic execution techniques, and secure information flow in web applications, with publications in premier venues like PLDI, POPL, and ECOOP. His recent publications demonstrate a strong focus on symbolic execution for JavaScript and related languages, with applications in web security and program verification. The research shows progression from foundational work on information flow security to advanced techniques like compositional symbolic execution and multi-language analysis platforms. His work on JaVerT and Gillian has established significant research directions in program analysis for dynamic languages. His notable scientific achievements include: Facebook research award for the JaVerT project Dr. Santos has supervised numerous graduate students on projects related to JavaScript verification, symbolic execution, web security, and formal methods. His research has practical applications, as evidenced by the collaboration with Amazon R&D engineers to verify critical components of the AWS Encryption SDK using JaVerT. He has served on program committees for major conferences including PLDI, OOPSLA, and IJCAI, demonstrating his standing in the programming languages community. As a member of the SAT group at INESC-ID, Dr. Santos collaborates with researchers working on formal methods, program verification, and software security. His current projects include extending JavaScript symbolic execution to Web Workers, developing formal semantics for JavaScript regular expressions, and creating first-order solvers for program analysis. He continues to push the boundaries of what's possible in JavaScript program analysis and verification.

Ranjit Jhalaمشاهده پروفایل

استاد

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

Ranjit Jhala is a Professor of Computer Science Engineering in the Jacobs School of Engineering at the University of California, San Diego. His research focuses on building reliable computer systems through programming languages and software engineering techniques. His primary research interests include Programming Languages, Formal Verification, and Software Engineering. He draws from and contributes to areas such as Type Systems, Model Checking, Program Analysis, and Automated Deduction, bridging theoretical foundations with practical implementations for real-world software development. Prof. Jhala's publication record shows a consistent trajectory in refinement type systems, evolving from Liquid Haskell to Flux for Rust, while also exploring neurosymbolic approaches to error repair and type error diagnosis. His work demonstrates a commitment to making formal verification techniques accessible to practitioners. He leads the Programming Systems Group at UCSD, mentoring graduate students and collaborating with researchers across the programming languages community. His service includes General Chair roles for POPL 2018 and PLDI 2022, reflecting his leadership position in the field. Prof. Jhala is also known for his mentoring activities, including talks on academic presentation skills and participation in ICFP's mentoring programs for students and early-career researchers.

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.

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.

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.

Baishakhi Rayمشاهده پروفایل

دانشیار

• Software Engineering
• Security
• Artificial Intelligence
• +۱ مورد دیگر

Baishakhi Ray is an Associate Professor of Computer Science at Columbia University's School of Engineering and Applied Science. Her work focuses on the intersection of AI, Software Engineering, and Security. She received her Ph.D. from the University of Texas, Austin and has established herself as a leading researcher in software engineering with AI applications. Dr. Ray's educational background includes a Ph.D. from the University of Texas, Austin. Her academic journey has led to a prominent position at Columbia University where she continues to advance research in software engineering. Dr. Ray's research spans several critical areas at the intersection of software engineering and artificial intelligence. Her work explores how machine learning techniques can improve software development processes, enhance security practices, and address challenges in program analysis. She has made significant contributions to understanding how large language models can be effectively applied to code generation, vulnerability detection, and software testing. Her research has practical implications for improving software reliability and security in real-world applications, particularly in safety-critical domains like autonomous systems. Analysis of Dr. Ray's recent publications reveals a clear trajectory toward leveraging AI for practical software engineering challenges. Her work has evolved from foundational program analysis techniques to cutting-edge applications of large language models in code understanding and generation. A notable trend is her focus on making AI-assisted software development more reliable, secure, and energy-efficient. Her research increasingly addresses the practical limitations of current AI approaches while developing novel methodologies to overcome them. IEEE TCSE Rising Star Award NSF CAREER Award IBM Faculty Award VMWare Faculty Award ICSME Most Influential Paper Award (2023) FSE'17 Distinguished Paper ASE'22 Distinguished Paper ISSTA'23 Distinguished Paper CACM Research Highlights Dr. Ray actively mentors graduate students and has built a productive research group focused on AI-driven software engineering solutions. Her research has been supported by prestigious grants including the NSF CAREER award. She has successfully guided numerous students through their research projects, with several of her advisees making significant contributions to publications in top-tier conferences. Dr. Ray also serves as an Amazon Visiting Academic, bridging academia and industry to address real-world software engineering challenges. Through her leadership in various research projects and collaborations, Dr. Ray has established a dynamic research environment that combines theoretical rigor with practical applications. Her work often involves interdisciplinary collaboration across computer science subfields, particularly connecting software engineering with security and AI research communities.

