جست‌وجوی استاد و پژوهشگر

Tian Tanمشاهده پروفایل

استادیار

• Program Analysis
• Static Program Analysis
• Software Engineering
• +۳ مورد دیگر

Tian Tan is an Assistant Professor at the Department of Computer Science and Technology , Nanjing University , where he co-runs the PASCAL Research Group . He previously worked as a postdoctoral researcher at Aarhus University (CASA) and earned his Ph.D. in Computer Science from the University of New South Wales (CORG) in 2017, advised by Prof. Jingling Xue. His research focuses on program analysis techniques and tools for programming languages, software engineering, and security. He has developed frameworks like Tai-e for static analysis and contributed to understanding Java reflection and pointer analysis. Education: Ph.D. (UNSW), B.Eng. (Northwestern Polytechnical University) Teaching: Courses on compilers and program analysis Recent work spans compiler design, cross-language pointer analysis, and security frameworks. His publications emphasize context sensitivity, artifact evaluation, and practical implementations. Scientific Awards: Distinguished Artifact Award (OOPSLA'23) Best Artifact Award (ICSE'25) Distinguished Paper Award (ECOOP'16) Distinguished Paper Award Nominee (ISSRE'17) He serves on program committees for SAS'25, ESEC/FSE'25, and SOAP'25, and has reviewed for top-tier venues like TOPLAS, SAS, and ISSTA.

Konstantinos Mamourasمشاهده پروفایل

استادیار

• Programming Languages
• Formal Methods
• Runtime Verification
• +۶ مورد دیگر

Konstantinos Mamouras is an Assistant Professor at the Department of Computer Science, Rice University. His research focuses on programming abstractions for data streams, runtime verification for cyber-physical systems, program semantics, and Kleene Algebra with Tests. Rice University, Houston, TX Department of Computer Science Research Interests : Design of programming abstractions for streaming data Runtime verification of cyber-physical systems Formal methods in program verification Kleene Algebra with Tests (equational theories) Efficient automata-based processing Quantitative monitoring frameworks Recent Scientific Contributions : 2025: Membership Testing for Semantic Regular Expressions (PLDI 2025) 2024: HybridSA GPU regex acceleration (OOPSLA 2024) 2024: Efficient regex with lookaround (POPL 2024) 2023: Bit Vector Automata for regex (OOPSLA 2023) 2021: Quantitative monitoring framework (RV 2021) Scientific Awards : 🏆 Distinguished Paper Award, PLDI 2024 🏆 Best Paper Award, EuroSys 2021 🏆 EATCS Best Theory Paper Award, FoSSaCS 2015 Advising : Mentored PhD student Lingkun Kong (2023) Advised MSc student Zhifu Wang (2022) Current advisees: Alexis Le Glaunec and Agnishom Chattopadhyay Teaching : Spring 2023: IoT Programming and Data Analysis (COMP 418/518) Fall 2022: Reasoning about Algorithms (COMP 382) Spring 2021: Reasoning about Software (COMP 403/503)

Markus Krötzschمشاهده پروفایل

استاد

• Knowledge Graphs
• Semantic Web
• Ontologies
• +۶ مورد دیگر

Markus Krötzsch is a Professor for Knowledge-Based Systems at the Institute for Theoretical Computer Science, Faculty of Computer Science, Technische Universität Dresden. He is also affiliated with TUD's Center for Advancing Electronics (cfaed) and directs the School of Embedded Composite AI (SECAI). His work bridges theoretical research and practical applications in knowledge representation and semantic technologies. Current Projects: Wikidata, Semantic MediaWiki, Nemo (Datalog Engine), ELK Reasoner Areas: Intelligent Knowledge Management, Ontology Languages, Rule-Based Reasoning His research focuses on knowledge graphs , semantic web technologies , and rule-based systems for data integration and reasoning. He contributes to standards like OWL 2 and develops tools for collaborative data management and large-scale knowledge processing. Recent publications highlight advancements in Datalog reasoning (2024-2025), with applications in knowledge graph querying, ontology languages, and computational logic. Keywords include semantic technologies, knowledge representation, and scalable rule engines. He supervises students working on topics like reasoning complexity , chase algorithms , and rule-based data access . His activities include editorial roles (Area Editor of Transactions on Graph Data and Knowledge ) and leadership in academic organizations like the Open Semantic Data Association.

