جست‌وجوی استاد و پژوهشگر

• Satisfiability Modulo Theories
• Automated Reasoning
• Formal Methods
• +۳ مورد دیگر

Clemens Eisenhofer is a PreDoc Researcher at TU Wien's Institute of Logic and Computation within the Faculty of Informatics. His role combines doctoral research with active contributions to multiple funded projects, positioning him at the forefront of SMT solver development and formal methods research. His research centers on advancing Satisfiability Modulo Theories through innovations in bit-vector reasoning, non-classical logics, and custom theory integration. Key focus areas include enhancing Z3's capabilities for word-level operations, embedding proof calculi like connection calculus, and developing user-propagator frameworks. These efforts target practical applications in software verification, program analysis, and constraint solving, with direct implications for reliability-critical systems. Eisenhofer actively contributes to four major research initiatives: ARTIST (2021-2026) on automated reasoning foundations; SFB SPyCoDe (2023-2030) for cyber-physical systems verification; TAIGER (2023-2027) in theorem proving; and ForSmart (2023-2027) for smart contract analysis. These projects provide substantial computational resources and foster international collaborations, though he does not currently supervise students given his PreDoc status. His research operates within TU Wien's Institute of Logic and Computation—a leading European hub for formal methods—leveraging institutional expertise in computational logic and strong industry ties. The institute's collaborative environment supports his work on solver extensions while connecting theoretical advances to practical verification challenges across multiple domains.

• Software Engineering
• Cryptography
• Programming Languages
• +۲ مورد دیگر

Christoph Hochrainer is a PreDoc Researcher at Technische Universität Wien, affiliated with the Software Engineering department. His academic role involves research in software systems and formal methods, supported by projects like ForSmart (2023–2027) and MirandaTesting (2023–2028). He completed his Diploma in automated reasoning at TU Wien in 2020. His research spans software engineering, cryptography, and programming languages, with specialized interests in fuzzing techniques, architecture description languages, and smart contract security. Recent work emphasizes zero-knowledge circuits, Solidity benchmarking, and macro systems for domain-specific tooling. Christoph's publications consistently explore automated testing and formal verification, with a trend toward practical applications in blockchain and secure software pipelines. He supervises student theses, including work on inconsistency detection in Solidity smart contracts. He contributes to collaborative projects focused on formal methods and software reliability, operating within TU Wien's research units. No scientific awards are documented.

• Artificial Intelligence
• Constraint Programming
• Optimization
• +۳ مورد دیگر

Mattias Guns is an Associate Professor in the Department of Computer Science at the Faculty of Engineering Science, KU Leuven. He is a core member of the Declarative Languages and Artificial Intelligence (DTAI) research unit and holds affiliations with Leuven.AI and the KU Leuven Institute for Mobility (LIM). He serves on the Council of the Faculty of Engineering Science and the Programme Committees for Artificial Intelligence and Mobility and Supply Chain. His research centers on bridging Artificial Intelligence with constraint-based optimization, focusing on Explainable AI, Predict-and-Optimize frameworks, and machine learning integration for constraint solving. Key interests include human-centric explainability in decision systems, perceptual reasoning, and energy-efficient optimization models. His work addresses fundamental challenges in program synthesis, scheduling, and trustworthiness of AI planning systems. Recent publications reveal strong trends in fusing machine learning with declarative problem-solving paradigms. Notable themes include LLM-driven constraint modeling, mutational testing for solvers, step-wise explanation generation, and preference learning for unsatisfiable constraints. His research consistently targets real-world applications in supply chain optimization, inventory management, and perceptual reasoning systems. As principal investigator, he leads multiple major projects: TED-AI: Trustworthy Explanations for Decision Making in AI (2025) Towards Human-Centric Explainable Constraint Solving (2025-2028) SAELING: Energy Optimization via Learning (2024-2027) From Natural Language to Constrained Optimization (2023-2027) He has supervised PhD student Mulamba Ke Tchomba on machine learning-enhanced constraint solvers for perceptual reasoning. Within the DTAI research group, he contributes to KU Leuven's leadership in declarative AI through collaborative work on constraint programming foundations and applications. His team actively develops open-source tools like CMPpy for prediction-optimization integration and participates in European AI initiatives through Leuven.AI.