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.

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

Dimitrios Karapiperis serves as an Academic Scholar at the School of Science and Technology, International Hellenic University (IHU), specializing in Entity Resolution and Privacy-Preserving Record Linkage. Previously, he held a post-doctoral position at the Hellenic Open University. He earned his PhD from the Hellenic Open University and his MSc from the University of York (UK). His doctoral thesis was featured in the IEEE Intelligent Informatics Bulletin of August 2017, highlighting its significance in the field. Dr. Karapiperis' research centers on developing advanced algorithms for entity resolution, including similarity measures, data structures, and scalable distributed solutions using randomization techniques. His work extends to privacy-preserving methods for record linkage with applications in electronic health records, cryptocurrency analysis, and social media sentiment. He has made significant contributions to efficient record linkage in data streams and spatio-temporal data through innovative blocking techniques and approximation schemes. His recent publications (2020-2022) reveal a consistent focus on scalable and privacy-aware record linkage, with increasing applications in financial technology and affective computing. Collaborations with prominent researchers like V.S. Verykios have resulted in numerous publications in top venues including IEEE Big Data and IEEE TIFS, demonstrating expertise in both theoretical foundations and practical implementations. Scientific Recognition Doctoral thesis featured in IEEE Intelligent Informatics Bulletin (2017) Research Projects University of York: Development of Java servlets for converting VisioXML into GSML within the High Integrity Systems Engineering research group University of Macedonia: Standardization of distance learning systems University of Macedonia: Establishment of a data bank for the fur sector in Kastoria University of Macedonia: System for organizing business processes of the Ministry of Macedonia and Thrace Dr. Karapiperis has collaborated with research teams across multiple institutions, contributing to diverse projects from healthcare data integration to government business process optimization, while maintaining active research in scalable entity resolution methodologies.

• Machine Learning
• Data Analytics
• Social Media Analysis
• +۵ مورد دیگر

Dr. Paraskevas Koukaras is an Academic Scholar at the International Hellenic University (IHU) and a Postdoctoral Research Associate at the Information Technologies Institute (ITI) of the Centre for Research and Technology - Hellas (CERTH), affiliated with the School of Science and Technology at IHU. His educational background includes: IT Engineer from the Department of Informatics, Alexander Technological Educational Institute of Thessaloniki (ATEI) PhD in Interdisciplinary data science methods using machine learning for enhanced knowledge acquisition from the School of Science and Technology, International Hellenic University (IHU) Dr. Koukaras' research spans social media analytics, energy systems, and machine learning. His work focuses on energy load forecasting and optimization, data analytics, information modeling, and graph mining in heterogeneous networks. He applies these techniques to address challenges in public health, financial markets, and building energy efficiency through prescriptive analytics. His recent publications (2020-2023) demonstrate a strong focus on applying machine learning to real-world problems, particularly in social media analysis for public health during the COVID-19 pandemic, energy forecasting, and fake news detection. His work consistently employs multi-model approaches leveraging both traditional and deep learning techniques across healthcare, finance, and energy domains. Dr. Koukaras has participated in major European research projects including eDREAM (H2020), DRIMPAC (H2020), PRECEPT, SmartWins, easySRI, and SMACCs, focusing on demand response technologies and energy ecosystems. He contributes to academic training through teaching courses in data science and computing despite no formal advisees being listed. He operates within interdisciplinary research teams at ITI/CERTH and IHU's School of Science and Technology, collaborating on AI applications for energy efficiency, healthcare support, and social media analytics in residential and industrial contexts.

