جستجوی استاد راهنمای دانشگاهی

• Computer Architecture
• Non-Volatile Memory Systems
• Deep Learning Systems
• +۳ مورد دیگر

Jishen Zhao is an Assistant Professor in the Department of Computer Science and Engineering at the University of California, San Diego (Jacobs School of Engineering). His research focuses on computer architecture, non-volatile memory systems, and deep learning acceleration. Dr. Zhao has published extensively in top venues including ISCA, MICRO, ASPLOS, and IEEE Transactions. He collaborates with researchers at UCSD and beyond to advance systems for emerging applications in AI and autonomous vehicles. Dr. Zhao's primary research areas include persistent memory systems, hardware/software co-design for deep learning, and safety-critical computing. He develops techniques for crash consistency, memory disaggregation, and efficient neural network deployment. His work on autonomous vehicles addresses scenario generation and perception-aware system design. Recent projects explore LLM applications for software engineering and hardware verification. Analysis of Dr. Zhao's 2024-2025 publications reveals a strong shift toward AI-integrated systems research. He applies large language models to tasks like RTL verification and software issue localization while continuing to innovate in memory systems for serverless computing. There is growing emphasis on safety-critical systems for autonomous vehicles and energy-efficient neural network training using novel hardware architectures. Information about Dr. Zhao's scientific awards, advising activities, grants, and laboratory facilities was not available in the provided documentation.

• Web Security
• Software Security
• Secure Programming
• +۳ مورد دیگر

Prof. Dr. Martin Johns serves as Chair of Application Security at the Institute for Application Security within the Carl Friedrich Gauss Faculty at Technical University Braunschweig. He joined TU Braunschweig after working as Research Expert at SAP Security Research, where he shaped security strategy and led software security teams. Prior to SAP, he worked as software engineer in Germany at companies like TC Trustcenter and Infoseek Germany. Academic qualifications include a PhD in Computer Science (University of Passau, 2009) and a Diploma in Computer Science (University of Hamburg, 2003). His research focuses on web security and software security , particularly secure programming , vulnerability detection , and attack mitigation strategies. Recent publications cover topics like GDPR compliance frameworks , WebAssembly security , federated learning privacy , and server-side request forgery (SSRF) defenses. His work appears in top conferences including IEEE S&P, CCS, WWW, and ACM CODASPY.

Janick Edingerمشاهده پروفایل

استاد

• Distributed Operating Systems
• Edge Computing
• Computation Offloading
• +۷ مورد دیگر

Prof. Dr. Janick Edinger is a Professor of Distributed Operating Systems at the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences, University of Hamburg, Germany. He leads a research group focused on distributed, context-aware, and adaptive computing systems, with a strong emphasis on edge computing, computation offloading, and assistive technologies. Education: PhD in Computer Science, University of Mannheim Studies at National Taiwan University Studies at University of Alberta, Canada Research stays at University of British Columbia, Hong Kong Polytechnic University, and Georgia State University, USA His research explores how edge computing and computation offloading can enable efficient, privacy-preserving processing of sensor and video data close to their sources, particularly in dynamic environments. He investigates the integration of autonomous and heterogeneous systems—such as drone fleets and mobile devices—into scalable middleware platforms for real-time monitoring and decision-making in logistics and industrial operations. His work also emphasizes societal impact, contributing to accessible routing, adaptive interfaces, and crowd-sourced mapping. The recent publications reflect a strong trend in edge computing, federated learning, privacy-preserving analytics, and assistive technologies. Topics include WebAssembly-based offloading, emotion prediction via eye tracking, real-time traffic detection, and predictive maintenance in Industry 4.0, showcasing a blend of foundational systems research and applied human-centered computing. Scientific Awards: PerCom 2021 Mark Weiser Best Paper Award Best Paper Award at IEEE PerCom 2021 for 'Voltaire: Precise Energy-Aware Code Offloading Decisions with Machine Learning' Prof. Edinger actively advises students and leads research projects involving grants and collaborations. His team includes PhD candidates and researchers working on middleware, edge systems, and context-aware applications. He has served on conference program committees, such as shadow PC member for EuroSys 2021, and publishes in top venues including IPDPS, PerCom, CHIIR, and COMPSAC. Labs and Teams: He leads the Distributed Operating Systems research group at the University of Hamburg, where he mentors students and collaborates on projects involving edge computing, IoT, and adaptive systems.

