Find Academic Supervisors

Sarah WinterView profile

Associate Professor

• Theoretical Computer Science
• Automata Theory
• Logic in Computer Science
• +7 more

Sarah Winter is a tenured Associate Professor (Maîtresse de Conférences) at Université Paris Cité and a member of the Automata and Applications team at IRIF (Institut de Recherche en Informatique Fondamentale). Previously, she was a postdoctoral researcher at Université libre de Bruxelles (2019–2023) in the Formal Methods and Verification group, and she completed her PhD in Computer Science at RWTH Aachen University under Christof Löding (2014–2018). Doctoral Degree: Computer Science, RWTH Aachen University, 2018 Master’s Degree: Computer Science, RWTH Aachen University, 2013 Bachelor’s Degree: Computer Science, RWTH Aachen University, 2011 Her research lies at the intersection of theoretical computer science, logic, and automata theory. She focuses on transducer synthesis, formal verification, streaming string transducers, delay games, and hyperproperties. Her work explores the computability and definability of functions and relations over infinite words and trees, often using logical and automata-theoretic frameworks. She investigates how systems can be synthesized from specifications, especially under constraints like delay or partial observability. Her recent publications, appearing in top-tier journals and conferences such as LMCS, TheoretiCS, LICS, and ICALP, show a consistent trend toward formal models of computation involving transducers, games with delay, and logical synthesis. Keywords across her work include reactive synthesis, automata on infinite structures, function uniformization, and model checking for hyperlogics. Her collaborations with researchers like Martin Zimmermann and Emmanuel Filiot reflect a strong network in European formal methods. Best Student Paper Award, MFCS 2018 Sarah Winter has advised students at the Master’s and PhD levels, as evidenced by her own academic lineage and supervision roles in publications, though no explicit list of advisees is provided. She has not mentioned specific grants, but her postdoctoral and faculty positions suggest funding support. She is actively involved in the theoretical computer science community, giving talks at international venues and workshops. She is a core member of the Automata and Applications team at IRIF, contributing to research on automata theory and its applications in verification and programming languages. Her work forms part of a broader effort to develop rigorous foundations for computing systems.

Alessandra GorlaView profile

Associate Professor

• Malware detection for mobile applications
• Automatic software repair
• Software testing
• +4 more

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.

Diego GarbervetskyView profile

Associate Professor

• Static analysis
• Program verification
• Smart Contract analysis
• +5 more

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.

Max JansenView profile

Research Fellow

• Educational Inequalities
• Social Stratification and Mobility
• Political Sociology
• +5 more

Max Jansen is a Research Fellow at the Institute of Sociology within the Faculty of Social Sciences at Goethe University Frankfurt. He contributes to the DFG-funded Research Group RISS (Reconfiguration and Internalization of Social Structure), specifically Project No. 4 on Internalized Efficacy Beliefs for Participation in Education and Political Life. His educational background includes: Master's in International Studies / Peace and Conflict Studies and Gender Studies (Goethe University Frankfurt) Bachelor's in Social Sciences (University of Cologne) International research experiences span Lebanon (American University of Beirut), Israel (Ben-Gurion University), and Hungary (Corvinus University). Jansen's research centers on educational inequalities, social stratification, and the Impostor Phenomenon (IP), employing sociological perspectives with innovative survey methodologies. His work examines how efficacy beliefs mediate political participation and educational trajectories among adolescents from diverse socioeconomic and migration backgrounds. Current projects involve large-scale surveys of 15-17-year-olds across Germany. His publication record reveals a strong focus on IP measurement development (notably the IPSS-3 scale) and its intersection with structural inequalities. Recent works demonstrate cross-national validation efforts and connections between impostor feelings, discrimination, and educational outcomes. Key journals include Frontiers in Psychology , Cogent Education , and Politics and Governance . Awards include the Best Poster Award at the Sixth Joint Doctoral Conference (2024) for work on workplace attachment and discrimination. Jansen actively contributes to academic governance as a board member of the GRADE Center Social Sciences and Forum for Critical Science (FkW), serves on AQAS expert panels for international study programs, and participates in graduate programs at the Institute for Social Research (IfS) and DIPF. His research integrates with collaborative initiatives including the RISS research group, Dialectics of Participation graduate program, and Peers4Practic teacher-researcher tandems.

