Secure Programming Professors and Supervisors in Germany | ApplySharif

فیلترهای فعال:

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۷۲۱-۷۳۵ از ۲٬۴۸۸ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Benoit Baudryمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Benoit Baudry is a Professor in Software Technology at Université de Montréal, Canada, with previous affiliation at KTH Royal Institute of Technology in Sweden. His research focuses on automated software engineering with emphasis on practical execution-based approaches. Baudry's core research interests include: Software testing : Automated test generation, mocking, and improvement techniques Software diversity : Runtime protection through variant execution and WebAssembly transformations Randomization : Fuzzing and chaos engineering for robustness validation DevOps : Supply chain analysis and dependency management in Maven ecosystems Analysis of his 15 most recent publications (2022-2025) reveals strong emphasis on: Software supply chain security and dependency management (6 publications) Test automation and mock generation techniques (4 publications) WebAssembly compilation and security (3 publications) Software-art interdisciplinary research (2 publications) His work consistently combines empirical analysis with tool development across Java and WebAssembly ecosystems. Baudry actively contributes to the academic community through program committees (ASE, ESEC/FSE, ICSE, ICST) and keynote presentations. He leads research in software diversity through his Software Diversity Lab .

پروفایل رسمی دانشگاه

Prem Devanbuمشاهده پروفایل

استاد پژوهشی

Max Planck Institute for Security and PrivacyGermany

Prem Devanbu is a Research Professor of Computer Science at the University of California, Davis, where he has been a faculty member since transitioning from his industrial R&D position at Bell Labs in New Jersey. He holds a distinguished position in the Department of Computer Science within the College of Engineering, focusing on cutting-edge research at the intersection of software engineering and artificial intelligence. Dr. Devanbu earned his B.Tech from the Indian Institute of Technology (IIT) Madras and completed his Ph.D at Rutgers University under the supervision of Alex Borgida. His career path from industry to academia has shaped his practical yet research-oriented approach to software engineering problems. Devanbu's research primarily centers on Empirical Software Engineering , the Naturalness of Software , and Software Engineering education . His groundbreaking work on the naturalness hypothesis—that software exhibits statistical properties similar to natural language—has profoundly influenced the field. This research has expanded to explore bimodality in software (its dual nature as both machine-executable code and human-readable text), opening new avenues for analysis and tool development. His recent work heavily focuses on the application of Large Language Models to software engineering tasks, particularly in code summarization, program repair, and type inference. Analysis of Dr. Devanbu's recent publications reveals a clear trend toward leveraging Large Language Models for software engineering tasks. His research demonstrates how statistical properties of code can be exploited to improve software development processes, with particular emphasis on program understanding, documentation generation, and automated repair. The work bridges theoretical insights about code naturalness with practical applications that address real-world software maintenance challenges. Dr. Devanbu has received numerous prestigious awards recognizing his contributions to the field: ACM SIGSOFT Outstanding Research Award (2021) - "for profoundly changing the way researchers think about software by exploring connections between source code and natural language" Alexander von Humboldt Research Award (2022) IEEE Computer Society Harlan Mills Award (2024) ACM Fellow Six "test-of-time" or "10 year most influential paper" awards (MSR 2006, MSR 2009, ESEC/FSE 2008, ESEC/FSE 2009, ESEC/FSE 2011, ICSE 2012) Throughout his career, Dr. Devanbu has been actively involved in mentoring the next generation of software engineering researchers, serving on doctoral committees, and participating in New Faculty Symposia to support early-career academics. His research has been supported by significant grants that have enabled his team to explore innovative approaches at the intersection of empirical methods and software tool development. At UC Davis, he has contributed to building a strong software engineering research group that bridges theoretical insights with practical applications. Dr. Devanbu leads research efforts focused on understanding the statistical properties of software and leveraging these insights to build practical tools. His work on the naturalness and bimodality of code has established a framework that continues to influence how researchers approach program analysis and software development. His current team is at the forefront of exploring how Large Language Models can be effectively applied to software engineering tasks while accounting for the unique characteristics of code as a specialized form of human communication.

