جست‌وجوی استاد و پژوهشگر

Paul Seiferthمشاهده پروفایل

پژوهشگر

• Computational Geometry
• Algorithms
• Data Structures
• +۳ مورد دیگر

Paul Seiferth is affiliated with the Department of Computer Science at Freie Universität Berlin. His research focuses on computational geometry, algorithms, data structures, and graph theory. He has contributed to topics like Voronoi diagrams, dynamic planar graphs, unit disk routing, and spanner construction. His work emphasizes algorithmic efficiency, time-space trade-offs, and geometric data structures. Education : PhD (2012–2016), Freie Universität Berlin Master's (2010–2012), Freie Universität Berlin Research Interests : His research addresses fundamental problems in computational geometry and graph theory, with applications to wireless networks and geometric algorithms. Key themes include dynamic data structures for proximity problems (e.g., Voronoi diagrams), routing in unit disk graphs, and efficient spanner constructions for directed transmission graphs. Key Contributions : His work on time-space trade-offs for Voronoi diagrams and dynamic planar Voronoi diagrams has advanced algorithmic techniques for geometric problems. He also developed efficient routing schemes for unit disk graphs and reachability oracles for transmission graphs, balancing theoretical guarantees with practical efficiency. Teaching : He teaches ProInformatik I: Logik und Diskrete Mathematik . Labs/Teams : Associated with the AG Theoretische Informatik research group at Freie Universität Berlin.

Thomas Kalinowskiمشاهده پروفایل

استاد

• Applied Mathematics
• Optimization
• Multi-Agent Systems
• +۲ مورد دیگر

Thomas Kalinowski is a Professor at the University of Rostock, affiliated with the Faculty of Mathematics and Natural Sciences and the Institute of Mathematics's Optimization group. He teaches courses like 'Mathematics 2 for ET and INF - Linear Algebra' and 'Mathematical Foundations of Machine Learning.' Email: thomas.kalinowski@uni-rostock.de His research focuses on mathematical methods for multi-agent systems, funded by the European Regional Development Fund (ERDF) from 2025 to 2027. He works in optimization, network theory, and applied mathematics, with teaching responsibilities bridging linear algebra and machine learning. He is involved in projects related to the analysis and optimization of multi-agent systems, indicating expertise in mathematical modeling of complex networks and algorithmic game theory. Current affiliations include the Optimization research group at the Institute of Mathematics, University of Rostock.

Michaela Geierhosمشاهده پروفایل

استاد

• Computational Linguistics
• Computer Science
• Natural Language Processing
• +۵ مورد دیگر

Prof. Dr. Michaela Geierhos holds the Chair of Data Science at the CODE Research Institute, Faculty of Computer Science, Bundeswehr University Munich. Her research bridges computational linguistics and computer science, focusing on semantic information processing and practical applications like cyber threat intelligence and trustworthy AI in law enforcement. Roles: Technical Director at CODE Research Institute (2021–present), Professor of Data Science (2020–present) Collaborations: Partnerships with military, industry, and public sectors; projects include disinformation detection, deepfake identification, and AI for cybersecurity. Her work emphasizes addressing dataset contamination in NLP, developing adjusted evaluation metrics, and exploring biases in healthcare data. She leads research into synthetic data generation, quantum NLP, and privacy-preserving AI. Recent articles focus on contestable AI systems, NER evaluation frameworks, and ethical considerations in language models. Scientific awards include the Best Paper Award at AI4HMO (NATO STO) in 2021. Grants: Directed projects like VIKING (trustworthy AI), KiTIE (technology transfer), and KIMONO (campaign monitoring). Education: Supervised doctoral students, including external candidate Philipp J. Rösch (2025), and contributed to interdisciplinary teaching combining theory and practice.