Sebastian KuckukView profile

Researcher

• High Performance Computing
• GPU Programming
• Parallel Computing
• +7 more

Dr. Sebastian Kuckuk is a researcher and head of training at the Erlangen National High Performance Computing Center (NHR@FAU), Friedrich-Alexander-Universität Erlangen-Nürnberg. He is affiliated with the Department of Computer Science and contributes to the Chair of System Simulation. His work bridges research, training, and software development in high-performance computing. Education: PhD in Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (2019) His research focuses on enhancing performance portability and programmer productivity using domain-specific languages, code generation, automatic parallelization, and GPU programming. These techniques are applied to develop massively parallel numerical solvers for computational fluid dynamics, particularly for the shallow water equations. He is a core developer of the ExaStencils framework, which enables automated generation of efficient multigrid solvers for structured and patch-structured grids. Analysis of his recent publications (2020–2025) reveals a consistent focus on code generation, GPU acceleration, and solver optimization for fluid dynamics problems. Key themes include heterogeneous computing, block-structured grids, and adaptive methods. His work integrates advanced compiler techniques with numerical mathematics to improve scalability and performance on modern HPC architectures. Scientific Recognition: NVIDIA Deep Learning Institute (DLI) University Ambassador Certified Instructor for DLI courses in GPU programming and CUDA He actively contributes to teaching and training through courses such as Programming Techniques for Supercomputers and High-End Simulation in Practice . He conducts workshops and tutorials on GPU programming and performance optimization. While no formal students are listed, his mentoring role is evident through collaborative research and training activities. He has no recorded grants in the provided text, but his involvement in NHR and KONWIHR projects indicates active participation in funded HPC initiatives. Laboratories and Projects: Lead developer of ExaStencils , a code generation framework for multigrid solvers Contributor to GHODDESS , a module for higher-order discretizations in shallow water modeling Active in NHR@FAU and KONWIHR projects focused on GPU computing and performance optimization

Giacomo ComoView profile

Associate Professor

• Control Theory
• Network Dynamics
• Game Theory
• +13 more

Giacomo Como is an Associate Professor in the Department of Automatic Control at the Faculty of Engineering, Lund University, Sweden. He has been affiliated with the university since August 2011, contributing significantly to research and education in systems and control theory. His research interests include network dynamics, game theory, applied probability, and distributed control, with applications in cyber-physical systems, transportation networks, and socio-economic systems. His work emphasizes resilience, information flow, and emergent behaviors in large-scale interconnected systems. The recent publications highlight a strong focus on distributed control, routing in dynamical networks, opinion dynamics, and cascading failures. These works integrate concepts from control theory, graph theory, and stochastic processes, demonstrating interdisciplinary depth in analyzing and designing robust networked systems. George S. Axelby Outstanding Paper Award (2015) Project Research Grant from the Swedish Research Council (VR), 2016–2019 Como has supervised master’s theses and taught both undergraduate and PhD courses such as Network Dynamics and Nonlinear Control. He has also been active in academic service, serving as an Associate Editor for IEEE Transactions on Network Science and Engineering and chairing program committees for international workshops. His collaborations span MIT, Yale, Uppsala University, and the Gran Sasso Science Institute, reflecting broad academic engagement. He leads research in large-scale network dynamics, contributing to foundational and applied aspects of control in complex systems, with ongoing impact in both theoretical and practical domains.

