Find Academic Supervisors

Fredrik KjolstadView profile

Assistant Professor

• Compilers
• Programming Models
• Performance Engineering
• +3 more

Fredrik Kjolstad is an Assistant Professor in the Department of Computer Science at Stanford University, specializing in compilers and programming models for sparse computing and performance engineering. His research focuses on separating algorithms from data representations to enable portable applications across diverse hardware platforms. His research interests span compilers, programming models, performance engineering, and computer architecture, with particular emphasis on sparse tensor algebra, compiler design for heterogeneous systems, and high-performance computing. He has pioneered frameworks like TACO, Simit, and Distal that enable efficient sparse computations across CPUs, GPUs, and specialized accelerators. Dr. Kjolstad's publications demonstrate expertise in compiler optimization techniques for sparse data structures, tensor algebra, and distributed systems. His work consistently addresses the challenge of bridging high-level programming abstractions with efficient hardware execution across diverse architectures. MIT EECS First Place George M. Sprowls PhD Thesis Award NSF CAREER Award Rosing Award Adobe Fellowship Google Research Scholarship Best Paper Awards at EuroMPI 2013, OOPSLA 2017, and OOPSLA 2021 ISCA Distinguished Artifact Award PLDI and OOPSLA Distinguished Paper Awards He advises multiple PhD students including James Dong, Olivia Hsu, and Rohan Yadav, while leading research on compiler technologies that have received significant grant support. His group develops practical tools like the TACO compiler and Legate Sparse that are used in both academic and industrial settings. Current projects focus on programmable accelerators for sparse tensor algebra, distributed sparse computing, and compiler support for emerging hardware architectures.

Anil MadhavapeddyView profile

Professor

• Planetary Computing
• Computer Systems
• Programming Languages
• +7 more

Anil Madhavapeddy is the Professor of Planetary Computing at the University of Cambridge Computer Laboratory, where he co-leads the Energy & Environment Group and is a member of the Systems Research Group. He is also a Fellow at Pembroke College where he serves as Director of Studies in Computer Science. Madhavapeddy completed his PhD from the University of Cambridge in 2003 and his BEng in Information Systems Engineering from Imperial College in 1999. He holds a JM Keynes Fellowship since 2022 for his work combining computer science with economics, and serves on the management committee of the Cambridge Conservation Initiative where he co-directs 4C (Cambridge Centre for Carbon Credits) and the Centre for Earth Observation. His research spans computer systems and programming languages with a strong focus on applying these technologies to global conservation, biodiversity, and climate change challenges. He leads the OCaml Labs group and has made significant contributions to open-source projects including OCaml, Docker, Xen, and OpenBSD. His work often bridges computer science with environmental science, developing computational approaches to address planetary-scale challenges. Madhavapeddy's recent publications demonstrate a clear trajectory toward integrating programming language research with environmental monitoring and conservation. His work spans from foundational programming language techniques to applied geospatial computing systems, with increasing emphasis on biodiversity measurement, carbon credit systems, and planetary-scale environmental monitoring. JM Keynes Fellowship (2022-present) As an educator, Madhavapeddy teaches undergraduate courses including Foundations of Computer Science, Software & Security Engineering, and Cloud Computing. He mentors MPhil and PhD students and co-founded the award-winning book 'Real World OCaml' (2nd Edition, 2022). He has co-founded several companies including Unikernel Systems, High Energy Magic, Segfault, and Tarides to translate research into real-world impact. Madhavapeddy leads the OCaml Labs group at Cambridge and works closely with the Energy & Environment Group, collaborating with colleagues from Plant Sciences, Zoology, Economics, and NGOs including UNEP-WCMC and the IUCN. His current efforts are primarily focused on conservation technology through partnerships with organizations like Canopy PACT.

Stefano MarkidisView profile

Professor

• High-Performance Computing
• Heterogeneous Systems
• Quantum Computing
• +3 more

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

Mayur NaikView profile

Professor

• Programming Languages
• Artificial Intelligence
• Neurosymbolic Programming
• +5 more

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.