Tomáš Kliegrمشاهده پروفایل

استاد

• Explainable machine learning
• Cognitive biases in machine learning
• Natural language processing
• +۴ مورد دیگر

Tomáš Kliegr is a Professor at the Faculty of Informatics and Statistics of Prague University of Economics and Business, leading the Data Science & Explainable AI (DSXAI) research team. He specializes in explainable machine learning, cognitive biases in AI, natural language processing for entity recognition and knowledge graphs, and preference learning. 2025: Professor of Applied Informatics at Prague University of Economics and Business 2019: Associate Professor (docent) in Applied Informatics at Prague University of Economics and Business 2017: PhD in Research in Electronic Engineering from Queen Mary University London, recognized in the Czech Republic as Ph.D. in Artificial Intelligence and Biocybernetics 2012: PhD in Applied Informatics at Prague University of Economics and Business His research focuses on explainable and interpretable machine learning, particularly rule-based models, cognitive biases in AI, natural language processing, and knowledge graphs. He has contributed to software tools like arc, action-rules, and pyIDS, and leads the EasyMiner.eu project. His articles between 2018 and 2025 span topics like counterfactual explanations, text clustering visualization, SARS-CoV-2 diagnostic modeling, and rule-based ML optimization. He co-organizes the RuleML Webinars and the XI-ML workshop, and was a program committee member for RuleML+RR 2020. Best paper award at RuleML Challenge 2019 He has advised PhD students including Lukas Sykora and Stanislav Vojíř, and collaborates with institutions like the Czech Academy of Sciences and Lawrence Berkeley National Laboratory. His work addresses the intersection of machine learning interpretability and human cognitive factors, with applications in public health and semantic web technologies.

Christian Clemenمشاهده پروفایل

استاد

• Building Information Modeling (BIM)
• Geomatics
• Geographic Information Systems (GIS)
• +۵ مورد دیگر

Prof. Dr.-Ing. Christian Clemen is a faculty member at the Faculty of Spatial Information at HTW Dresden. He specializes in BIM-GIS interoperability , 3D modeling , and digital twin technologies, with a focus on standardization and practical implementation. Active in ISO/TC 59/SC 13/JWG 14 (BIM-GIS) and chairs the DVW AK3 'BIM' (2023–2026). Leads projects like VideoBIM , ClimaLiftControl , and BIM4HEI (ERASMUS+/EU). Develops open-source tools such as IfcTerrain for BIM-GIS data conversion. His research explores topological analysis , point cloud registration , and automated construction monitoring . Recent publications address BIM standardization , terrain modeling , and collaborative workflows . He supervises PhD students like Enrico Romanschek and has mentored graduates such as Tim Kaiser. Teaching includes modules like 3D Modeling , Coordinate Reference Systems , and Building Information Modeling (BIM) across geomatics and green tech programs. He serves as an External Examiner at TU Dublin and contributes to Leitfaden Geodäsie und BIM (Version 3.0).

• Software Engineering
• Formal Methods
• Verification and Validation
• +۵ مورد دیگر

