Find Academic Supervisors

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.

Rachit NigamView profile

Assistant Professor

• Programming Languages
• Computer Architecture
• Hardware Acceleration
• +3 more

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

Kunle OlukotunView profile

Professor

• Computer Architecture
• Parallel Programming
• Chip Multiprocessors
• +4 more

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.

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.

• Programming Languages
• Static Analysis
• Concurrency
• +3 more

Ondřej Pavela is a researcher at the Faculty of Information Technology, Brno University of Technology, specializing in programming language tools and software verification. His work bridges theoretical computer science with practical static analysis applications. His research focuses on concurrency analysis and static program verification , with core expertise in: Deadlock and atomicity violation detection Performance analysis of concurrent systems Static analyzer plugin development Bug detection in multi-threaded programs At PLDI 2020, he presented novel plugins for the Infer static analyzer framework, demonstrating significant contributions to automated software verification. His work addresses critical challenges in concurrent program reliability through innovative tooling approaches. He actively participates in the programming languages research community through conference contributions like PLDI, focusing on practical implementations that enhance static analysis capabilities for real-world software systems.

• 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.

Nadia PolikarpovaView profile

Associate Professor

• Program Synthesis
• Program Verification
• Type Systems
• +2 more

Nadia Polikarpova is an Associate Professor in the Computer Science and Engineering Department at the University of California, San Diego. She leads the Programming Systems group and serves as a member of IFIP Working Group 2.8 on Functional Programming since 2022. Her academic journey includes a PhD from ETH Zurich (Switzerland) under Bertrand Meyer's supervision in 2014, followed by postdoctoral work at MIT CSAIL with Armando Solar-Lezama. Her research interests center around program synthesis, program verification, and type systems, with a focus on building practical tools that enhance software security and reliability. Polikarpova's work bridges theoretical foundations with real-world applications, particularly in the emerging area of AI-assisted programming. Her recent publications demonstrate a strong trajectory in program synthesis techniques, with increasing integration of machine learning approaches. The research spans from foundational type-driven synthesis methods to practical applications for validating AI-generated code and synthesizing heap-manipulating programs. Her work frequently appears in top-tier programming languages venues including PLDI, POPL, ICFP, and OOPSLA. 2020 Sloan Fellow 2020 Intel Rising Stars Award 2020 NSF CAREER Award Distinguished paper awards at PLDI'21, ICFP'20, and POPL'19 Best paper award at FM'15 Polikarpova actively mentors PhD students and has advised numerous graduates who now work at Microsoft Research, University of Michigan, and various tech companies. She teaches core programming languages courses including CSE 130 and specialized graduate courses on program synthesis (CSE 291). Her service to the community includes program committee roles for major conferences and co-chairing the Haskell conference in 2022.

Marc PouzetView profile

Professor

• Programming Languages
• Synchronous Systems
• Reactive Systems
• +3 more

Marc Pouzet is a Professor at École Normale Supérieure (ENS) in the Department of Computer Science (DIENS), where he serves as Director of CS studies. He leads the INRIA project-team PARKAS and was a Junior Member of the Institut Universitaire de France (2007–2012). His research centers on synchronous programming languages for safety-critical embedded systems, with contributions to real-time software verification, hybrid systems modeling, and probabilistic reactive programming. Research Focus Pouzet's work bridges theory and practice in: Synchronous Languages : Design/extensions of Lustre, Lucid Synchrone, and Zelus for embedded control Formal Methods : Mechanized semantics (Coq) and verified compilers (Vélus) for correctness guarantees Hybrid Systems : Integrating ODEs with discrete logic (ProbZelus for probabilistic inference) Real-time Systems : Scheduling, latency constraints, and memory-safe compilation Awards & Leadership Inria–Académie des sciences Innovation Award (2016) Program committees: EMSOFT, PLDI, POPL, ECRTS Associate Editor: EURASIP Journal on Embedded Systems Advising & Projects Supervised 19+ PhD students on topics spanning compiler verification (Bourke, Pesin), probabilistic languages (Baudart), and hybrid systems (Pauget). Leads development of open-source tools: Zelus (synchronous language with ODEs) Vélus (verified Lustre compiler) ReactiveML (reactive extension of OCaml)

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.

Koushik SenView profile

Professor

• Software Engineering
• Programming Languages
• Formal Methods
• +3 more

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.

