جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Nonmonotonic Reasoning
• Argumentation Frameworks
• +۴ مورد دیگر

Stefan Woltran is a Full Professor in the Databases and Artificial Intelligence department at TU Wien. He serves as Vice Dean of Academic Affairs for the Informatics Master program and leads the Research Unit for Databases and Artificial Intelligence. His research focuses on logic-based AI, including Propositional Logic, Nonmonotonic Reasoning, Argumentation frameworks, Knowledge Representation, and Logic Programming. He coordinates the Double-Degree Program Logic and Computation. His research projects include analyzing formal properties of logic-based AI approaches, complexity analysis, and developing algorithms via logic and dynamic programming. Notable projects include the HYPAR and REVEAL-AI initiatives exploring abstract argumentation and AI problem-solving. He has contributed to over 150 publications since 2001, focusing on argumentation frameworks, computational complexity, and formal methods. Woltran teaches courses such as Abstract Argumentation, Formal Methods in Computer Science, and Theoretical Computer Science. His work integrates theoretical advancements with practical solver development, such as the ASPARTIX system for argumentation tasks. He actively participates in international conferences and competitions in computational argumentation, emphasizing the application of formal methods to real-world problems.

• Machine Learning
• Graph Neural Networks
• Bioinformatics
• +۳ مورد دیگر

Tamara Drucks is a PreDoc Researcher at the Department of Machine Learning, Technische Universität Wien. She specializes in machine learning, with a focus on graph neural networks, bioinformatics, and optimization algorithms. Drucks teaches courses including 'Introduction to Machine Learning' and 'Theoretical Foundations and Research Topics in Machine Learning.' Her research explores expressive power of graph networks and applications in phylogenetic modeling. Key projects include the StruDL initiative (2023–2027) focusing on maximally expressive GNNs for outerplanar graphs. She has advised one PhD student, Martin Plattner, on optimization techniques in machine learning. Publications span theoretical advancements in GNNs and practical applications in computational biology. Drucks holds a Diploma in Technical Mathematics from TU Wien (2021) and is involved in interdisciplinary research at the intersection of AI and biological data analysis.

Thierry Langerمشاهده پروفایل

استاد

• Computer-Aided Molecular Design
• Pharmacophore Modeling
• Drug Discovery
• +۷ مورد دیگر

Professor Thierry Langer is a Full Professor of Pharmaceutical Chemistry at the University of Vienna’s Faculty of Life Sciences (Department of Pharmaceutical Sciences). He leads research in computational drug design, with a focus on pharmacophore modeling, 3D-QSAR analysis, and AI-driven molecular design. His work bridges theoretical and experimental chemistry, addressing targets like viral proteases (e.g., SARS-CoV-2), GABA receptors, and dopamine transporters. Research interests include: Pharmacophore-guided drug discovery for anti-viral and CNS therapies Development of next-generation computational tools (e.g., PharmacoMatch, QPhAR) Protein-ligand interaction modeling using neural networks and graph-based algorithms Recent studies focus on: Inhibitors for herpesvirus nuclear egress complexes, AI-optimized antivirals, and dopamine transporter inhibitors for cognitive enhancement. His lab collaborates on projects like the NeuroDeRisk initiative to de-risk neurotoxic compounds. Publications emphasize drug repurposing, metabolic pathway analysis, and scalable synthesis methods for promising drug candidates.

Marc Pollefeysمشاهده پروفایل

استاد

• 3D Computer Vision
• Robotics
• Machine Learning
• +۵ مورد دیگر

Marc Pollefeys is a Full Professor of Computer Science at ETH Zurich and Director of the Microsoft Mixed Reality and AI Zurich Lab. He has held roles such as Visiting Professor at Stanford University (2007) and Assistant/Associate Professor at UNC-Chapel Hill (2002–2009). His research focuses on 3D computer vision, robotics, machine learning, and augmented reality. Education: PhD in Computer Science from KU Leuven (1999), followed by postdoctoral research there until 2002. He transitioned to academic roles at UNC-Chapel Hill before joining ETH Zurich in 2007. Research interests include 3D reconstruction, visual localization, SLAM, and applications in archaeology, urban modeling, and robotics. Notable projects include real-time 3D scanning, city-scale reconstruction, and autonomous vision-based drones. Key awards include ACM Fellow (2022), IEEE Fellow (2012), and ERC Starting Grant (2008). He advises numerous PhD students and collaborates with institutions like Google and Microsoft. Labs and teams: Leads the Computer Vision and Geometry (CVG) lab at ETH Zurich and directs the Microsoft Mixed Reality and AI Lab. His work bridges academia and industry, focusing on perception for mixed reality and autonomous systems.

