جست‌وجوی استاد و پژوهشگر

• Software Engineering
• Programming Languages
• Static Analysis
• +۴ مورد دیگر

Michael Schröder is a Researcher at TU Wien's Faculty of Informatics, affiliated with the Institute of Software Technology. He holds a BSc and a Dipl.-Ing. (Master's equivalent) in Informatics. His research focuses on software engineering, static analysis, and programming languages, with notable contributions to probabilistic program analysis, security, and empirical studies on developer workflows. Education : Bachelor of Science in Informatics Diplom-Ingenieur (Dipl.-Ing.) in Informatics from TU Wien Research Interests : His work spans static analysis of probabilistic programs, security in software repositories, grammar inference for ad hoc parsers, feature flag dependency analysis in large systems, and empirical studies on command-line tool customization. He has also contributed to medical research in pediatric oncology through a 2019 study on leukemia genetics. Recent Trends in Publications : Recent efforts emphasize language-agnostic static analysis frameworks (2024), lateral movement detection in source code (2023), and grammar inference techniques for parsers (2022). Earlier work includes neural ranking models (2020) and transactional memory systems (2015). Grants & Advising : No explicitly listed grants or student advisement, though recent theses supervised include static grammar inference projects (2025). Labs/Teams : Not explicitly mentioned in available records.

Florian Sextlمشاهده پروفایل

پژوهشگر ارشد

• Program Verification
• Formal Methods
• Programming Languages
• +۳ مورد دیگر

Florian Sextl is a Research Fellow and university assistant at the Formal Methods in Systems Engineering research unit at TU Wien, where he conducts research on program verification and formal foundations of programming languages. His work focuses on memory safety fundamentals, particularly through separation logic-based methods and the Rust programming language. Current projects explore biabduction techniques for ensuring memory safety across Rust-C foreign function interfaces and compositional shape analysis. Sextl teaches Program Analysis courses and has supervised research on join operators for bi-abductive analysis of low-level code. He maintains expertise in interactive theorem proving with Isabelle/HOL and Rocq.

• Formal Methods
• Program Analysis
• Verification
• +۹ مورد دیگر

Florian Zuleger is an Associate Professor at TU Wien's Department of Formal Methods in Systems Engineering (E192-04). He has a 100% research focus and serves as Curriculum Coordinator for the Master’s program in Verification and Automated Reasoning. His work emphasizes automated methods for termination analysis, resource-bound estimation, verification of programs with dynamic data structures, parameterized systems, and automated feedback for introductory programming tasks. He has led projects funded by the European Commission (2024–2027), Austrian Science Fund (FWF), Amazon Research Awards, and Vienna Science and Technology Fund. Research Interests: Automated Program Verification Formal Methods for Concurrent Systems Separation Logic and Decision Procedures Resource and Complexity Analysis Parameterized Model Checking Inductive Logic in Verification Grants & Advising: Zuleger’s recent grants explore verification of safety-critical applications and automated cost analysis. He has advised numerous students on topics ranging from verified data structures to fault-tolerant algorithms. His projects include collaboration with Amazon, the European Commission, and FWF. Labs/Teams: Involved with the LogiCS Research Group, focusing on logical methods in computer science, and contributes to tool development (e.g., ATLAS, SpecBMC, SL-COMP competitions).

• Formal Methods
• Temporal Logic
• Automata Theory
• +۵ مورد دیگر

Michele Chiari is a PostDoc Researcher at TU Wien's TrustCPS Group led by Prof. Ezio Bartocci. Previously, he was a PhD candidate and PostDoc at Politecnico di Milano's DEIB in the DeepSE group. His primary affiliations include TU Wien and the TrustCPS group, with a focus on formal verification and cyber-physical systems. Education: PhD candidate and PostDoc at Politecnico di Milano's Department of Electronics, Information, and Bioengineering (DEIB). Research interests include formal methods for safety-critical systems, temporal logic, automata theory, model checking for recursive probabilistic programs, infrastructure-as-code modeling (DOML), floating-point computation verification, and approximate computing. Research highlights: Development of POTL (Probabilistic Operator Temporal Logic), model checkers for operator precedence languages (POMC), and contributions to the PIACERE and CORPORA projects. His work bridges theoretical formal methods with practical applications in software engineering and embedded systems. Key projects include leadership of the EU-funded MSCA PF CORPORA project (2023–present) and contributions to the PIACERE H2020 initiative. Collaborations include tools like TAFFO (floating-point precision tuner) and DOML (Infrastructure-as-Code modeling framework). Labs/Teams: Core member of TU Wien's TrustCPS Group and former contributor to Politecnico di Milano's DeepSE Group. Active in conferences like CAV, RV, and CAiSE, with recent service roles on OOPSLA and RV program committees.

• Agent Based Modelling
• Reactive synthesis
• Formal Methods
• +۶ مورد دیگر

Luca Di Stefano is a Post-Doc Researcher at Technische Universität Wien (TU Wien) since March 2024. His research focuses on the specification and verification of complex collective systems like multi-agent systems and robot swarms, using formal methods such as model checking and reactive synthesis. He works on online formal techniques including runtime monitoring. Research Interests: Software verification Model checking Multi-agent systems Formal semantics Process calculi Reactive synthesis Static analysis Recent Article Trends: His work spans formal verification of reconfigurable systems, emergent behavior in collective systems, and synthesis techniques for infinite-state models. Keywords include Agent-Based Modelling, Formal Methods, Temporal Logic, and Runtime Monitoring. Thesis Supervision: He supervises BSc and MSc theses at TU Wien, with Ezio Bartocci as main advisor. Examples include "Type checking a novel language for reconfigurable multi-agent systems" (Benjamin Stolz, 2025) and "Evaluating in-memory caching strategies" (Love Lyckaro, 2023). Teaching: He teaches courses like "Scientific Research and Writing" and "GPU Architectures and Computing" at TU Wien, and has served as teaching assistant for concurrent programming courses at University of Gothenburg and Chalmers. Labs & Projects: He contributes to tools like LAbS (attribute-based stigmergy language), SLiVER (verification tool), R-CHECK (model checking for reconfigurable systems), sweap (symbolic reactive synthesis), and pyxmv (Python interface for nuXmv).