Manu UpadhyayaView profile

Researcher

• Continuous Optimization
• Convex Optimization
• Machine Learning
• +3 more

Manu Upadhyaya is a Doctoral Candidate at Lund University's Department of Automatic Control within the Faculty of Engineering. His research focuses on continuous optimization with applications in machine learning, control systems, and finance. He is actively involved in the Department of Automatic Control's research ecosystem and collaborates internationally with institutions including Inria Paris, UC Berkeley, and ETH Zürich. His educational background includes an MSc in Engineering Physics (2020), an MSc in Finance (2020), and a BSc in Mathematics (2015), all from Lund University. His PhD defense is scheduled for September 26, 2025, under supervisors Pontus Giselsson and Sebastian Banert. Upadhyaya specializes in the design and performance analysis of first-order algorithms for convex optimization problems. His recent work centers on automated Lyapunov analysis frameworks for verifying convergence properties of optimization algorithms, bridging theoretical guarantees with practical implementation. This research has direct applications in machine learning systems and control theory where computational efficiency is critical. His publications demonstrate a strong trend toward computer-aided analysis of optimization algorithms, with emphasis on tight convergence guarantees and automated verification methods. Key contributions appear in high-impact venues like Mathematical Programming, focusing on systematic approaches to algorithm design. Co-organizer of EUROPT 2024 (21st Conference on Advances in Continuous Optimization) Active participant in WASP (Wallenberg AI, Autonomous Systems and Software Program) Member of ELLIIT (Excellence Center at Linköping–Lund in Information Technology) Upadhyaya leads research projects including 'Automatic Lyapunov analysis of optimization algorithms' and contributed to ESA-funded 'AI4GNC' (Artificial intelligence for guidance, navigation, and control). His work connects theoretical optimization with real-world applications in cloud computing and autonomous systems through Lund's RobotLab and WASP initiatives. Current projects focus on scalable control of interconnected systems and optimization for learning frameworks.

Emanuele D'OsualdoView profile

Professor

• Programming Languages
• Verification
• Security
• +8 more

Emanuele D'Osualdo is a Tenure-Track Professor of Formal Methods for Software Engineering at the University of Konstanz, Department of Computer and Information Science. Previously, he was a Postdoctoral Researcher at Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken until April 2024, working with Derek Dreyer on verification of concurrent software. Before that, until September 2020, he was a Marie Curie Fellow at Imperial College London, working with Prof. P. Gardner. From 2015 to 2017, he was a PostDoc in the Concurrency Theory Group at the University of Kaiserslautern, working with Prof. Roland Meyer. His educational background includes: PhD (DPhil) in Computer Science from the University of Oxford (2015), supervised by Prof. C.-H. Luke Ong Undergraduate and master's studies at the University of Udine, Italy, graduating with honors and supported by the Scuola Superiore scholarship Emanuele D'Osualdo's research focuses on Formal Methods for the verification of software, with particular emphasis on two main approaches: automatic verification methods using static analysis and infinite-state model checking; and compositional methods, focusing on program logics for properties beyond safety. His work spans several areas including Programming Languages, Verification, Security, Concurrency Theory, Probabilistic Programs, Types, Static Analysis, Process Algebra, and Model Checking. His research has led to the development of tools such as Soter for automatic safety verification of Erlang programs and James Bound for analyzing π-calculus. His recent publications demonstrate a strong focus on advanced verification techniques for concurrent and distributed systems, with particular attention to linearizability, session types, security protocols, and probabilistic reasoning. His work bridges theoretical foundations with practical applications in software verification, showing a progression from foundational work on π-calculus to more applied verification of concurrent data structures and probabilistic systems. He has received notable recognition for his work, including: Winner of the 2016 CPHC/BCS Distinguished Dissertation award Marie Curie Fellow Emanuele actively supervises students and leads research in formal methods. He is involved in several research projects related to software verification and has presented his work at top-tier conferences including POPL, OOPSLA, ESOP, and CAV. He is scheduled to give a keynote at HYPER'25 in Zagreb and will be attending POPL'25. His research group appears to focus on developing theoretically sound yet practical verification techniques for modern concurrent and distributed software systems.

Helge ParzyjeglaView profile

Researcher

• Publish/Subscribe Systems
• Distributed Event-Based Systems
• Time-Sensitive Networking
• +5 more