Eirini Ntoutsiمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Responsible AI
• +۷ مورد دیگر

Prof. Eirini Ntoutsi is a Professor of Open Source Intelligence at the CODE Research Institute for Cybersecurity and Smart Data , Bundeswehr University Munich . She leads the Artificial Intelligence & Machine Learning (AIML) research group , focusing on adaptive learning, responsible AI, and generative AI. Research Interests: Developing intelligent algorithms for real-world data challenges, addressing fairness-aware machine learning, explainable AI, and generative models. Projects: Co-leads the EU-funded MAMMOth (Multimodal AI for Trustworthy Human-Centric Applications) and STELAR (Spatio-Temporal Linked Data for Agri-food) initiatives. Applications: Deploying AI solutions in education, social networks, banking, agriculture, manufacturing, and engineering. Key Contributions: Developed the MMM-Fair open-source toolkit for fairness analysis with no-code interface. Actively contributes to conferences like ECML PKDD , FAccT , IJCNN , and WWW .

Stefan Wolfgang Picklمشاهده پروفایل

استاد

• Operations Research
• Risk Management
• Complex Systems Optimization
• +۳ مورد دیگر

Prof. Dr. Stefan Pickl is a full Professor of Operations Research at Universität der Bundeswehr München, where he leads the Chair of Operations Research and the Core Competence Center COMTESSA. His research integrates operations research, risk management, and complex systems optimization, with applications in critical infrastructure resilience, disaster reduction, and network security. Education includes a diploma in Mathematics and Philosophy from TU Darmstadt (1993), a doctorate (1998), and habilitation (2005) from TU Darmstadt and Universität zu Köln. He was an ERASMUS scholar at EPFL Lausanne. Research focuses on: Optimization of stochastic systems and game-theoretic frameworks for decision support. Risk analysis in transportation security (e.g., BMBF projects RIKOV and REHSTRAIN). Resilience modeling for critical infrastructure against hybrid threats. His recent publications emphasize stochastic positional games, humanitarian logistics, and ethical infrastructure challenges, reflecting interdisciplinary collaboration across computer science, engineering, and social sciences. Awards include three Best Paper Awards (CASYS 2003, 2005, 2007) and the Acquisition Research Symposium Award (2013). He secured significant grants for projects like RIKOV (terrorism risk in rail transport) and REHSTRAIN (high-speed train resilience). Leads the COMTESSA research team with 15+ members, including junior professors, scientists, and engineers. Collaborates with international centers like MUNICH AEROSPACE, CENETIX-NPS, and CODE.

• Discrete Mathematics
• Optimization Methods
• Applications of Mathematics in Everyday Life
• +۱ مورد دیگر

Prof. Dr. Tilla Schade is a Professor of Mathematics, Statistics, and Operations Research at the Department of Automation and Computer Science, Harz University of Applied Sciences. Her work bridges theoretical mathematics with practical applications in optimization and cryptography. Research focus: Discrete mathematics and optimization methods applied to real-world problems Teaching specialties: Basic mathematics, probability theory, statistical methods, linear optimization, algorithmic graph theory Notable research activity: Work on bent functions in coding and cryptography (2013/2014 research semester) Professional engagements: Translator for Springer-Verlag, Study Coordinator, and industry collaborator with companies like Robert Bosch GmbH and MAN Truck & Bus AG Her educational background includes a mathematics degree with computer science minor (Justus Liebig University, 1989) and a doctorate in natural sciences (1994). She has taught at multiple institutions including Magdeburg-Stendal University of Applied Sciences.

Zachary Tatlockمشاهده پروفایل

دانشیار

• Programming Languages
• Formal Verification
• Compiler Optimization
• +۵ مورد دیگر

Zachary Tatlock is an Associate Professor at the Paul G. Allen School of Computer Science & Engineering , University of Washington. He leads the UW PLSE research group and focuses on making programming languages and compilers more accessible through formal verification and practical tool development. Current affiliations: University of Washington (Paul G. Allen School) Academic rank: Associate Professor His research spans programming languages, compiler optimization, and formal verification, with recent work on: E-Graphs and equality saturation for program synthesis Floating-point error analysis and accuracy optimization Accessible web layout verification using formal logic Hardware-software co-design for compiler generation His recent publications demonstrate expertise in both theoretical foundations (congruence closure proofs, anti-unification) and practical implementations (Odyssey tool for FP rewriting, Titanic framework for number systems analysis). Collaborations span institutions like Adobe and involve rigorous formal verification in Coq and CakeML.