پروفایل رسمی دانشگاه

Alessandra Gorlaمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Malware detection for mobile applications
Automatic software repair
Software testing
+۴ مورد دیگر

Alessandra Gorla is an associate researcher professor at IMDEA Software Institute in Madrid, Spain, with a strong background in software engineering research. She previously worked as a postdoctoral researcher with Andreas Zeller at Saarland University in Germany and completed her PhD under Mauro Pezzè at the University of Lugano in Switzerland. Her research bridges theoretical foundations with practical applications in mobile software systems. Her research focuses on malware detection for mobile applications, automatic software repair, software testing and analysis. She has developed techniques for detecting behavior anomalies in graphical user interfaces, identifying third-party libraries in mobile apps, and leveraging intrinsic software redundancy for reliability. Her work spans both Android and iOS ecosystems, with particular attention to permission systems, release practices, and security implications. Analysis of her recent publications reveals a strong trend toward mobile application security and analysis, with increasing focus on iOS systems alongside traditional Android research. Her work combines static and dynamic analysis techniques, often incorporating natural language processing for comment analysis and test generation. There's a clear progression from foundational work on intrinsic software redundancy to more applied research on mobile security and testing. FRITZ-KUTTER AWARD! for PhD thesis on Automatic Workarounds BEST PAPER AWARD! for Search-based Security Testing of Web Applications BEST STUDENT POSTER AWARD! for Automatic Workarounds as Failure Recoveries Dr. Gorla actively mentors students and seeks motivated individuals for internship and PhD opportunities in software engineering. She has served in various organizational roles including Tool Demonstrations co-chair for FSE 2016, Artifact Evaluation co-chair for ESSoS 2016 and ISSTA 2016, and multiple program committee positions at top software engineering conferences. Her work has been supported through collaborations with major research institutions and industry partners. At IMDEA Software Institute, Dr. Gorla leads research on mobile application analysis, particularly focusing on behavioral analysis of Android and iOS applications. Her CHABADA prototype for clustering Android apps by description topics and identifying API usage outliers demonstrates her practical approach to malware detection. She also investigates intrinsic software redundancy for building more resilient systems.

پروفایل رسمی دانشگاه

Weiyang Liuمشاهده پروفایل

استادیار

Max Planck Institute for Intelligent SystemsGermany

Weiyang Liu is a machine learning researcher and incoming Assistant Professor in the Department of Computer Science and Engineering at The Chinese University of Hong Kong (CUHK), where he will lead the Scalable Principles for Learning and Reasoning Lab (SphereLab). He has previously held postdoctoral and research roles at the Max Planck Institute for Intelligent Systems, Georgia Tech, Google Brain, Nvidia Research, and MERL. His research focuses on principled modeling of inductive bias in learning algorithms, emphasizing geometric invariance, symmetry, and formal reasoning in large language models. His work spans generative modeling (diffusion models, 3D mesh synthesis), foundation models (parameter-efficient training), and symbolic/mathematical reasoning evaluation. Publications include top-tier conferences like NeurIPS, ICML, CVPR, and ICLR, with Spotlight/Notable Top-25% designations. He mentors PhD students including Zeju Qiu, Longhui Yu, and Zhouliang Yu, with alumni transitioning to institutions like Technical University of Munich, University of Tübingen, and Caltech. His lab emphasizes curiosity-driven research , theoretical rigor, and open collaboration.