Bryan ParnoView profile

Professor

• Secure Systems
• Formal Software Verification
• Applied Cryptography
• +7 more

Bryan Parno is the Kavčić-Moura Professor of Electrical & Computer Engineering and Computer Science at Carnegie Mellon University, where he leads the Secure Foundations Lab within CyLab, CMU's Security & Privacy Institute. His research combines theory and practice to provide formal, rigorous security guarantees about concrete systems, with emphasis on creating solid foundations for practical solutions. His research spans secure systems , formal software verification , applied cryptography , data privacy , and usable security . Current work focuses on protocols for verifiable computation and zero-knowledge proofs, building practical formally verified secure systems, and developing next-generation application models. His lab maintains a strong commitment to reproducibility, open-sourcing code under permissive licenses, and avoiding patenting results to maximize public benefit. His recent publications demonstrate a clear trend toward practical verification of real-world systems, particularly through the Verus project for verifying Rust code, Everest for building verified HTTPS stacks, and Ironclad for provably secure systems. These works bridge the gap between theoretical security guarantees and practical implementation, with applications ranging from blockchain protocols to verified cryptographic libraries deployed in the Linux kernel. His scientific achievements include multiple Distinguished Paper/Artifact Awards (USENIX Security, SOSP, PLDI), the IEEE Cybersecurity Award for Practice , the Sloan Fellowship , and the ACM Doctoral Dissertation Award . His work on verifiable computation protocols has influenced blockchain systems, while his research on secure code execution environments contributed to Intel's SGX and TDX technologies. As an advisor, Parno has mentored numerous PhD students including Aymeric Fromherz (recipient of the ACM SIGSAC Doctoral Dissertation Award) and Jay Bosamiya. His lab receives funding from diverse sources including NSF, industry partners, and security foundations. Notably, his work has been incorporated into Windows 8+, iOS 13+, and the Linux kernel. He also serves in leadership roles including Chair of IEEE Computer Society's Technical Committee on Security & Privacy. The Secure Foundations Lab maintains strong industry connections, with alumni joining Microsoft Research, Inria, Northeastern University, and other leading institutions. Recent projects like Verus, Everest, and Ironclad represent the lab's commitment to building end-to-end verified systems that provide rigorous security guarantees while maintaining practical performance.

Fernando Magno Quintão PereiraView profile

Associate Professor

• Compilers
• Code Generation
• Compiler Optimizations
• +3 more

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

• Programming Languages
• Formal Verification
• Compilers
• +8 more

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

Baishakhi RayView profile

Associate Professor

• Software Engineering
• Security
• Artificial Intelligence
• +1 more

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.

• Machine Learning
• Data Analytics
• Social Media Analysis
• +5 more

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.

Angelo SifalerasView profile

Professor

• Mathematical Programming
• Network Optimization
• Heuristic Methods
• +2 more

Angelo Sifaleras is a Full Professor at the Department of Applied Informatics, School of Information Sciences, University of Macedonia (Thessaloniki, Greece). He also serves as an Adjunct Professor of Quantitative Methods at the Hellenic Open University. His academic credentials include a Ph.D. in Applied Informatics (University of Macedonia, 2007) and a B.Sc. in Mathematics (Aristotle University of Thessaloniki, 1999). Research Focus: Professor Sifaleras specializes in Mathematical Programming , Network Optimization , and Heuristic Methods . His work integrates computational optimization with real-world logistics, supply chains, and sustainable systems. Key research themes include metaheuristic algorithms for vehicle routing, pollution-aware logistics, and parallel computing solutions for network analysis. Publication Trends: His 15 most recent articles emphasize hybrid metaheuristics (e.g., combining reinforcement learning with Variable Neighborhood Search), sustainable supply chain modeling, and high-performance computing applications. Dominant domains include operations research, environmental optimization, and educational algorithm visualization. Teaching & Service: He instructs courses in Combinatorial Optimization, Linear Algebra, and Heuristic Methods, employing tools like CPLEX, Gurobi, and SageMath. As an editor for Operations Research Forum and the Yugoslav Journal of Operations Research , he supports academic discourse in optimization. A Senior ACM member, he contributes to conferences like ICVNS and ITS.