Ilya SergeyView profile

Associate Professor

• Programming Languages
• Concurrency
• Type Theory
• +7 more

Ilya Sergey is an Associate Professor at the National University of Singapore (NUS) School of Computing, with previous faculty appointments at University College London (2015-2018). His academic career spans multiple prestigious institutions including IMDEA Software Institute (postdoctoral position) and KU Leuven (PhD). His educational background includes a PhD in Computer Science from KU Leuven (2012), an MSc in Mathematics and Computer Science from Saint Petersburg State University (2008), and professional experience as a software engineer at JetBrains prior to academia. Sergey's research focuses on the intersection of programming language theory and practical software verification, with particular emphasis on concurrent systems , smart contracts , and program synthesis . His work bridges theoretical foundations in type theory and separation logic with practical applications in blockchain technology and Rust programming. He has developed novel techniques for verifying heap-manipulating programs, analyzing commutativity in distributed transactions, and synthesizing correct-by-construction code. Analysis of his recent publications reveals a clear trajectory toward practical verification of blockchain systems and concurrent data structures, with increasing focus on Rust programming language applications. His work demonstrates consistent innovation in mechanized reasoning techniques while maintaining relevance to real-world software challenges, particularly in the domains of smart contracts and distributed systems. Sergey maintains an active research group at NUS, as evidenced by his social media references to lab traditions and student collaborations. He frequently participates in major programming languages conferences as both author and committee member, serving in leadership roles including General Chair for ICFP 2025. His research lab follows distinctive traditions, including location-based Mattermost status updates when traveling. Sergey is deeply engaged with the programming languages community through conference organization, mentoring activities, and outreach initiatives such as nature walks for conference attendees.

Maria HalkidiView profile

Associate Professor

• Data Mining
• Machine Learning
• Recommender Systems
• +6 more

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.

• Information Technology Law
• Personal Data Protection
• Privacy
• +4 more

Evgenia Alexandropoulou-Agyptiadou serves as Professor at the Department of Applied Informatics, School of Information Sciences, University of Macedonia, where she currently holds a Board of Directors position (2023-2026). She directs the Inter-Institutional Master's Program "Law and Informatics" and founded the Informatics Law Research Group, having previously served as Vice-Rector for Finance (2018-2023) and Deputy Rector for Academic Affairs (2013-2014). Her academic credentials include a PhD in Civil Law (unanimous distinction), Master's in Private Law (distinction, grade 10), and Law Degree (distinction, grade 9.1), all from Aristotle University of Thessaloniki's Department of Law. Prior professional experience encompasses Supreme Court-admitted legal practice in Thessaloniki and Head of Legal Service for Northern Greece at EGNATIA BANK S.A. Professor Alexandropoulou-Agyptiadou's research critically examines legal frameworks for emerging technologies, with particular expertise in GDPR implementation, AI ethics, and IoT privacy challenges. Her work bridges European law with digital innovation across intellectual property, cybercrime legislation, and electronic government systems, influencing national policy through active participation in standard-setting bodies. She mentors twelve graduate researchers specializing in digital law: Kitsos Panagiotis Mylosi Maria Giannoukakou Ekaterini Moschidou Efi Chrysopoulou Eleni Nikita Maria Metallidou Chryssi Poutouri Dimitra Lazou Dimitra Vergidis Konstantinos Tassis Spyros Despina Vezakidou The Informatics Law Research Group (Itlawteam), established in 2010 and integrated into the Software and Data Technology Laboratory since 2016, operates as an interdisciplinary hub for GDPR compliance training, cybercrime research, and ethical AI development. This team co-organizes international conferences, provides Data Protection Officer services, and collaborates with governmental bodies on digital policy frameworks while maintaining close ties to the "Law and Informatics" postgraduate program.

• E-Commerce Technologies
• Web Services & e-Transactions
• Mobile Commerce
• +6 more

Christos Georgiadis is a Professor in the Department of Applied Informatics at the University of Macedonia, Thessaloniki, Greece, specializing in E-Commerce Technologies, Web Services, and Security frameworks. His academic credentials include: B.Sc. in Mathematics from Aristotle University of Thessaloniki (1987) Postgraduate scholarship in Informatics at Universita' di Pisa, Italy (1989) Ph.D. in Information Systems Security (Access Control in Web Databases) from Aristotle University of Thessaloniki (2002) His research integrates E-Commerce Security, Mobile Commerce, and Context-awareness with practical applications in Web Services & e-Transactions. Current investigations focus on personalization algorithms and e-commerce application development within team-based collaborative environments, addressing critical gaps in secure transaction processing and multimedia database management. Professional recognition includes: ACM Professional Member ACM Senior Member (2014) He actively supervises research within the Software and Data Engineering Lab, directing projects on DevOps frameworks and technical debt management while mentoring graduate students in e-commerce system design.

Apostolos AmpatzoglouView profile

Associate Professor

• Technical Debt
• Reverse Engineering
• Software Maintainability
• +5 more

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.