Aalok Thakkarمشاهده پروفایل

استادیار

• Programming Languages
• Formal Logic
• Artificial Intelligence
• +۳ مورد دیگر

Aalok Thakkar is an Assistant Professor in the Department of Computer Science at Ashoka University, specializing in Programming Languages , Formal Logic , and Artificial Intelligence . He earned his Ph.D. in 2023 from the University of Pennsylvania , advised by Rajeev Alur and Mayur Naik. His research focuses on example-guided synthesis of relational queries , with applications in program verification, automated reasoning, and AI. Recent work includes the Mobius framework (OOPSLA 2023) and Relational Query Synthesis ⋈ Decision Tree Learning (VLDB 2023). Published in npj Digital Medicine (2021) on pandemic risk modeling Contributed to Natural Computing (2020) on Boolean network concurrency Workshop papers on synthesis algorithm complexity (SYNT 2022) and reactive systems (SYNT 2020) He was previously affiliated with Adobe Systems, Aptos Labs, Amazon AWS, and Bell Labs. Awards include the Alt Carbon Darjeeling Revival Fellowship . Teaching includes courses on Symbolic Logic , Rust programming , and Games on Graphs . He will host an IndiCS Seminar on Automated Synthesis in 2025.

Işıl Dilligمشاهده پروفایل

دانشیار

• programming languages
• program analysis
• program verification
• +۴ مورد دیگر

Işıl Dillig is an Associate Professor of Computer Science at the University of Texas at Austin, where she leads the UToPiA research group. Her work focuses on programming languages, with specific emphasis on program analysis, verification, and synthesis. B.S., M.S., and Ph.D. from Stanford University Her research aims to enhance software reliability, security, and development efficiency through advanced synthesis techniques. Recent work spans: Neurosymbolic and semantic synthesis Blockchain and smart contract optimization Type systems for safety She has received prestigious accolades including: Sloan Fellowship NSF CAREER award Contributions to the field include leadership roles in conference organization and mentoring initiatives. Her lab actively explores applications in databases, security, and concurrent programming.

Michael Winterمشاهده پروفایل

پژوهشگر

• Algorithmic Information Theory
• Music Theory
• Digital Humanities
• +۴ مورد دیگر

Michael Winter is a composer, sound artist, and researcher currently working as a specialist for the Digital Humanities project 'Commoning Biomedicine: Networking Decentralised Collections of Oral Histories' at the Max Planck Institute for the History of Science in Berlin. He is also the co-founder and director of the nonprofit arts organization The Wulf, which hosts free experimental music performances in Los Angeles. His career bridges artistic practice with rigorous academic research in algorithmic information theory and digital humanities. Winter's research interests focus on the intersections of Algorithmic Information Theory, Music Theory, Digital Humanities, Sound Art, Phenomenology, Mathematics, and Epistemology. His work explores how algorithmic processes shape musical composition, perception, and social structures. He frequently examines the connections between music, mathematics, communication theory, and epistemology, with particular attention to how computational models can illuminate phenomenological experiences. His publications reveal a consistent interdisciplinary trajectory, with recent works like 'A simplicity bubble problem and zemblanity in digitally intermediated societies' (2024) demonstrating his ongoing exploration of how algorithmic information theory relates to social phenomena in the digital age. His research often investigates the emergence of complexity, consensus, echo chamber effects, and niche construction through mathematical models, with applications to understanding Big Data and algorithmization in contemporary society. Winter has extensive experience in digital humanities projects, having worked as a research programmer for Wolfram Alpha and the Brain Operation Database developed by the University of Southern California Brain Project. He was also an artist-in-residence at the Akademie Schloss Solitude in Stuttgart, Germany from 2018 to 2019, and co-founded the Los Angeles-based arts organization The Wulf in 2008, which has become a hub for experimental arts.

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.