• Software Engineering
• Program Analysis
• Automated Testing
• +۲ مورد دیگر

Markus Fleischmann is a Researcher at the Vienna University of Technology , affiliated with the Faculty of Informatics and the Department of Software Engineering . His work focuses on improving program analyzers through constraint-based testing and formal verification. Role: Researcher (PreDoc) Contact: markus.fleischmann@tuwien.ac.at Project: MirandaTesting (2023–2028): Automated soundness testing of program analyzers Research areas include: Program analysis and testing Constraint-based verification Formal methods in software engineering Markus is based in Room HB0222 at Favoritenstrasse 9, and his recent publications emphasize automated testing frameworks for program analyzers.

• Software Engineering
• Program Analysis
• Software Testing
• +۴ مورد دیگر

David Michael Kaindlstorfer is a PreDoc Researcher at the Department of Software Engineering, Faculty of Informatics, Vienna University of Technology (TU Wien). He holds the academic rank of Researcher and teaches courses including Advanced Software Engineering (194.187) and Software Engineering (194.020) for the 2025W semester. His research centers on program analysis and software testing, with specific expertise in developing constraint-based test oracles and interrogation testing methodologies to address soundness and precision issues in static program analyzers. He also investigates symbolic execution enhancements for shape analysis of C programs, particularly focusing on linked data structures and memory safety verification. Current work is anchored in the MirandaTesting project (2023-2028) , which pioneers novel testing frameworks for program analysis tools. Kaindlstorfer’s recent publications at ASE 2024 demonstrate a clear research trajectory toward improving the reliability of automated program analysis through innovative testing strategies. His work bridges theoretical advancements in symbolic execution with practical applications in software verification, particularly for low-level systems programming. As a core contributor to the MirandaTesting initiative, he collaborates on developing infrastructure for large-scale interrogation of program analyzers. His technical role involves designing constraint-based oracle mechanisms and refining abstraction techniques for complex heap structures.

Raimundo Saonaمشاهده پروفایل

پژوهشگر ارشد

• Game Theory
• Probability Theory
• Algorithmic Game Theory
• +۳ مورد دیگر

Raimundo Saona is a Research Fellow in the Department of Mathematics at the London School of Economics and Political Science (LSE), where he joined in 2025. His work bridges theoretical mathematics with practical applications in computer science and decision theory. His research focuses on Game Theory, Probability Theory, Algorithmic Game Theory, Stochastic Analysis, Optimal Control, and Imprecise Probability Theory. He develops mathematical tools to provide new insights on situations involving uncertainty, working with both continuous and discrete models, proving theoretical existence theorems, coding efficient algorithms, and analyzing both dynamic online and static offline settings. His publication record shows a strong focus on stochastic games, Markov decision processes, and prophet inequalities. His recent work (2022-2024) has centered on ergodic unobservable MDPs, marginal values in stochastic games, and zero-sum random games on directed graphs, demonstrating his continued contribution to advancing theoretical frameworks in game theory and decision processes. His earlier work established foundational results in POMDPs and prophet inequalities.

Sakeena Muntahaمشاهده پروفایل

پژوهشگر

• Machine Learning
• Computer Vision
• Image Processing
• +۳ مورد دیگر

Sakeena Muntaha serves as a Junior Researcher at the University of Applied Sciences St. Pölten, affiliated with the Institute of Creative\Media/Technologies and the Department of Media and Digital Technologies since 2017. Currently on leave, she contributes to the institution's research mission through interdisciplinary projects spanning computer vision and applied machine learning. Her academic foundation includes a Master's degree in Computer Engineering from the National University of Sciences and Technology (NUST), Pakistan (2016) and a Bachelor's degree in Computer System Engineering from the NFC Institute of Engineering and Technology (NFCIET), Pakistan (2012). These qualifications underpin her technical expertise in visual computing systems. Dr. Muntaha's research program centers on machine learning and computer vision with dual application tracks: medical diagnostics (skin lesion segmentation, dermoscopy analysis) and environmental/urban systems (building footprint extraction, flood monitoring, real estate analysis). Her methodological approach integrates deep learning architectures with classical image processing techniques like level sets and Gabor filters, demonstrating versatility across domains from cultural heritage preservation to cybersecurity. Recent work shows increasing focus on robustness evaluation and real-world deployment challenges in vision systems. Analysis of her 15 most recent publications reveals strong thematic continuity in computer vision applications, with growing sophistication in handling real-world data constraints. Early work focused on medical imaging and malware detection, while recent publications emphasize urban infrastructure analysis and environmental monitoring, reflecting strategic alignment with societal challenges. The consistent use of deep learning frameworks across diverse domains highlights her technical agility. As an active member of the Media Computing Research Group, she contributes to projects including IMREA (Intelligent Multimodal Real Estate Assessment), Scribe ID AI (cultural heritage analysis), and ImmBild (location assessment via computer vision). Her collaborative research involves partnerships with institutions across Austria and Pakistan, though specific grant details and advising activities are not documented in available sources.