پروفایل رسمی دانشگاه

Thomas Demmelhuberمشاهده پروفایل

استاد

University of Erlangen–NurembergGermany

Thomas Demmelhuber is Professor of Middle Eastern Politics and Society at Friedrich-Alexander University Erlangen-Nuremberg (FAU), holding the Chair of Middle Eastern Politics and Society at the Institute of Political Science since October 2015. He also serves as Visiting Professor at the College of Europe (Natolin) since 2015 and has held previous academic positions including Junior Professor of Political Science at the University of Hildesheim (2012-2015). Demmelhuber's research focuses on authoritarian dynamics in the Middle East, particularly examining how authoritarian regimes influence and attract neighboring states. His work spans Middle Eastern politics, Gulf monarchies, European Neighbourhood Policy, and comparative authoritarianism. He has developed the influential concept of 'Authoritarian Gravity Centers' to explain how certain regimes act as forces of attraction and contagion for countries in geopolitical proximity, examining this phenomenon across multiple regions including the Middle East, Latin America, Eastern Europe, Central Asia, and Asia. His publications reveal a consistent focus on authoritarian diffusion, Gulf politics, and the interplay between domestic political structures and international relations. Recent work increasingly examines China-Gulf relations and the strategic partnerships forming between authoritarian states. His research demonstrates how authoritarian regimes adapt and innovate through decentralization, historical narratives, and regional organizations to maintain power while influencing neighboring states. Fellow of the Bavarian Science Alliance for Peace, Conflict, and Security Research (FOKS) since 2024 Member of the academic advisory board of the Orient Institute in Beirut since 2020 Member of the research advisory board of the German Institute for International and Security Affairs (SWP) in Berlin since 2021 Board member of the German Association for the Middle East (DAVO, 2018-2025) At FAU, Demmelhuber has held numerous leadership positions including Managing Director of the Institute of Political Science (2017-2021), Chair of the Doctoral Committee of the Faculty of Philosophy (2018-2024), and currently serves as Member of the Senate and University Council since 2023. He manages the MA Middle Eastern Studies program since 2017 and the MA Political Science program since 2018, demonstrating significant commitment to academic administration and student mentoring.

پروفایل رسمی دانشگاه

Jan Seedorfمشاهده پروفایل

استاد

Stuttgart University of Applied SciencesGermany

Jan Seedorf serves as a Professor at Stuttgart University of Applied Sciences, where he is integral to the Computer Science discipline through teaching and academic leadership. His responsibilities span three bachelor's programs: Computer Science, Business Information Systems, and Augmented Reality / Virtual Reality Engineering, reflecting a commitment to multidisciplinary technical education. His research and teaching focus centers on critical infrastructure domains: IT Security encompasses cryptographic systems, threat mitigation, and secure protocol design, while Computer Networks addresses modern architectures, wireless transmission, and network optimization. These areas directly respond to evolving digital security challenges and communication demands in enterprise environments. Professor Seedorf maintains dedicated student engagement through Wednesday office hours (10:00-11:00 AM) and appointment-based consultations, supporting academic development across all enrolled bachelor's cohorts. His structured availability underscores an advisor role focused on practical application of theoretical concepts in rapidly advancing technological fields.

پروفایل رسمی دانشگاه

Jiachi Chenمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Jiachi Chen is an Associate Professor at the School of Software Engineering, Sun Yat-sen University, China. He received his Ph.D. from Monash University, Australia, and has established himself as a leading researcher in blockchain security and Web3 technologies. His educational background includes: Ph.D. in Information Technology from Monash University (2019-2022) Research Assistant at Hong Kong Polytechnic University (2016-2018) Dr. Chen's research spans software security, program analysis, smart contracts, and Web3 technologies. His work bridges traditional software engineering with blockchain, focusing on security vulnerabilities, large language models for code generation, and empirical studies of smart contract development. Recent publications show increasing integration of AI techniques to address blockchain security challenges. His publication trends reveal deep expertise in smart contract security, with numerous papers on vulnerability detection and code analysis. Recent work has expanded into LLM applications for software engineering, particularly examining code generation quality and security implications in Web3 contexts. Dr. Chen has received significant recognition: Multiple ACM SIGSOFT Distinguished Paper Awards (ICSE 2025, ISSTA 2024, Internetware 2024) Best Paper Award at IEEE CSCloud/EdgeCom 2023 Best Paper Award at IEEE INFOCOM 2018 Best Paper Award at ISPEC 2017 He serves on program committees for top software engineering conferences (ICSE, FSE, ASE, ISSTA) and is actively recruiting students in Web3/Blockchain/Smart Contract research areas. His work appears consistently in premier venues including IEEE Transactions on Software Engineering and ACM conferences, demonstrating sustained research impact.