Michael Pradelمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Program Analysis
• +۹ مورد دیگر

Michael Pradel is a full professor at the University of Stuttgart, specializing in software engineering, programming languages, and machine learning. He will join CISPA as a faculty member from September 2025 while retaining his Stuttgart position. His research focuses on: Neuro-symbolic software analysis Web application analysis Dynamic analysis and test generation Quantum software testing Machine learning for code Recent publications address: LLM-based program repair (RepairAgent, Treefix) WebAssembly analysis (Wasm-R3, LintQ) Python security and analysis (DyLin, DyPyBench) Quantum program analysis (LintQ) Scientific awards: Ernst-Denert Software Engineering Award Emmy Noether grant (1.3M Euro) ERC Starting Grant (1.5M Euro) 3x ACM SIGSOFT Distinguished Paper Award at FSE ACM Distinguished Member Best Paper/Distinguished Paper Awards at ISSTA, ASE, ASPLOS, MSR Key contributions include: DeepBugs for name-based bug detection Getafix for automated bug fixing LintQ for quantum program analysis DyLin for Python dynamic analysis Neuro-symbolic developer tools

Johannes Kinderمشاهده پروفایل

استاد

• Software Security
• Program Analysis
• Machine Learning
• +۳ مورد دیگر

Prof. Dr. Johannes Kinder is a Professor and Chair of Programming Languages and Artificial Intelligence at the Institute of Informatics , Ludwig Maximilian University of Munich. His research focuses on software security through program analysis and machine learning, particularly targeting malware detection , vulnerability analysis , and reverse engineering . He has held faculty positions at Royal Holloway, University of London, and Bundeswehr University Munich. Research Interests include: Securing software systems via program and machine learning techniques Detection of software vulnerabilities and malware Preventing exploitation through binary analysis Applications of formal methods in systems security Recent Publications highlight advancements in binary function embedding , malware detection in npm , and speculative execution attack modeling . His work appears in top venues like USENIX Security and IEEE S&P . Education : Diplom from TU Munich (2005), Doctorate from TU Darmstadt (2010). Professional Roles : General Chair, ACM CCS 2019 Doctoral Symposium Chair, ESSoS 2016 Program Committee member for NDSS 2026, IEEE S&P 2022-2025

Claire Le Gouesمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Defect Repair
• +۵ مورد دیگر

Claire Le Goues is a Professor of Computer Science at Carnegie Mellon University, primarily affiliated with the Software and Societal Systems Department (S3D) within the School of Computer Science (SCS). She serves as the Associate Department Head for Faculty within S3D and leads the squaresLab research group. Le Goues also co-directs the REUSE@CMU summer program and teaches software engineering and program analysis at undergraduate, master's, and PhD levels. Her research spans software engineering and programming languages, with a particular focus on how to construct, maintain, evolve, improve/debug, and assure high-quality software systems. Le Goues has made significant contributions to automated program repair, program analysis, and defect detection. Her work often bridges theoretical foundations with practical applications, addressing real-world challenges in software development and maintenance. Le Goues' recent publications demonstrate a clear trend toward integrating large language models and generative AI with traditional software engineering techniques. Her research examines how these technologies can enhance program repair (BatFix, AdverIntent-Agent), vulnerability detection (Interpretable Vulnerability Detection Reports), and testing (LWDIFF for WebAssembly). This represents an evolution from her earlier foundational work in program repair (GenProg) toward leveraging contemporary AI advancements. She has mentored numerous students through her squaresLab research group and has been instrumental in developing educational programs that prepare the next generation of software engineers. Le Goues is also known for her advocacy for double-blind review processes in academic conferences, having implemented this approach when co-chairing the Symposium for Search-Based Software Engineering in 2014.

Heiko Bornholdtمشاهده پروفایل

پژوهشگر

• Distributed Communication Middleware
• Overlay Networking
• P2P Networks
• +۳ مورد دیگر

Dr. Heiko Bornholdt is a Researcher in the Computer Networks group at the Department of Informatics, University of Hamburg. He is affiliated with the Faculty of Mathematics, Informatics, and Natural Sciences. His research focuses on distributed communication middleware, overlay networking, and edge computing. He holds a doctoral degree and has been with the university since 2016. Position: Research Associate / Postdoc Office: Room F-622, Vogt-Kölln-Str. 30 Contact: heiko.bornholdt@uni-hamburg.de | +49 40 42883-2332 Research Interests Dr. Bornholdt’s work emphasizes distributed systems , particularly in the context of smart cities and IoT. Key areas include: Overlay networks for edge computing Decentralized privacy-preserving systems Efficient data discovery in IoT Latency-aware network protocols Publications Overview His recent work spans 20+ publications, with significant contributions to: Edge computing middleware (e.g., software-defined overlay networks) Secure communication in untrusted environments Smart urban data spaces Awards & Grants No specific awards mentioned, but active in funded projects including the EU-GDPR compliant blockchain research. Labs & Teams Part of the Computer Networks Team led by Prof. Mathias Fischer, collaborating with researchers like Kevin Röbert and Jeetesh Gupta.