Sourav Chakrabortyمشاهده پروفایل

استاد

• Theoretical Computer Science
• Boolean Functions
• Quantum Complexity
• +۴ مورد دیگر

Sourav Chakraborty is a Professor in the Advanced Computing and Microelectronics Unit (ACMU) of the Computer and Communication Sciences Division at the Indian Statistical Institute (ISI), Kolkata, India. He joined ISI in July 2018 after serving as faculty at Chennai Mathematical Institute from 2010-2018. Previously, he held postdoctoral positions at Centrum Wiskunde & Informatica (CWI) in Amsterdam and Technion in Israel. Education: Ph.D. in Computer Science, University of Chicago (2008) M.S. in Computer Science, University of Chicago (2005) B.Sc. in Mathematics, Chennai Mathematical Institute (2003) Research Focus: Professor Chakraborty specializes in Theoretical Computer Science with emphasis on classical and quantum complexity of Boolean functions, including sensitivity analysis, property testing, and quantum database search. His work extends to graph algorithms, electronic commerce mechanisms, and coding theory. His research explores fundamental questions in computational complexity through innovative mathematical frameworks. Publication Trends: Recent work demonstrates a strong focus on property testing, sampling algorithms, and complexity theory, with significant contributions to streaming algorithms, Boolean function analysis, and quantum query complexity. His publications frequently appear in top theoretical computer science venues and exhibit consistent innovation in algorithm design and complexity boundaries. Awards & Honors: Praise from Donald E. Knuth for streaming algorithms research Inclusion in Oded Goldreich's 'my choices' list for Conditional Sampling and Huge-Object Model work Chakraborty's function named in his honor for Sensitivity Conjecture contributions Academic Service: Teaches courses in discrete mathematics and theoretical computer science, with detailed course materials available through institutional pages. Organized workshops including the 2020 Workshop on Sensitivity and Query Complexity at ISI.

• Artificial Intelligence
• Network Science
• Computational Biology
• +۳ مورد دیگر

Yong Gao is a Professor of Computer Science, Data Science, and Mathematics at the University of British Columbia (UBC) Okanagan, affiliated with the Irving K. Barber Faculty of Science. He holds a PhD from the University of Alberta and leads research in algorithmic and computational problems in artificial intelligence, network science, and computational biology. His work emphasizes graph theory, probabilistic methods, and applications in social media and biological systems. Educational Background : PhD in Computer Science, University of Alberta Research Interests : Algorithmic foundations of AI and network science Graph-based methods for computational biology and social media analysis Probabilistic modeling of complex systems Awards & Grants : Recipient of multiple NSERC Discovery Grants (2006–2019) UBC Okanagan Startup Grant (2005–2008) Senior Member, Association for the Advancement of AI (AAAI) Professional Roles : Member, Centre for Optimization, Convex Analysis and Nonsmooth Analysis Graduate student supervisor Teaching : Courses in algorithm design, artificial intelligence, discrete mathematics, and network science.

Alexey Ignatievمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Formal Methods
• Satisfiability Modulo Theories (SMT)
• +۳ مورد دیگر

Alexey Ignatiev is an Associate Professor in the Optimisation research group at Monash University's Faculty of Information Technology. Previously, he was a postdoctoral researcher and researcher at the University of Lisbon's Faculty of Sciences, focusing on SAT/SMT-based decision procedures. He holds a Ph.D. from the Matrosov Institute for System Dynamics and Control Theory (Russian Academy of Sciences), where his thesis explored parallel CDCL-BDD integration. His research emphasizes formal methods in AI, including explainable AI (XAI), SAT-based reasoning, and optimization for applications like software upgradability, model-based diagnosis, and fault localization. His work spans over 100 publications, with notable contributions to MaxSAT solving (RC2 solver), neuro-symbolic frameworks (NEUSIS), and rigorous explanations for machine learning models. He has collaborated extensively with institutions like the University of Lisbon and Monash University, contributing to advancements in formal verification and interpretable machine learning.

Ioannis Stefanakosمشاهده پروفایل

عضو هیئت علمی

• Formal Verification
• Robotics Safety
• Autonomous Systems
• +۳ مورد دیگر

Ioannis Stefanakos is a Research Associate at the Department of Computer Science, University of York, affiliated with the High Integrity Systems research group. His work focuses on formal verification of autonomous systems, safety-critical robotics, and software performance analysis. Current projects include assurance frameworks for drones, adaptive reinforcement learning in healthcare robotics, and probabilistic modeling of software performance. Recent research emphasizes interdisciplinary applications in UAV systems, medical decision support systems, and collaborative manufacturing robots. No academic awards are listed, though his work has been published in top-tier conferences. Advising and grants details are not explicitly stated, but his involvement in doctoral forum papers suggests potential supervision roles in software systems research.