پروفایل رسمی دانشگاه

Ajay Jhaمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Ajay Jha is an Assistant Professor in the Department of Computer Science at North Dakota State University (NDSU), where he leads the Software Testing and Maintenance (STAM) Lab. His academic journey began with industry experience, followed by graduate studies and postdoctoral research that shaped his current focus on software engineering research. His educational background includes: Ph.D. in Computer Science from Kyungpook National University (2017) Master's degree from Kyungpook National University (2013) Over five years of industry experience before graduate studies, including co-founding two startups Postdoctoral research at University of Alberta (over two years) and Kyungpook National University (three years) Dr. Jha's research focuses on software engineering, particularly in the areas of software testing, maintenance, and evolution. His work centers on mining large-scale software repositories to uncover real-world issues in software quality, reliability, and maintainability. He develops innovative tools and techniques to address challenges in regression testing, library migration, and mobile application development. His research has significant practical implications for improving software development processes and enhancing the reliability of modern software systems, particularly in mobile and Python environments. His publication record shows a clear progression from Android-focused research to broader software engineering challenges, with recent work emphasizing Python library migration and large language models for software engineering tasks. His research methodology typically involves empirical studies of real-world software repositories combined with tool development to address identified challenges. Dr. Jha is actively involved in academic service, serving on program committees for major software engineering conferences including MSR, ICSME, SANER, ASE, and ICSE. He also reviews for prestigious journals such as IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology. At NDSU, he teaches a range of courses from undergraduate to graduate level, including Mobile Software Engineering, Software Development Processes, and Software Project Planning and Estimation. He also leads graduate seminars on specialized topics like 'LLMs for Software Testing and Maintenance' and 'Code Smell and Refactoring.' He leads the Software Testing and Maintenance (STAM) Lab at NDSU, which focuses on mining software repositories to identify quality issues and developing practical tools to address software maintenance challenges. The lab's research has produced several benchmarks (PyMigBench, JTestMigBench) and tools (TRec) that have been shared with the research community.

پروفایل رسمی دانشگاه

Xiang Chenمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Xiang Chen is an Associate Professor at the Department of Software Engineering, School of Artificial Intelligence and Computer Science, Nantong University, China. He received his B.Sc. degree from Xi'an Jiaotong University in 2002 and his M.Sc. and Ph.D. degrees in computer software and theory from Nanjing University in 2008 and 2011 respectively. He is an editorial board member of Information and Software Technology and serves as a program committee member for prestigious conferences including FSE 2026 and ASE 2025. Chen is also a senior member of the China Computer Federation (CCF) and active in various academic committees. Chen's research focuses on empirical software engineering, mining software repositories, and software testing and maintenance, with particular emphasis on applying AI techniques to software engineering problems. His work spans large language models for software engineering, security vulnerability analysis, code change representation, and regression testing. He has published over 110 papers in top-tier journals and conferences including IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology. His recent publications demonstrate a strong trend toward integrating AI techniques, particularly large language models, with traditional software engineering practices. The research spans code generation evaluation, deep learning framework testing, vulnerability detection, and automated program repair, showing a consistent focus on improving software quality through innovative testing and analysis techniques. ACM SIGSOFT Distinguished Paper Award (ICSE 2021) ACM SIGSOFT Distinguished Paper Award (ICPC 2023) Top 1% CNKI Highly Cited Scholar (2024) Top 2% Scientist by Stanford University (2023-2025) NASAC 2019 Prototype Competition First Prize Chen has successfully advised numerous graduate and undergraduate students who have gone on to prestigious institutions including Nanjing University, Tsinghua University, and Zhejiang University. Many of his students have won national programming competitions and received scholarships. His research group, smartSE, actively works on projects funded by the Natural Science Foundation of China and various provincial research programs. Chen also serves as a reviewer for top journals including IEEE Transactions on Software Engineering and ACM Transactions on Software Engineering and Methodology.