Apostolos Ampatzoglouمشاهده پروفایل

دانشیار

• Technical Debt
• Reverse Engineering
• Software Maintainability
• +۵ مورد دیگر

Apostolos Ampatzoglou serves as Associate Professor in the Department of Applied Informatics at the University of Macedonia, where he leads research in software engineering with particular emphasis on technical debt management and software quality. Previously, he held an Assistant Professor position at the University of Groningen (2013-2016) and maintains active collaborations across European research initiatives. His academic credentials include a PhD in Software Engineering from Aristotle University of Thessaloniki (2013), MSc in Computer Systems from the University of Macedonia (2005), and BSc in Informatics from the Technological Education Institute of Thessaloniki (2003). Dr. Ampatzoglou's research program centers on technical debt quantification, reverse engineering, and software maintainability. He pioneered financial models for technical debt management and developed metrics for assessing ripple effects in software systems. His work bridges theoretical foundations with industrial applications through projects like SDK4ED and SmartCLIDE, focusing on energy-efficient development and cloud service engineering. Current investigations explore machine learning applications for vulnerability prediction and technical debt prioritization. His extensive publication record reveals strong trends in applying AI to software quality assurance, with recent work emphasizing transformer models for vulnerability detection and explainable AI for technical debt identification. He actively investigates energy-aware development practices and service-oriented architecture patterns in cloud environments. Notable recognitions include: Top-7 reviewer for Journal of Systems and Software (2022) Best paper awards at IGSCC'21, ICSR'18, and EASE'17 18th most active Consolidated Researcher in Software Engineering (2013-2020) 3rd most active Early Stage Researcher (2010-2017) Multiple personal research grants from National Scholarships Association He has successfully supervised PhD candidates including Dr. Areti Ampatzoglou (Best PhD Thesis Award, University of Groningen) and Dr. Elvira-Maria Arvanitou (VERSEN Institute award). His research is funded through major European projects such as SDK4ED, SmartCLIDE, and SKILLAB, with recent grants exceeding €2M in total funding. Current work focuses on FAIR data implementation and skills gap analysis in European labor markets. As leader of the Software Engineering Lab at the University of Macedonia, he directs a 15+ member team working on technical debt management tools, cloud development environments, and XR applications for warehouse management. The lab maintains strong industry partnerships with technology clusters in Thessaloniki and participates in the Eclipse Foundation ecosystem.

Georgios Kokosalakisمشاهده پروفایل

استادیار

• Maritime Systems
• Environmental Protection
• Shipping
• +۶ مورد دیگر

Dr. Georgios Kokosalakis serves as Assistant Professor at the School of Business and Economics, American College of Greece (ACG), and Executive Director of the Center of Excellence in Logistics, Shipping and Transportation (CoELST). He maintains dual academic roles as Senior Research Associate at University of Patras' Civil Engineering Department and Educational Counselor at MIT, while also directing industry ventures through Proteus Marine Ltd. His academic credentials include: Science Doctorate in Civil and Environmental Engineering, MIT (2006) Master of Science in Civil and Environmental Engineering, MIT (2000) Diploma in Civil Engineering (Structural Division), National Technical University of Athens (1998) Dr. Kokosalakis' research centers on Maritime Systems and Environmental Protection, with emphasis on operational efficiency, energy conservation, and emissions control in shipping logistics. His interdisciplinary approach integrates large data analytics, systems modeling, and sensor technology to develop practical solutions for sustainable maritime operations while addressing environmental pollution challenges. Recent publications (2019-2021) reveal dual research trajectories: maritime-focused work on energy efficiency impacts on container ship valuation, regulatory responses in shipping, and pandemic effects on second-hand markets; and civil engineering contributions to water distribution network optimization through probabilistic modeling of minimum night flow and real losses. This cross-disciplinary pattern demonstrates his ability to transfer methodologies between maritime and infrastructure domains. His scientific recognition includes: Schoettler Fellowship Award from MIT (2002-2003) Technical Chamber of Greece Best Thesis Award (1998) Exceptional Student Performance Awards (1995-1997) Active grant funding supports his research through projects with Athens Water Supply Company (2021), Greece's Center for Renewable Energy Sources (2020), and Hellenic Foundation for Research Innovation (2019). His industry experience as a shipowner and Proteus Marine Ltd Director provides practical grounding for academic work, though specific student supervision details aren't documented in available materials. The Center of Excellence in Logistics, Shipping and Transportation (CoELST) functions as his primary research ecosystem, facilitating collaborations between ACG, University of Patras, MIT, and maritime industry partners to advance sustainable transportation solutions through integrated engineering and business perspectives.