Christoph Haaseمشاهده پروفایل

دانشیار

• Algorithmic Verification
• Automated Reasoning
• Automata Theory
• +۵ مورد دیگر

Christoph Haase is an Associate Professor at the Department of Computer Science, University of Oxford, and a Fellow of St Catherine’s College. His research focuses on developing rigorous mathematical methods for algorithmic verification, automated reasoning, automata theory, and logic in computer science. University of Oxford, UK (Current) University College London, UK (Former) ENS Paris-Saclay, France (Former) Microsoft Research Cambridge, UK (Former) His work includes fundamental contributions to decision procedures for arithmetic theories, particularly in Presburger and Büchi arithmetic, and applications to verification of software and hardware systems. He leads the ARiAT project, funded by an ERC Starting Grant (2020–2025), aiming to advance quantifier elimination and complexity bounds for arithmetic theories. Key publication trends include verification , automata theory , arithmetic logic , computational complexity , and automated reasoning . Collaborations span institutions like University of Paris, UCL, and Microsoft Research. Scientific Awards : ERC Starting Grant (2019) EPSRC Doctoral Prize (during DPhil studies) He has supervised PhD and MEng projects on topics such as SAT solving, linear arithmetic, and matrix semigroups, often co-supervising with researchers like Stefan Kiefer and James Worrell. Teaching includes Logic and Proof at Oxford and Operating Systems at ENS Paris-Saclay.

Radosław Klimekمشاهده پروفایل

استاد

• Formal Methods
• Software Verification
• Context-Aware Systems
• +۵ مورد دیگر

Radosław Klimek serves as a Professor at AGH University of Science and Technology in Kraków, affiliated with the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering within the Department of Applied Computer Science . His office is located in room C-2 404, and he maintains active contact through email and office hours (Thursdays 11:00-12:00). His research centers on formal methods and software verification , with significant contributions to context-aware systems , logical specifications , and process mining . Key areas include: Deduction-based verification of behavioral models Automatic generation of logical specifications Smart environment applications for rescue operations and tourism Temporal logic applications in software engineering His work bridges theoretical computer science with practical implementations in environmental monitoring and public safety systems. His publication record demonstrates consistent output in high-impact venues, with recent focus on LLM integration for model verification (2025) and context-aware systems for forest monitoring (2024). The research trajectory shows evolution from foundational work in temporal logic (1990s) to contemporary applications in smart environments and AI-assisted verification. No scientific awards were explicitly mentioned in the source materials. Professor Klimek maintains active teaching responsibilities with defined office hours for student consultations. His research spans multiple domains including smart city infrastructure, environmental monitoring systems, and formal verification frameworks. Current projects involve context-aware systems for mountain rescue operations and police interventions, leveraging sensor networks and real-time data processing. His laboratory work focuses on contextual data modeling and deduction-based verification systems , with practical implementations in: Forest monitoring networks Intelligent queue management Tourist assistance applications Smart contract validation These projects integrate formal methods with real-world environmental and public safety challenges.

• Computer Science
• Electronic Engineering
• Integrated Circuit Testing
• +۶ مورد دیگر

Marcello Dalpasso is an Associate Professor of Computer Science at the School of Engineering, University of Padova, Italy, and a member of the Department of Information Engineering. He has held this position since 2004 after serving as a researcher and teaching assistant at the same university from 1998. Born in Ferrara, Italy (1965) Graduated with highest honors in Electronic Engineering (1990), University of Bologna PhD in Electronic Engineering and Computer Science (1994), Rome His research focuses on integrated circuit testing , fault simulation , and algorithm design . He has developed techniques for IDDQ testing , bridging fault modeling , and Boolean satisfiability applications in digital systems. Other contributions include optimization algorithms for Traveling Salesman Problem (TSP) and efficient data structures. Recent publications highlight his work on Answer Set Programming for timing analysis, Python programming education , and TSP neighborhood exploration . His research spans both theoretical and applied domains, from hardware testing to software development and computational biology. He has co-authored textbooks on Computer Networks , Software Design , and Programming in Java/Python/C++ , serving as a key contributor to educational materials in computer science.

Eric Reinerمشاهده پروفایل

استاد مدعو

• Finance
• Financial Engineering
• Formal Methods
• +۳ مورد دیگر

Eric Reiner serves as an Adjunct Professor of Finance and Faculty Director of the Master of Financial Engineering program at UCLA Anderson School of Management. His unique academic profile bridges finance and formal methods, combining financial engineering expertise with advanced computational verification techniques. Dr. Reiner's research spans two distinct domains: traditional finance and formal methods in computer science. His work in formal methods focuses on satisfiability modulo theories (SMT), bit-precise reasoning, and model checking, with publications appearing in leading formal methods venues. This unusual interdisciplinary approach suggests innovative applications of verification techniques to financial systems, potentially addressing challenges in algorithmic trading verification, risk model validation, and financial protocol security. Analysis of his recent publications (2022-2024) reveals a strong focus on improving SMT solver capabilities, particularly for bit-vector reasoning and user extensibility. His work shows progression from theoretical foundations toward practical industrial applications, with increasing attention to proof generation, solver performance optimization, and machine learning techniques for algorithm selection. The consistent publication record in formal methods venues indicates deep technical expertise that complements his finance role. As Faculty Director of the Master of Financial Engineering program, Dr. Reiner oversees curriculum development that likely integrates both traditional finance knowledge and cutting-edge computational verification methods. This distinctive combination prepares students to develop and validate complex financial algorithms with mathematical rigor, addressing growing industry needs for verified financial technologies.