پروفایل رسمی دانشگاه

Fang Liuمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Software Engineering
Artificial Intelligence for Software Engineering
Program Understanding
+۳ مورد دیگر

Fang Liu is an Assistant Professor at the School of Computer Science & Engineering, Beihang University, China. She has made significant contributions to the field of software engineering, particularly in the intersection of artificial intelligence and software development practices. Dr. Liu received her Ph.D. in Computer Science from Peking University (Sep. 2017 - Jul. 2022), supervised by Prof. Zhi Jin and Prof. Ge Li. Prior to that, she earned her B.S. in Computer Science from Chongqing University (Sep. 2013 - Jul. 2017). Her research interests focus on AI for Software Engineering, including program understanding and generation, program repair, and applications of Large Language Models to software development tasks. Dr. Liu teaches Compiler Technology as a compulsory course at Beihang University (Fall 2024) and Programming in Cangjie Language as an elective course (Spring 2025). Her recent publications demonstrate a clear trend toward leveraging large language models for various software engineering tasks, with a particular emphasis on code editing, program repair, and code translation. Her research spans both theoretical advancements in model architectures and practical applications to real-world software development challenges, with numerous publications in top-tier venues like ASE, ICSE, and FSE. Distinguished Paper Award at ICPC'20 for "A Self-Attentional Neural Architecture for Code Completion with Multi-Task Learning" Dr. Liu actively participates in the software engineering research community as a program committee member for major conferences including ASE, FSE, and ICSE. Her work has significant implications for improving developer productivity, software quality, and the integration of AI technologies into the software development lifecycle.

پروفایل رسمی دانشگاه

Michael Pradelمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Michael Pradel is a full professor at the University of Stuttgart and a faculty member at the CISPA Helmholtz Center for Information Security. He leads the Software Lab at the University of Stuttgart and holds additional affiliations with the International Max Planck Research School (IMPRS) for Intelligent Systems and the Stuttgart ELLIS Unit. Previously, he served as an assistant professor at TU Darmstadt, a postdoctoral researcher at UC Berkeley, and a lecturer and postdoctoral researcher at ETH Zurich, where he completed his PhD. His educational background includes computer science studies at TU Dresden and engineering studies at Ecole Centrale Paris, with a master's thesis conducted at EPFL. He has taken sabbaticals at Facebook, UC Berkeley, and UCLA. Pradel's research spans software engineering, programming languages, security, and machine learning, with a focus on tools and techniques for building reliable, efficient, and secure software. He is particularly interested in neural-symbolic software analysis, analyzing web applications, dynamic analysis, and test generation. His recent work increasingly incorporates large language models for software engineering tasks including bug detection, test generation, and program repair. His research group has produced significant work in WebAssembly analysis, Python dynamic analysis, quantum program analysis, and automated program repair, with notable tools including Wasm-R3, DynaPyt, LintQ, and RepairAgent. Ernst-Denert Software Engineering Award Emmy Noether grant by the German Research Foundation (DFG) (1.3 million Euro) ERC Starting Grant (1.5 million Euro) Best/Distinguished Paper Awards at FSE (3x), ISSTA, ASE, ASPLOS, and MSR ACM Distinguished Member Multiple ACM SIGSOFT Distinguished Paper and Artifact Awards Pradel has advised numerous PhD students including Matteo (thesis on "Testing and Analysis of Quantum Software"), Luca (thesis on "Supporting Software Evolution via Search and Prediction"), and Daniel (thesis on program analysis for WebAssembly). His research has been supported by significant grants including the Emmy Noether grant and ERC Starting Grant. He serves in leadership roles for major conferences including PC co-chair for FSE 2027 and area chair for ICSE 2026. Pradel leads the Software Lab at the University of Stuttgart, which includes visiting professors Cristian Cadar and Prem Devanbu (both supported by Humboldt Research Awards). The lab maintains active collaborations with institutions including CMU, Google, KAIST, and USI Lugano, and regularly contributes to major software engineering conferences.