Mirjam Dürمشاهده پروفایل

استاد

• Mathematical Optimization
• Copositive Programming
• Quadratic Optimization
• +۷ مورد دیگر

Mirjam Dür is a Full Professor (W3) at the Department of Discrete Mathematics, Optimization and Operations Research within the Faculty of Mathematics, Natural Sciences and Technology at the University of Augsburg (since 2017). Previously, she held Full Professor positions at the University of Trier (2011-2017) and other academic roles in Groningen, Darmstadt, and Vienna. Her research focuses on mathematical optimization, particularly copositive programming, quadratic optimization, matrix theory, and conic optimization. Born in Vienna, Austria M.Sc. in Mathematics (1996) and PhD in Applied Mathematics (1999) from University of Trier Positive Habilitation evaluation at TU Darmstadt (2005) Research Interests : Global optimization, quadratic and combinatorial optimization, conic optimization and matrix theory, copositive programming, and applications to graph theory and discrete problems. She has pioneered methods like factorization-based approaches for completely positive matrices and cutting plane techniques in copositive programming. Scientific Awards : 2013 Optimization Letters Best Paper Award 2010 VICI Grant (NWO) 2012 GIF Research Grant (German-Israeli Foundation) Key Contributions : Development of algorithms for copositive optimization, theoretical advances in matrix cones, and novel applications to problems like graph stability and discrete optimization. She serves as Senior Editor for Optimization Methods and Software and editorial board member for multiple optimization journals.

Elisabeth Gaarمشاهده پروفایل

استاد

• operations research
• combinatorial optimization
• graph theory
• +۱ مورد دیگر

Elisabeth Gaar serves as Professor of Optimization within the Chair of Discrete Mathematics, Optimization and Operations Research at the Institute of Mathematics, Faculty of Mathematics, Natural Sciences and Technology, University of Augsburg. She has held this position since May 2024, following a prior appointment from March 2023 to April 2024. Previously, she conducted postdoctoral research at Alpen-Adria-University Klagenfurt and worked at Johannes Kepler University Linz's Institute for Production and Logistics Management from October 2020 to February 2023. Her academic credentials include Bachelor's and Master's degrees in Technical Mathematics with specialization in Operations Research from Graz University of Technology, culminating in a doctorate from Alpen-Adria-University Klagenfurt's Institute of Mathematics in 2018. Dr. Gaar's research focuses on combinatorial optimization and nonlinear programming , with significant contributions to graph theory and algorithmic development. Her work bridges theoretical mathematics with practical applications in logistics and decision systems, emphasizing efficient solution methods for complex optimization problems. Her distinguished recognition includes: ÖGOR award for master's thesis ÖGOR award for doctoral dissertation GOR Young Researchers Award 2022 She collaborates within a specialized research team comprising Prof. Dr. Mirjam Dür, Prof. Dr. Dirk Hachenberger, and administrative support staff including Thomas Hirschmüller, Sara Joosten, and Regina Koller, advancing collective work in discrete mathematics and optimization theory.

• Mathematical Logic
• Theoretical Computer Science
• Proof Complexity
• +۳ مورد دیگر

Professor Moritz Müller holds the Chair of Mathematical Logic at the University of Passau since October 2022, after positions at the University of Freiburg, Barcelona, and Vienna. His research bridges mathematical logic and theoretical computer science, focusing on proof complexity and computational complexity. Current affiliation: University of Passau (Faculty of Computer Science and Mathematics) Prior affiliations: University of Freiburg, Barcelona, Vienna Research interests center on the P versus NP problem, proof complexity, and the interplay between mathematical logic and computational theory. His work explores foundational questions like the inherent difficulty of proving complexity lower bounds and the structure of proofs in restricted systems. Recent publications analyze parameterized complexity, circuit lower bounds, and logical frameworks for computational constraints. Key themes include automating proof systems, NP search problems, and algebraic approaches to complexity hierarchies. Scientific contributions have been recognized with a Best Paper Award at FOCS19. His team 'Logic in Passau' investigates logical foundations of algorithmic law and structural representations in foundational theories.