Professor Wolfgang Reif serves as Director of the Institute for Software & Systems Engineering at the University of Augsburg's Faculty of Applied Computer Science. His research spans multiple domains where formal methods meet practical engineering applications, particularly in software engineering, robotics, and self-organizing systems. Prof. Reif's research interests focus on applying formal verification techniques to complex systems engineering challenges. His work bridges theoretical computer science with practical applications in robotics, manufacturing, and autonomous systems. He has developed approaches for verification of concurrent systems, self-organizing production cells, and human-robot collaboration frameworks. His research demonstrates a consistent pattern of translating theoretical formal methods into practical engineering solutions for real-world problems. The recent publications reveal a strong trend toward integrating artificial intelligence with traditional engineering domains. His team has been particularly active in applying machine learning techniques to robotics, manufacturing processes, and verification problems. The publications show increasing focus on practical implementations of self-organizing systems, with applications in drone swarms, production automation, and composite material manufacturing. The work consistently demonstrates how formal verification can be applied to increasingly complex systems involving AI components. Prof. Reif leads a substantial research group with numerous PhD students and collaborators. His team operates within the Institute for Software & Systems Engineering, where they maintain active collaborations with both academic and industrial partners. The research environment supports work across multiple domains including formal verification, robotics, manufacturing systems, and AI applications. The team has developed several notable frameworks including PROTEASE for swarm robotics, SensorClouds for multi-modal sensor processing, and various verification tools built around the KIV system.

Marcus Böschمشاهده پروفایل

پژوهشگر

• Disinformation and Online Media
• Social Media Analysis
• Political Communication
• +۳ مورد دیگر

Marcus Bösch serves as a Researcher at the Department of Information and Media Communication within the Faculty of Design, Media and Information at Hamburg University of Applied Sciences. He is currently active as a research associate in the BMBF-funded HybriD project focused on real-time detection of hybrid disinformation campaigns in online media through information triangulation with journalism and business experts. Education: M.A. in Political Science, Medieval and Modern History, and Media Informatics (University of Cologne and University of Cambridge) M.A. in Game Development and Research (TH Köln/Cologne University of Applied Sciences) Volunteer training at Deutsche Welle His research centers on the intersection of digital platforms and societal impact, with specialized expertise in TikTok's political communication dynamics during elections, hybrid disinformation detection, and immersive storytelling techniques. He examines how algorithmic opacity affects democratic processes while exploring virtual reality's transformative potential in investigative journalism. His work bridges media studies, political science, and emerging technologies to address contemporary challenges in digital information ecosystems. Analysis of his 2019-2021 publications reveals a concentrated focus on TikTok's evolving role in German political communication, particularly during the 2021 federal election. His research demonstrates methodological innovation in studying opaque platforms while connecting disinformation studies with immersive media applications. The consistent emphasis on real-world verification through expert triangulation highlights his practical approach to digital media challenges. Marcus Bösch actively contributes to the HybriD project funded by the German Federal Ministry of Education and Research (BMBF), which develops detection frameworks for hybrid disinformation campaigns. Since 2020, he has published the influential weekly newsletter Understanding TikTok , establishing himself as a key analyst of platform dynamics. His work integrates academic research with industry and journalism practice through the project's triangulation methodology. He operates within the HybriD research team at HAW Hamburg, collaborating with cross-sector experts to develop real-time disinformation detection systems. This project structure facilitates direct knowledge transfer between academic research, journalistic practice, and business intelligence applications in the digital media landscape.

• Artificial Intelligence
• Human-Computer Interaction
• User Modeling
• +۵ مورد دیگر

Cristina Conati is a Professor at the University of British Columbia, Canada, with an extensive research portfolio spanning artificial intelligence, human-computer interaction, and educational technology. Her work focuses on developing intelligent systems that adapt to user characteristics and behaviors, particularly through the analysis of eye-tracking data and other implicit user signals. Her research interests include user-adaptive visualizations, intelligent tutoring systems, explainable AI, and eye-tracking analysis. She investigates how AI can be used to personalize user experiences, particularly in educational contexts, by modeling user cognitive abilities, emotional states, and learning behaviors. Her work often bridges theoretical AI research with practical applications in education and decision support. Analysis of her recent publications (2023-2025) shows a strong focus on explainable AI in educational contexts, adaptive visualization techniques, and the use of eye-tracking to understand and support user interactions. Her research demonstrates a consistent trajectory toward making AI systems more transparent, adaptive, and effective for diverse users across various domains including education, healthcare, and decision-making. Extensive work on user modeling through eye-tracking data Development of adaptive visualization techniques Research on explainable AI for educational applications Studies on how individual differences affect user-system interaction Her research has significant implications for designing more effective educational technologies, decision support systems, and user interfaces that can adapt to individual user needs and characteristics. She has been instrumental in advancing the field of user-adaptive interfaces through both theoretical contributions and practical implementations.