Maira Kotsovoulouمشاهده پروفایل

استادیار

• Software Systems
• Databases
• Technology Enhanced Learning
• +۵ مورد دیگر

Dr. Maira Kotsovoulou serves as Assistant Professor in the Department of Information Technology at Deree College and Graduate School, The American College of Greece, a position she has held since February 1, 1996. Her academic journey spans over 25 years of teaching and research in software systems and educational technology. Educational background includes: Doctorate in Technology Enhanced Learning, University of Lancaster (2011–2019) MSc in Human Computer Interaction, Heriot-Watt University (1994–1995) BSc in Computer Information Systems, The American College of Greece (1990–1994) Her research centers on the Software Systems and Databases Research Group, where she investigates visual programming applications for undergraduate education, automated assessment tools, and database optimization techniques. This work bridges theoretical computer science with practical pedagogy, focusing on how technology enhances student motivation and learning outcomes in programming courses. Her methodology combines empirical classroom studies with software development expertise gained through industry projects. Recent publications (2013–2018) reveal an evolving focus from collaborative resource tagging to sophisticated e-assessment systems, consistently addressing challenges in computer science education. The trajectory demonstrates increasing sophistication in analyzing instructor experiences and student perceptions while maintaining practical applicability in real classroom settings. Professional recognition includes: Oracle Certified Professional (OCP) in Database Administration Her industry engagement as a freelance solution architect complements academic work, with notable projects including Greece's national e-prescription system (IDIKA), COSMOTE retail software, and medical decision support systems. This dual expertise creates unique opportunities for students to engage with both academic research and enterprise-scale development challenges. As leader of the Software Systems and Databases Research Group, she fosters collaboration between academic theory and industry practice, emphasizing agile methodologies and practical implementation of educational technologies in real-world software development contexts.

John P. Makrisمشاهده پروفایل

استاد

• Seismoelectromagnetism
• Earthquake Prediction
• Magnetotellurics
• +۶ مورد دیگر

Professor John P. Makris is a distinguished academic at the Hellenic Mediterranean University where he serves in the Department of Electronics Engineering. With over 25 years of experience in geophysics and seismology, Professor Makris has established himself as a leading researcher in earthquake prediction and seismic monitoring, particularly in the seismically active Hellenic Arc region of Greece. His academic journey began with a BSc in Physics (1992) followed by a PhD in Applied Geo-Electromagnetism (1997), both from the National and Kapodistrian University of Athens (NKUA). Professor Makris has held significant leadership roles including Head of the Department of Electronics Engineering (2008-2012) and Head of the Institute of Natural Resources and Natural Hazards (2005-2015). Professor Makris's research spans several interconnected domains: Seismoelectromagnetic phenomena and earthquake prediction through VAN method Magnetotelluric studies of the Hellenic subduction zone Development of seismic monitoring networks (HC-SNC) Structural health monitoring systems for earthquake zones Integration of machine learning and IoT technologies with seismic monitoring His recent publications (2024) demonstrate a strategic evolution toward incorporating modern computational methods with traditional geophysical approaches. This work focuses on laboratory studies of rock fracturing, smart sensor networks, and analysis of recent seismic sequences in Central Crete. Professor Makris has secured significant research funding throughout his career, with '25+ research projects (funding ~4.5M€)'. His work has resulted in '60+ articles in refereed journals and conference proceedings, 7 monographs' with 815 citations according to ResearchGate metrics. As supervisor of HC-SNC (2002-2024), Professor Makris has led the development of critical seismic monitoring infrastructure in Crete. His laboratory work bridges theoretical modeling and practical instrumentation development, creating comprehensive research opportunities for students and collaborators.