Rui Abreuمشاهده پروفایل

استاد

• Software Engineering
• Software Testing
• Debugging
• +۶ مورد دیگر

Rui Abreu is a Professor at the Faculty of Engineering of the University of Porto (FEUP), Portugal, with extensive expertise in software quality, testing, and debugging. Previously, he served as Associate Professor at IST-ULisbon and Assistant Professor at the University of Porto. His research bridges academia and industry through roles including Visiting Researcher at Google NYC (2019-2020) and co-founding DashDash, a $9M Series A-funded startup for spreadsheet-based web app development. His educational background includes a Ph.D. in Computer Science - Software Engineering from Delft University of Technology and an M.Sc. in Computer and Systems Engineering from the University of Minho. His research focuses on automating software testing and debugging , with growing emphasis on quantum software testing, vulnerability detection, and AI-assisted development tools. Recent work explores large language models for loop invariant generation, interpretable vulnerability reports, and quantum mutation testing. His publication trends reveal a strong shift toward security-critical systems and emerging computing paradigms , with 30% of recent papers addressing quantum software challenges and 45% focusing on vulnerability detection/repair. The work consistently combines static/dynamic analysis with machine learning, targeting practical tool development for real-world engineering problems. 6 Best Paper Awards Distinguished Paper Award at ESEC/FSE 2019 Abreu actively mentors through conference committees (serving on 12+ program committees in 2024-2025) and industry engagement. His DashDash venture demonstrates successful technology transfer, while Google collaboration advanced C/C++ security tooling. Current work includes quantum software metrics and security commit standardization. He leads research teams focused on software quality automation, with recent projects including GZoltarAction (GitHub fault localization bot) and Maestro (vulnerability repair benchmarking platform). Future directions emphasize scalable security analysis for quantum systems and human-AI collaboration in debugging workflows.

Deian Stefanمشاهده پروفایل

دانشیار

• Security
• Programming Languages
• Systems
• +۷ مورد دیگر

Deian Stefan is an Associate Professor in the Computer Science and Engineering (CSE) Department at University of California, San Diego (UCSD) . His research focuses on secure systems , spanning security , programming languages , and systems . Notably, he works on WebAssembly , JavaScript JITs , and language-based security (e.g., constant-time programming, memory safety, information flow control). Education : PhD in Computer Science from Stanford University (2015), M.Eng and B.Eng in Electrical Engineering from Cooper Union (2011) His research trend emphasizes secure compilation , transient execution attacks , and hardware-software co-design for security . Key themes include SFI (Software Fault Isolation) , constant-time cryptography , and WebAssembly hardening . Scientific Awards Distinguished paper awards at POPL 2023, IEEE MICRO Top Picks 2024 IEEE Cybersecurity Award for Practice 2022 CSA W first place (2020), DJB Prize (2010) He teaches graduate courses like CSE 227: Graduate Computer Security and CSE 291: Building Secure Systems , covering topics from supply chain attacks to hardware defenses . He co-founded web-security startup Intrinsic (acquired by VMWare).

Amal Ahmedمشاهده پروفایل

استاد

• Compiler Verification
• Language Interoperability
• Type Systems
• +۷ مورد دیگر

Amal Ahmed is a Professor at Khoury College of Computer Sciences, Northeastern University, where she leads the SILC (Secure Interoperability, Languages, and Compilers) research group. She holds a Ph.D. in Computer Science from Princeton University. Her research focuses on programming languages, compilers, and software security, with emphasis on compiler verification, language interoperability, type systems, gradual typing, and secure compilation. She teaches courses including CS7470 (Seminar in PL: Logical Relations) and CS7400 (Intensive Principles of Programming Languages). Research Focus Dr. Ahmed's work bridges theoretical foundations and practical implementation, exploring: semantics and type systems for imperative/probabilistic languages; safe multi-language interoperability; compiler correctness; gradual typing; and provenance. Her recent publications demonstrate strong emphasis on secure compilation techniques, WebAssembly interoperability, and formal verification of compiler transformations. Professional Recognition NSF CAREER Award recipient Keynote speaker at major conferences including OOPSLA 2023, LICS 2022, and ESOP 2018 Program chair for POPL 2023 and OOPSLA 2022 Editorial board member for Journal of Functional Programming and Mathematical Structures in Computer Science Research Team & Students Dr. Ahmed leads an active research group with 7 PhD students and 1 postdoc. She has graduated 4 PhD students who now hold academic positions at University of Michigan, UBC, and Northeastern. Her mentorship extends to numerous MS students and undergraduates, with several receiving NSF GRFP awards.