Harshit Jitendra Motwaniمشاهده پروفایل

پژوهشگر ارشد

• Computational Algebraic Geometry
• Formal Verification
• Tensors
• +۵ مورد دیگر

Harshit Jitendra Motwani is a Postdoctoral Researcher at the Max Planck Institute for Software Systems (MPI-SWS) , Germany. Previously, he was a Postdoctoral Fellow at the Hong Kong University of Science and Technology (HKUST) (2023-2024), following doctoral research at Ghent University (2021-2023) and earlier engagements at HKUST, Ghent University, and the University of Bristol . Education : PhD in Mathematics: Algebra and Geometry from Ghent University (2021-2023), Thesis on Algebro-Geometric Algorithms for Program Synthesis; Integrated BSc and MSc in Mathematics and Computing from IIT Kharagpur (2015-2020). Research Focus : Integrates mathematics into computational domains, particularly Computational Algebraic Geometry , Formal Verification , and Tensors . His work spans program synthesis , tensor networks , conditional independence models , and control theory applications . Publications : Recent contributions include algorithmic advancements in formal methods (FM, AAAI, LAGOS), algebraic statistics (IMRN), and quantum computing (SIGMA). His research combines symbolic computation with practical software engineering challenges. Awards & Honors : IEEE Computer Society Larson Best Paper Award (2023) ACM SIGPLAN Distinguished Paper Award (2023) Young Researcher of the Heidelberg Laureate Forum (2023) INSPIRE Scholarship (2015-2020) Teaching : Guest Lecturer at HKUST, Teaching Assistant at RPTU Kaiserslautern-Landau and IIT Kharagpur. Mentored multiple bachelor's projects at Ghent University and IIT Kharagpur.

• Astrophysics
• Exoplanet Detection
• Planet Formation
• +۴ مورد دیگر

René Heller is an astrophysicist and Team Leader for ESA's PLATO mission at the Max Planck Institute for Solar System Research , with habilitation from the University of Göttingen. His research focuses on exoplanet detection , planet formation , and planetary habitability , particularly through innovative data analysis techniques and space mission contributions. 2023–Present: Team Lead and Scientist for ESA's PLATO mission 2016–2023: Scientist for ESA's PLATO mission Habilitation in Astrophysics (2020, University of Göttingen) PhD in Exoplanetary Science (2010–2013, DFG Graduiertenkolleg) His work spans exoplanet habitability , space mission instrumentation , and astrobiological theory , with notable contributions to transit timing variations and exomoon detection . Recent publications focus on JWST observational strategies for superhabitable worlds and innovative propulsion concepts for interstellar exploration. Scientific Awards: 2022 Robert-Wichard-Pohl Medal for teaching excellence 2018 Lecturer Grant from Hans Lenze Foundation 2013 Best talk award from EANA Heller contributes to exoplanet catalog development , mission tool creation , and astrophysical theory , with a particular emphasis on habitable zone planets and observational verification through missions like PLATO and Roman Space Telescope.