Rolf Drechslerمشاهده پروفایل

استاد

• Formal Verification
• Quantum Computing
• RISC-V Architecture
• +۴ مورد دیگر

Rolf Drechsler is a Full Professor and Head of the Group of Computer Architecture at the University of Bremen's Institute of Computer Science since 2001, and Director of the Cyber-Physical Systems Group at DFKI Bremen since 2011. He holds an adjunct professorship at the Indian Statistical Institute and has been affiliated with Duke University. Education: Diploma (1992) and Dr. phil. nat. (1995) in Computer Science from Goethe University Frankfurt Academic Leadership: Dean of Mathematics and Computer Science Faculty (2018-2025), Vice Rector for Research (2008-2013) His research focuses on formal verification , RISC-V architectures , and quantum/in-memory computing . Recent work explores LLM integration in hardware testing and polynomial-based verification techniques. Publications from 2024-2025 span IEEE Transactions , DATE , and DAC , emphasizing automated verification , quantum circuit mapping , and LLM-driven testbench generation . Scientific Awards IEEE/ACM Best Paper Awards (2013, 2018) Berninghausen-Preis for Innovative Teaching (2018) IEEE Fellow (2015) Founder Award for Solvertec (2013) He has served on program committees for DAC, ICCAD, DATE, and founded graduate schools in Embedded Systems and System Design under Germany's Excellence Initiative.

Arjun Guhaمشاهده پروفایل

دانشیار

• Programming Languages
• Program Synthesis
• Low-Resource Programming Languages
• +۶ مورد دیگر

Arjun Guha is an Associate Professor at Northeastern University's Khoury College of Computer Sciences, where he also serves as the Area Chair for Software. He conducts research in programming languages with a focus on program synthesis for low-resource programming languages and understanding how computer science education is impacted by large language models. His work spans multiple domains including WebAssembly, software-defined networking, and serverless computing. Guha's research interests center around programming language design, implementation, and application. He has made significant contributions to understanding JavaScript through formal semantics (LambdaJS), developing functional reactive programming for web applications (Flapjax), and creating tools for software-defined networks (NetKAT, Frenetic). His recent work focuses on leveraging large language models for code generation in specialized programming languages and understanding their impact on programming education. His publications reveal a strong trend toward applying AI and machine learning techniques to programming language problems, particularly in code generation and understanding. The research spans from foundational programming language theory to practical applications in education and software development tools, with increasing focus on the intersection of programming languages and large language models. Guha has received several prestigious awards including the OOPSLA Most Influential Paper Award in 2019 for his work on Flapjax, an ACM SIGPLAN Research Highlight for his work on NetKAT, and a Best Student Paper Award. His research has been recognized for its foundational contributions to programming language theory and practical impact on software development. OOPSLA Most Influential Paper Award (2019) for Flapjax ACM SIGPLAN Research Highlight for A Fast Compiler for NetKAT Best Student Paper Award for Flapjax paper Guha advises numerous PhD, MS, and undergraduate students, with several alumni now at leading tech companies and academic institutions. His research has been supported by the National Science Foundation, the Department of Energy, the Office of Naval Research, and industry partners including Google, JPMorgan Chase, MathWorks, Meta, Oracle, and Roblox. He leads the Programming Research Laboratory at Northeastern and is actively involved in major research collaborations like the BigCode Project. Guha is a member of the Programming Research Laboratory at Northeastern and leads several major research initiatives including the BigCode Project's evaluation working group. His lab develops practical software systems like MultiPL-E (a polyglot benchmark for Code LLMs) and WasmFX (bringing effect handlers to WebAssembly), with applications in education, software development, and high-performance computing.

Ding Liمشاهده پروفایل

استادیار

• Program Analysis
• Energy Optimization
• Mobile Applications
• +۲ مورد دیگر

Ding Li is an Assistant Professor in the School of Computer Science at Peking University. He holds a Ph.D. in Computer Science from the University of Southern California (USC) and a B.S. from Peking University. His research focuses on program analysis, energy optimization for mobile applications, and security, with publications in top conferences including ICSE, FSE, and ASE. His research interests span: Program Analysis : Techniques to optimize mobile application energy consumption. System Security : Identifying vulnerabilities in Android apps and WebAssembly binaries. Cloud/Edge Computing : Enhancing serverless computing efficiency and federated learning security. Dr. Li's recent work explores the integration of large language models into pointer analysis and automated optimization of resource inefficiencies. His publications demonstrate a consistent focus on practical system optimizations and security enhancements across mobile, cloud, and machine learning domains. Awards: Viterbi Undergraduate Research Mentoring Award (2014)