Anton Semjonovمشاهده پروفایل

پژوهشگر

• Computation Offloading
• Edge Computing
• Distributed Systems
• +۷ مورد دیگر

Anton Semjonov is a Research Associate in the Distributed Operating Systems (DOS) group at the Department of Informatics, University of Hamburg, working under Prof. Dr. Janick Edinger. He also leads the interdisciplinary Creative Lab "base.camp" at the faculty level, fostering student innovation and real-world problem solving. His academic journey includes a Master’s in Informatics with a focus on Information Security from Universität Hamburg (2023) and a Bachelor’s in General Engineering Science with a focus on Computer Science from TU Hamburg (2020). Master of Science, Informatics (Information Security), Universität Hamburg, 2023 Bilingual Bachelor of Engineering, General Engineering Science (Computer Science), TU Hamburg, 2020 His research focuses on computation offloading and edge computing, particularly through browser-based middleware like Wasimoff, which leverages WebAssembly to enable zero-setup, volunteer-driven distributed computing. He also investigates coordination in distributed systems and information security, with publications at Middleware and IEEE PerCom. His work extends into computer science education, where he analyzes how creative labs bridge gaps in traditional curricula. The most recent articles highlight a strong trend in decentralized, secure, and scalable computing frameworks that utilize idle edge devices through web browsers. These works emphasize real-world deployment, performance evaluation, and the integration of privacy-preserving and context-aware mechanisms in heterogeneous environments. There is a clear interdisciplinary thread combining systems research with educational innovation. No scientific awards have been mentioned in the provided materials. Anton Semjonov is actively involved in research advising through his leadership in the DOS group and the base.camp lab. He contributes to research projects such as DDLitLab's LegalGPT initiative. While no formal grants are listed, his ongoing contract and project involvement suggest active funding support. He collaborates with Prof. Edinger and other researchers on distributed systems and AI applications. He is a key member of the Distributed Operating Systems research group and leads the Creative Lab "base.camp," which serves as an interdisciplinary platform for students to develop innovative solutions to real-world problems. These environments support open-ended, exploratory learning and promote collaboration across academic and societal domains.

• Binary Analysis
• Reverse Engineering
• Software Security
• +۷ مورد دیگر

Thorsten Holz is a Professor and Head of the Chair for System Security at Ruhr-University Bochum's Faculty of Computer Science. His research team focuses on critical areas of cybersecurity including binary analysis, automated vulnerability discovery (fuzzing), embedded systems security, and privacy compliance (GDPR). Research Focus: His work spans: Binary analysis & reverse engineering techniques Software security with emphasis on fuzzing and automated vulnerability assessment Security of embedded/IoT systems Privacy mechanisms and GDPR implementation Network and internet security protocols Publication Trends: Recent works (2024-2025) demonstrate strong emphasis on: Advanced fuzzing methodologies for software/hardware systems Security of satellite and aerospace systems Detection of AI-generated media (deepfakes) and LLM vulnerabilities Trusted execution environments (TEEs) and memory corruption defenses Social media/platform security abuses He leads a research group developing cutting-edge tools for vulnerability discovery and security validation, with significant real-world impact in both academic and industry domains.

Benoit Baudryمشاهده پروفایل

استاد

• Software testing
• Software diversity
• Randomization
• +۱ مورد دیگر

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 .

Michael Pradelمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Program Analysis
• +۶ مورد دیگر

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.

Bryan Parnoمشاهده پروفایل

استاد

• Secure Systems
• Formal Verification
• Cryptography
• +۹ مورد دیگر

Bryan Parno is a Professor at Carnegie Mellon University, holding the Kavčić-Moura Chair in Electrical and Computer Engineering and Computer Science. His work bridges theoretical and practical aspects of secure systems verification, focusing on formal methods to ensure rigorous security guarantees. Research Areas: Secure systems, formal verification, cryptography, concurrency, distributed systems Key Contributions: Development of Verus, Leaf, IronFleet, and FastVer2 for verified secure systems Awards: Jay Lepreau Best Paper (OSDI 2025), IEEE Cybersecurity Award for Practice (2024), Distinguished Artifact Award (SOSP 2024) His recent publications demonstrate a focus on scalable formal verification across diverse domains, including Rust programming, WebAssembly sandboxing, and cryptographic protocols. Tools like Verus and OwlC enable provably correct implementations with performance optimizations. Scientific recognition includes: ACM Doctoral Dissertation Award (2011) IEEE Golden Core Recognition (2023) Forbes 30-Under-30 (2011) Sloan Research Fellowship (2018) Multiple best paper awards at USENIX Security, CAV, and IEEE S&P Parno advises PhD students in secure systems and contributes to critical infrastructure projects like Project Everest. His lab develops open-source tools for verified cryptography and systems programming.