Dr. Helge Parzyjegla is a researcher at the Institute of Computer Science at the University of Rostock, Germany. His work focuses on publish/subscribe systems, time-sensitive networking, and autonomous underwater vehicles. He has maintained a consistent publication record since 2005 and continues to produce significant contributions to distributed systems and networking. Dr. Parzyjegla completed his PhD in 2014 at the University of Rostock with a dissertation titled "Engineering Publish/Subscribe Systems and Event-Driven Applications." Prior to that, he earned his Master's degree in 2005 from the Technical University of Berlin with a thesis on "An adaptive broker network for publish/subscribe systems." His research spans several interconnected areas in computer science and engineering. He has made significant contributions to publish/subscribe middleware systems , developing autonomous and adaptive approaches for event-based communication. His work on time-sensitive networking addresses critical challenges in real-time industrial applications, focusing on reliability, scheduling, and security. More recently, he has expanded his research to autonomous underwater vehicles , developing simulation models, path planning algorithms, and collaborative systems for maritime applications. His interdisciplinary approach bridges theoretical computer science with practical engineering applications. An analysis of his recent publications (2021-2025) reveals a clear progression from foundational work on publish/subscribe systems toward more applied research in time-sensitive networking and autonomous underwater vehicles. His work consistently addresses reliability, efficiency, and security challenges in distributed systems. The increasing focus on maritime applications since 2021 demonstrates his ability to adapt his expertise to new application domains while maintaining technical rigor. Best Paper Award in System Software and Security (2015) Dr. Parzyjegla has collaborated extensively with researchers at the University of Rostock and other institutions, particularly in the areas of networked systems and maritime technology. His sustained publication record suggests successful funding for his research activities. His work appears to involve both theoretical development and practical implementation, with numerous collaborations on simulation frameworks and experimental systems. His research appears to be conducted within the broader context of the Institute of Computer Science at the University of Rostock, with particular connections to groups working on distributed systems, networking, and maritime applications. The consistent collaboration with researchers like Gero Mühl, Peter Danielis, and Willi Brekenfelder suggests a cohesive research team focused on networked systems and their applications.

Ulrik Pagh SchultzView profile

Professor

• Generative Programming
• Embedded Systems
• Domain-Specific Languages
• +3 more

Ulrik Pagh Schultz is a Professor at the University of Southern Denmark, specializing in generative programming, domain-specific languages, and embedded systems. His research focuses on automatic code generation, real-time systems, and reconfigurable robotics, with applications in autonomous drone operations and energy modeling for embedded systems. He has served as a committee member and session chair for numerous conferences including PEPM, GPCE, SPLASH, and POPL since 2011. Notable contributions include work on Idris programming language, reversible computing, and service-oriented architectures for drones. His career spans active involvement in programming language design and practical implementation challenges in robotics software engineering, particularly through collaborations at ACM SIGPLAN conferences. While specific students and awards aren't listed, his extensive service roles demonstrate significant academic engagement.

• Computational Fluid Dynamics
• Machine Learning in Fluid Dynamics
• Compressible Flow Modeling
• +3 more

Dr. Deniz Bezgin is a Researcher at the Department of Aerodynamics and Fluid Mechanics of the Technische Universität München (TUM) . Her work focuses on computational fluid dynamics (CFD), machine learning integration in numerical methods, and high-order differentiable solvers for compressible flows. Research specialties include shock-capturing methods, multi-phase flow modeling, and data-driven shape optimization. Developed JAX-Fluids, a fully-differentiable framework for compressible two-phase flows. Key contributions to ENO/WENO schemes and thermodynamically consistent interface models. Current projects explore machine-learned discretizations and GPU-based high-performance computing. Her recent publications address differentiable simulations, data assimilation, and turbulence modeling. She has not received any explicitly listed scientific awards.

• GPU computing
• Parallel computing
• Domain-specific languages
• +9 more

Prof. Dr.-Ing. Richard Membarth is a faculty member at Technische Hochschule Ingolstadt , where he holds the professorship for System-on-a-Chip and AI for Edge Computing. He is also affiliated with the German Research Center for Artificial Intelligence (DFKI) as a Senior Researcher and Team Leader for Compiler Technologies and High-Performance Computing, and with the Saarland University Computer Graphics Lab . His research spans GPU computing, domain-specific languages, and compilers. PhD from Friedrich-Alexander University Erlangen-Nürnberg (2013) Postgraduate diploma from Auckland University of Technology His research focuses on: Parallel computer architectures and programming models Automatic code generation for embedded to HPC systems Image processing, computer graphics, and deep learning applications Domain-specific languages for performance-portable code Recent publications highlight compiler design, GPU acceleration, and parallel algorithms. Scientific awards include the HiPEAC Paper Award (2018) and GPCE Best Paper Award (2015) . Professional roles include organizing High-Performance Graphics conferences as Treasurer (2024-2025) and Papers Chair (2020).