Kokil Jaidkaمشاهده پروفایل

استادیار

• Social Media Analytics
• Computational Social Science
• Computer-Mediated Communication
• +۷ مورد دیگر

Kokil Jaidka is an Assistant Professor in the Department of Communications and New Media at the National University of Singapore (NUS), Faculty of Arts and Social Sciences. She is the founding Principal Investigator of the SMOL (Social Media, Online behavior and Language) project, focusing on computer-mediated communication and online human behavior. Her research spans social media analytics, computational social science, digital well-being, and ethical AI. She has contributed to policy discussions on age verification and platform regulation in Singapore and has developed tools like Twilly and SMOLgram for longitudinal online experiments. Her recent scholarly work explores emotional expression in political discourse, emoji use in digital communication, affordances of social platforms, misinformation dynamics, and ethical frameworks for computational research. She advocates for responsible experimentation and has co-developed ethical guidelines for top-tier conferences. Key research trends in her recent publications include: Use of NLP and machine learning to analyze social media content Design and ethics of longitudinal online behavioral studies Impact of platform design on user behavior and well-being Political communication and disinformation in digital spaces Policy implications of social media governance Her scientific contributions emphasize interdisciplinary approaches at the intersection of communication, computer science, and psychology. As a PI and faculty member, she leads the SMOL research team, mentors students, and secures research grants for innovative projects in digital behavior. She actively engages with public discourse through blog posts and media collaborations, translating academic insights for broader audiences. She has developed and shared resources for online experimentation using platforms like Amazon Mechanical Turk, oTree, Empirica, and custom-built tools, supporting open and reproducible research practices.

Delia Kesnerمشاهده پروفایل

استاد

• Programming languages
• Proof-assistants
• Lambda Calculus
• +۱۲ مورد دیگر

Delia Kesner is a Full Professor in Computer Science at UFR d'Informatique, Université Paris Cité, and a member of the Institut de Recherche en Informatique Fondamentale (IRIF), a joint CNRS unit. She holds significant leadership roles as Deputy Director of the École Doctorale 386 de Sciences Mathématiques de Paris Centre, Director (France) of the IRP SINFIN, and In charge of the ERC Unit at CNRS Informatics. She is a Senior Member of the Institut Universitaire de France (IUF) and a Corresponding Member of the Academy of Sciences of Torino, reflecting her high standing in the academic community. Her research is centered on the theoretical foundations of computation, with primary interests in programming languages, lambda calculus, type theory, proof theory, linear logic, and rewriting theory. Her work delves into specific areas such as evaluation strategies (call-by-need, call-by-push-value), intersection type theory, the Curry-Howard isomorphism, resource calculi, and explicit substitutions. This research provides deep insights into the semantics and behavior of programming languages and logical systems. The trends in her recent publications, which appear in top venues like Logical Methods in Computer Science (LMCS) and PACMPL, show a consistent focus on the interplay between logic and computation. Her work often involves developing fine-grained, quantitative models for lambda calculi, investigating inhabitation problems, creating strong bisimulations for classical calculi, and revisiting foundational systems like the Bang Calculus. A unifying theme is the use of type systems and resource-aware semantics to analyze and understand computational processes with precision. Senior Member of Institut Universitaire de France (IUF) Corresponding Member of the Academy of Sciences of Torino RAICES International Cooperation Award (2016) Delia Kesner has a distinguished record of mentoring, having advised numerous PhD students, including well-known researchers like Beniamino Accattoli, Pierre Vial, and Pablo Barenbaum. Her leadership extends to major collaborative research projects and working groups, such as the LIA INFINIS (co-directed with Argentina), the GDRI Linear Logic, and the French working groups SCALP and LHC. She has coordinated international projects like ECOS-Sud and STIC-Amsud. Her service to the community is extensive, having served on the steering committees of FSCD, ETAPS, and IFIP WG 1.6, and on the program committees of countless top conferences including POPL, LICS, and ICFP. She is a central figure in several international research communities, organizing and co-organizing workshops like HOR, LSFA, and the Workshop on Intersection Types. Her work in the LIA INFINIS and IRP SINFIN highlights her commitment to fostering long-term international cooperation, particularly between France and Argentina.