پروفایل رسمی دانشگاه

Jongmoon Baikمشاهده پروفایل

استاد

Max Planck Institute for Security and PrivacyGermany

Jongmoon Baik serves as a Professor at the Korea Advanced Institute of Science and Technology (KAIST), School of Computing, South Korea, and maintains active membership in IEEE and ACM professional organizations. His academic foundation includes a PhD in Computer Science from the University of Southern California, establishing expertise in rigorous software engineering methodologies. Professor Baik's research program centers on software process modeling, software economics, software reliability engineering, and software Six Sigma, with emphasis on quantifying development efficiency and product quality through statistical process control. His work bridges theoretical modeling with industrial application in software lifecycle optimization. Current research trajectories demonstrate growing integration of security analysis into process modeling, exemplified by his upcoming ASE 2025 publication on vulnerability detection using modifiability signals at the line-level code analysis. Professional recognition includes sustained engagement with premier software engineering venues through conference participation and publications. He advises graduate researchers within KAIST's School of Computing and leads the Software Process Research Laboratory (SPIRAL), identifiable through his institutional web presence at spiral.kaist.ac.kr, focusing on empirical studies of software development economics and reliability metrics.

پروفایل رسمی دانشگاه

Petra Bendelمشاهده پروفایل

استاد

Alice Salomon University of Applied Sciences BerlinGermany

Petra Bendel is Professor of Political Science at Friedrich-Alexander-Universität Erlangen-Nuremberg (FAU), where she serves as Academic Director of the Central Institute for Regional Research and Deputy Director of FAU's Center for Human Rights Erlangen-Nuremberg (CHREH). She holds influential policy positions including Chair of the Expert Council of German Foundations on Integration and Migration (SVR), Chair of the Scientific Advisory Board of the Federal Office for Migration and Refugees (BAMF), and Member of the German Federal Government's expert commission on "Framework Conditions and Capacity for Integration." Her research focuses on EU asylum and refugee policy, German refugee policy at national and local levels, integration policy, and human rights of refugees and migrants. Bendel examines migration governance through multiple political levels, analyzing tensions between EU policy frameworks and their human rights implications. Her work often addresses the practical implementation challenges of migration policies in diverse political contexts. Analysis of Bendel's publication record reveals consistent scholarly contribution since the 1990s, with recent work increasingly focused on pandemic impacts on migration systems, municipal-level integration approaches, and sustainable solutions for displacement. Her research bridges academic analysis with practical policy recommendations, particularly regarding EU burden-sharing mechanisms and local implementation of integration policies. Bendel leads multiple research projects examining displacement, migration, and integration across political levels. Her institutional leadership positions demonstrate significant influence in shaping German and European migration policy discourse. The empirical focus on 92 municipalities across 12 German states in her 2020 work "Zwei Welten? Integrationspolitik in Stadt und Land" exemplifies her commitment to evidence-based policy analysis.