Martin BuchholzView profile

Professor

• High-Frequency Engineering
• RFID Systems
• Antenna Design
• +5 more

Prof. Dr.-Ing. Martin Buchholz is the Head of Electrical Engineering at Saarland University of Applied Sciences . He leads the RI-ComET research group and oversees the High Frequency Laboratory and Optical Communications Laboratory . His work focuses on high-frequency systems, wireless communication, and embedded design. Contact: martin.buchholz@htwsaar.de Location: Room 2302, Goebenstraße 40, Saarbrücken Research Highlights: Development of innovative RFID systems and TPMS (Tire Pressure Monitoring Systems). Advancements in antenna design , software-defined radio , and radio field propagation . Focus on contactless energy transfer , embedded systems , and real-time FPGA implementations . Collaboration with partners like IKU Systems & Services and Stürmer Freizeittechnik for high-altitude balloon projects ( htw saar stratos ). Academic Contributions: Co-authored 15+ publications on RFID , OFDM systems , and DVB-H receivers (1999–2014). Key journals/conferences: IEEE Transactions on Consumer Electronics , ISSCC , Wireless Congress Munich . Students & Team: Dipl.-Ing. Joachim Hauck , M.Sc. Andreas Becker , M.Sc. Christian Schmidt , and B. Eng. Tina Müller are listed as team members. Projects include Mission I–VI of the stratosphere balloon program, with test flights from 2014 to 2019. Labs & Facilities: High Frequency Laboratory and Optical Communications Laboratory at Saarland University of Applied Sciences. Technical center for EMC measurements and antenna testing.

Anthony Widjaja LinView profile

Professor

• Automated Reasoning
• String Constraint Solving
• Formal Language Theory
• +5 more

Anthony Widjaja Lin is a Full Professor (W3) in Theoretical Computer Science (Automated Reasoning) and Max-Planck Fellow at University of Kaiserslautern-Landau, Germany. Previously, he was an Associate Professor in Programming Languages at Oxford University Department of Computer Science and Governing Body Fellow at Kellogg College (2016-2019), and an Assistant Professor at Yale-NUS, Singapore (2014-2016). He completed his PhD in Informatics at University of Edinburgh in 2010 under Leonid Libkin (supervisor) and Richard Mayr (co-advisor). Dr. Lin's educational background includes: PhD in Informatics, University of Edinburgh (2010) MSc, University of Toronto BSc (Honours), Melbourne University Dr. Lin's research focuses on automated reasoning, particularly over strings, formal language theory, learning/synthesis, and foundations of machine learning. His work has significant applications in software verification, program synthesis, querying graph databases, and computer security. He leads the development of the OSTRICH string solver, which won the QF_S (Single Query Track) in SMT-COMP 2023. His research has evolved from foundational work on string constraint solving to applications in verification of string-manipulating programs and more recently to connections with machine learning models like transformers. Dr. Lin has received numerous prestigious awards including an ERC Consolidator Grant (2023), Amazon Research Award (2021), ERC Starting Grant (2017), Google Faculty Award (2017), and the LICS Kleene Award (2010). Dr. Lin has advised several PhD students to completion, including Pascal Bergsträßer, Chih-Duo Hong, and Xuan-Bach Le, who have gone on to become Assistant Professors at institutions like National Chingchi University and Nanyang Technical University. He currently supervises multiple PhD students and postdocs working on string solving, automated reasoning, and verification. Dr. Lin leads the AV-SMP project (Algorithmic Verification of String-Manipulating Programs), which was supported by an ERC Starting Grant (2017-2022) and an Amazon Research Award (2021). His research group develops tools like OSTRICH, SLOTH, and CertiStr for string constraint solving and verification.

• High Performance Computing
• Energy Efficiency
• Parallel Computing
• +6 more

Laura Carrington is a researcher at the University of California, San Diego, specializing in High Performance Computing (HPC) with a focus on energy efficiency, memory management, and performance optimization. She has contributed to the development of tools like PEBIL for binary instrumentation, ADAMANT for data movement analysis, and frameworks for power management in large-scale systems. Her research spans multiple domains including ARM processor evaluation, Xeon Phi vectorization, and communication reduction in graph algorithms. Key collaborations include work with Michael Laurenzano, Allan Snavely, Ananta Tiwari, and Pietro Cicotti. Laura's work addresses critical challenges in HPC such as DVFS configuration optimization, workload colocation, and energy-aware algorithm design. While no explicit academic rank is stated, her extensive publication record across 2002-2019 in top venues like SC, IPDPS, and IJHPCA establishes her as a significant contributor to HPC research. Her work has influenced practices in system-level power management, scientific application characterization, and energy-efficient computing for both CPU/DRAM domains and emerging memory technologies.