Sebastian Siebertzمشاهده پروفایل

استاد

• Algorithmic Graph Structure Theory
• Sparse Graphs
• Logic in Computer Science
• +۴ مورد دیگر

Professor Sebastian Siebertz is a faculty member in the Department of Computer Science at the Faculty of Mathematics and Computer Science, University of Bremen. His research focuses on the intersection of graph theory and logic in computer science, particularly in the areas of sparse graph classes and algorithmic meta-theorems. His primary research interests include Algorithmic Graph Structure Theory (especially sparse and structurally sparse graphs), Logic in Computer Science (particularly first-order model-checking, query evaluation, enumeration, and counting), and Applications of stability theory in the finite. He has made significant contributions to the theory of bounded expansion and nowhere dense graph classes, which provide robust notions of uniform sparsity. Notably, in collaboration with Martin Grohe and Stephan Kreutzer, he proved that the first-order model-checking problem is fixed-parameter tractable on nowhere dense graph classes. His recent publications (2022-2024) demonstrate a strong focus on extending model-checking results to more general graph classes, exploring connections with stability theory, and developing efficient algorithms for graph problems, particularly in reconfiguration, connectivity, and structural graph theory. Professor Siebertz actively serves the academic community through program committee memberships for major conferences including LICS, IPEC, and Highlights of Logics, Games and Automata, and has organized Dagstuhl seminars on sparsity in algorithms, combinatorics and logic. He currently supervises several doctoral students and postdocs, including Dr. Alexandre Vigny, Mario Grobler, and Nikolas Mählmann, indicating an active research group focused on theoretical computer science problems at the University of Bremen.

• Logic
• Well Quasi-Orders
• Verification
• +۷ مورد دیگر

Sylvain Schmitz is a Professor of Computer Science at Université Paris Cité, affiliated with the Institut de Recherche en Informatique Fondamentale (IRIF). He leads the automata and applications team and is a member of the modelling and verification team. His research focuses on logic, well quasi-orders, verification, formal languages, and database theory. He is actively involved in the academic community, serving on steering and program committees for major conferences such as STACS, LICS, and CSL. PhD in Computer Science, defended on September 24, 2007, at I3S Laboratory, Sophia Antipolis. Habilitation titled Algorithmic Complexity of Well-Quasi-Orders , defended on November 27, 2017, at ENS Paris-Saclay. His research interests span logic, well quasi-orders, verification, formal languages, database theory, theoretical computer science, complexity theory, program verification, automata theory, and model checking. His recent work explores complexity bounds in vector addition systems, reachability problems, and logical foundations of verification. His publications exhibit a strong focus on theoretical foundations of computation, particularly in the analysis of infinite-state systems, complexity hierarchies beyond elementary, and logical characterizations of computational problems. Key themes include well-structured transition systems, non-elementary complexity, and applications of ordinal analysis to verification. IUF junior (2018–2023) Sylvain Schmitz has supervised several PhD students, including Hector Buffière, Aliaume Lopez, Anthony Lick, and Simon Halfon, often in joint supervision with researchers such as Jean Goubault-Larrecq, David Baelde, and Philippe Schnoebelen. His research has been funded by multiple ANR projects including BraVAS, PRODAQ, ReacHard, and AVeriSS. He is a key member of the IRIF laboratory, contributing to research in automata, verification, and logic. He has organized major events such as ICALP 2022 and RP 2020, and is deeply involved in the European theoretical computer science community through committee memberships and conference organization.

Mooly Sagivمشاهده پروفایل

استاد

• Static Program Analysis
• Automated Theorem Proving
• Abstract Interpretation
• +۶ مورد دیگر

Professor Mooly Sagiv is a Chair of Software Systems at the School of Computer Science, Tel Aviv University , focusing on static program analysis and formal verification. His work bridges automated theorem proving with abstract interpretation to develop practical techniques for verifying software systems. Key Research Areas : Static analysis, formal verification, abstract interpretation, and automated reasoning about distributed systems and smart contracts. Notable Contributions : Development of the IVY tool for distributed protocol verification and frameworks for dynamic information flow control in cloud applications. Scientific Recognition : Fellow of the ACM Best Paper Award at PLDI'12 Recent Publications focus on binarized neural networks, stateful network verification, and liveness properties in infinite-state systems using decidable logic fragments.