پروفایل رسمی دانشگاه

Soha Husseinمشاهده پروفایل

استادیار

Max Planck Institute for Security and PrivacyGermany

Soha Hussein is an Assistant Professor at Ain Shams University in Egypt. She is actively involved in the software engineering research community, serving in various roles including Publication Co-chair for ASE 2025 and Posters/Tools/SRC Co-Chair for SPLASH/ISSTA 2026. Dr. Hussein received her Ph.D. and M.S. in Computer Science from the University of Minnesota. She also completed the Early Career Teaching and Learning program and the Prepare Future Faculty program at the University of Minnesota, demonstrating her commitment to both research and education. Her research focuses on enhancing software reliability and security through advanced program analysis techniques. Specifically, she specializes in symbolic execution, fuzzing, formal verification, and software testing. Her work addresses the critical challenge of path explosion in symbolic execution through innovative path-merging approaches. Dr. Hussein's research has practical applications in verifying Java programs and improving automated program verification techniques, with recent work extending to AWS Lambda applications. Her publications demonstrate a consistent trajectory of advancing verification techniques while maintaining strong theoretical foundations. Dr. Hussein has received multiple prestigious awards for her work on Java Ranger, including Gold Medals at SV-COMP 2020, 2021, and 2025, as well as a Bronze Medal at SV-COMP 2020. These awards recognize the effectiveness of her path-merging approach in reducing path explosion and improving verification efficiency. She is actively involved in mentoring students, particularly through the Google Summer of Code program where she serves as an organization admin and mentor for the Java Pathfinder (JPF) Organization. Dr. Hussein encourages excellent students to reach out for research opportunities in her lab, having successfully mentored students like Kunha Kim who accepted a Master scholarship at University of Colorado Boulder. Dr. Hussein leads research related to Java Ranger, an extension to Symbolic Pathfinder that implements path-merging techniques for Java verification. Her team continues to advance this work, with recent developments supporting string and array operations and applying the technology to AWS Lambda applications. She maintains active contributions to the SymbolicPathFinder/jpf-symbc repository on GitHub, demonstrating her commitment to open-source verification tools.

پروفایل رسمی دانشگاه

Diego Garbervetskyمشاهده پروفایل

دانشیار

Max Planck Institute for Security and PrivacyGermany

Diego Garbervetsky is an Associate Professor at the Computer Science Department, School of Sciences, University of Buenos Aires, and a Researcher at ICC/CONICET. He also serves as Director of the Institute of Research in Computer Sciences (ICC). His academic career spans multiple roles in software engineering research and education. His educational background is not explicitly stated in the provided texts, but his current position reflects extensive academic achievement. Garbervetsky's research focuses on static analysis techniques for Java-like programs and Smart Contracts, automated program verification , program understanding , and validation . His specific interests include program understanding, testing and verification of programs featuring rich protocols, static analysis for program verification, and automatic symbolic resource analysis (gas consumption, dynamic memory, energy, etc.). His research has significant implications for blockchain technology, particularly in smart contract verification. Analysis of his recent publications reveals a strong trend toward smart contract security and verification , with multiple papers on modal abstractions, predicate abstractions, and tools like VeriSol for Solidity smart contracts. His work bridges formal methods with practical software engineering challenges, particularly in the blockchain domain. His scientific contributions include the development of multiple research tools: Contractor: Automated tool for behavior validation Contractor.NET: Visual Studio extension for .NET validation JConsume2: Compositional analysis for Java heap memory Consume.Net: Compositional analysis for .NET heap memory BudaPest: Automated software verifier VInTime: Verification suite for Real Time systems Garbervetsky has supervised numerous PhD students including Daniel Wappner, Javier Godoy, and Alexis Soifer, with former students now working at companies like Microsoft, Veritran, and Dialpad. He has served on program committees for major conferences including ICSE, FSE, ASE, and ISSTA, demonstrating his standing in the software engineering research community. His service includes chairing workshops and serving on artifact evaluation committees, showing his commitment to research quality and reproducibility. He currently teaches Software Engineering 2 at the University of Buenos Aires, having previously taught courses in algorithms, automatic software validation, program analysis, programming paradigms, and computer organization.

پروفایل رسمی دانشگاه