Mamatas EleftheriosView profile

Associate Professor

• Wireless and Mobile Networks
• Quality of Service
• Network Management
• +4 more

Mamatas Eleftherios serves as an Associate Professor in the Department of Applied Informatics at the University of Macedonia, specializing in next-generation wireless networking research and education. His academic credentials include a Diploma in Electrical and Computer Engineering (2003) and PhD in Computer Networks (2008), both from Democritus University of Thrace, Greece. Research focuses on critical networking challenges: Wireless/Mobile Networks infrastructure Quality of Service optimization Software-Defined Networking (SDN) architectures Energy-efficient communication protocols Stochastic modeling for network performance His publication portfolio comprises 8 books, 37 journal articles, and 59 conference papers reflecting deep technical engagement. Teaching responsibilities include BUSINESS DATA COMMUNICATIONS (ISC501), COMPUTER SYSTEMS (AIC105), and advanced topics in network performance analysis. No scientific awards or grant information appears in the provided documentation.

Georgios KokosalakisView profile

Assistant Professor

• Maritime Systems
• Environmental Protection
• Shipping
• +6 more

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.

Nikolaos BakasView profile

Assistant Professor

• Machine Learning
• Numerical Methods
• High-Performance Computing
• +4 more

Dr. Nikolaos Bakas serves as an Assistant Professor in the Information Technology Department at the School of Liberal Arts and Sciences, The American College of Greece, Deree. His academic profile centers on bridging theoretical mathematics with practical machine learning implementations through rigorous algorithmic development. His research program focuses on fundamental mathematical modeling of machine learning systems , with specialized expertise in Numerical Methods and High-Performance Computing (HPC) . Key contributions include stochastic optimization algorithms (notably the ITSO framework), gradient-free neural network training techniques, and computational mechanics applications. This interdisciplinary work connects theoretical mathematics with engineering solutions in structural analysis and environmental risk assessment. Analysis of his 2019-2023 publications reveals a clear trajectory toward practical HPC implementations of machine learning frameworks, with increasing emphasis on domain-specific applications. His research consistently addresses computational efficiency challenges while maintaining mathematical rigor, particularly in stochastic search methods and partition-based approximation systems. As Principal Investigator for multiple industry and academic projects, Dr. Bakas demonstrates active research leadership with direct organizational consulting experience. His project portfolio indicates strong translation of theoretical research into real-world AI and HPC adoption, though specific grant details remain undisclosed.

Konstantinos VavousisView profile

Associate Professor

• Cybersecurity
• Artificial Intelligence in Cybersecurity
• Machine Learning
• +6 more

Dr. Konstantinos Vavousis serves as Associate Professor and Department Chair of the Department of Information Technology, Cybersecurity, and Computer Science at The American College of Greece's School of Liberal Arts and Sciences. He maintains dual research associate appointments at the University of Piraeus (Department of Business Administration) and European University of Cyprus (Department of Computer Science and Engineering). His research program centers on Artificial Intelligence applications in cybersecurity, machine learning for threat detection, and GDPR compliance frameworks. Current investigations include wireless network security for smart cities (LoRaWAN), social engineering countermeasures, and secure infrastructure development for national institutions like the National Library of Greece. This work directly informs his leadership of the MSc in Cybersecurity program and Cyber Club activities. Dr. Vavousis actively secures research funding through major projects: OCEANIDS (climate data harmonization), GRACE (law enforcement tools against child exploitation), and THEIA (EU crisis management systems). As Cyber Club advisor, he mentors students in Capture The Flag competitions while coordinating thesis projects that address real-world security challenges for Greek government entities and critical infrastructure. His professional impact extends through EthiHak - the pioneering ethical hacking contest he initiated (2016-2019) - and certifications as Ethical Hacker and ISO 27001 Lead Auditor. With 17+ years of industry experience spanning pharmaceuticals, energy, finance, and government sectors, he integrates practical case studies into courses like Ethical Hacking & Penetration Testing and Intrusion Detection.