Mihyun Kangمشاهده پروفایل

استاد

• Combinatorics
• Discrete Probability
• Algorithms
• +۳ مورد دیگر

Mihyun Kang is a Professor in the Institute of Discrete Mathematics at Graz University of Technology (TU Graz), leading the Combinatorics Group. She holds significant academic positions and has been recognized with a Heisenberg Fellowship (German Research Foundation) and a Friedrich Wilhelm Bessel Research Award (Alexander von Humboldt Foundation). Her research focuses on combinatorics, discrete probability, and algorithms, with a specialization in random graph theory. She contributes to editorial boards, including Random Structures & Algorithms . Her research interests emphasize high-dimensional graphs, percolation processes, and structural properties of random graphs. She explores topics such as phase transitions, graph enumeration, and algorithmic applications in combinatorial problems. Her work bridges theoretical foundations with practical applications in algorithm design and probabilistic modeling. Dr. Kang’s scientific achievements include pioneering studies on hypergraphs, bootstrap percolation, and the evolution of random graph processes. Her recent publications highlight advancements in understanding graph components, connectivity thresholds, and universality phenomena in random structures. She collaborates widely, contributing to conferences and international initiatives like the SFB “Discrete random structures: enumeration and scaling limits.” Her professional activities include advising doctoral students and supervising research projects at TU Graz. She leads the Combinatorics Group, which hosts the Graz Combinatorics Seminar and actively engages in academic outreach. Her contributions extend to textbook authorship, including Diskrete Mathematik für die Informatik , and she maintains an active presence in discrete mathematics education and research.

Ivan Violaمشاهده پروفایل

دانشیار

• Visualization
• Computer Graphics
• Biological Visualization
• +۳ مورد دیگر

Ivan Viola is an Associate Professor at the Institute of Computer Graphics and Algorithms, part of the Faculty of Informatics at TU Wien, Austria. He holds a leave of absence until December 2024 while also being affiliated with King Abdullah University of Science and Technology (KAUST) as an Associate Professor funded by the Vienna Research Groups program. His research focuses on visualization techniques in medicine, biological sciences, and earth sciences, with a specialty in illustrative visualization and DNA-nanotechnology applications. Viola has contributed over 100 scientific works and serves as a reviewer and panelist for major conferences in computer graphics and visualization. Education: M.Sc. (2002) and Ph.D. (2005) in Computer Graphics from TU Wien. Postdoctoral research at the University of Bergen (2006-2011), where he became Full Professor before returning to TU Wien. Research Interests: Whole-cell visualization Molecular modeling Interactive 3D environments Biomedical visualization Data-driven colormap techniques Awards: IEEE VIS 2017 Best Paper Honorable Mention, 'Best Overall Concept' for CellView, and multiple visualization awards. Active in EuroVis and IEEE VIS organizing roles. Grants & Supervision: Leads the Visualization Group at TU Wien, supervising student projects and master’s theses. Involved in grants like the Vienna Research Groups program. Labs/Teams: Visualization Group at TU Wien, collaborating on projects like CellView and Molecumentary.

• Automating Software Engineering Tasks
• Mining Software Repositories
• Program Analysis
• +۹ مورد دیگر

Univ.-Prof. Martin Pinzger is a Professor at the Department of Informatics Systems, Alpen-Adria-Universität Klagenfurt. He serves as Head of Department and Member of the Senate, actively contributing to academic governance. Research Focus: Automating Software Engineering Tasks, Mining Software Repositories, Program Analysis, Software Evolution and Visualization Recent Work: Developing tools for API evolution analysis, cybersecurity AI (CAI), robotics benchmarking (RobotPerf), and dependency validation His research combines empirical studies with tool development for software maintenance and security. Current projects address challenges in REST API breaking changes, cloud security certifications, and robotic system performance evaluation. Publications since 2023 demonstrate continued engagement with topics spanning AI-driven code segmentation, microservice API evolution, and cybersecurity tool development. Key trends include cross-disciplinary applications of NLP to software engineering and security-focused tool creation. Contact: martin.pinzger@aau.at

Xu Dongمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Multimedia
• +۳ مورد دیگر

Professor Dong Xu is a Tenured Professor in the Department of Computer Science at the University of Hong Kong (HKU), part of the School of Computing and Data Science. He holds a B.Eng. and Ph.D. from the University of Science and Technology of China (USTC). His career includes tenured roles at Nanyang Technological University and the University of Sydney, alongside postdoctoral research at Columbia University. His research focuses on Artificial Intelligence, Computer Vision, Multimedia, and Machine Learning , with applications in autonomous driving, AR/VR, medical image analysis, and video surveillance. Xu has authored over 150 papers in top journals and conferences, including CVPR, ICCV, and IEEE Transactions. He actively contributes to the academic community as an editorial board member for journals like ACM Computing Surveys and IEEE Transactions, and through leadership roles in conferences such as ACM Multimedia and ICME. Notable awards include Fellowships from IEEE and IAPR, and the IEEE Signal Processing Society Distinguished Lecturer title (2021–2022). Education: B.Eng. (USTC, 2001), Ph.D. (USTC, 2005) Professional Service: Program Coordinator of ACM Multimedia 2024, Guest Editor of over ten special issues.

Ammar Mostafaمشاهده پروفایل

استاد

• Computer Network Architectures
• Mobile Cloud Computing
• Overlay Networks
• +۷ مورد دیگر

Mostafa Ammar is a Regents' Professor and Interim Chair of the School of Computer Science at the Georgia Institute of Technology. He has held leadership roles including Associate Chair (2006–2012) and has been a faculty member since 1985. His research focuses on network architectures, protocols, and services, with contributions to mobile cloud computing, network virtualization, and disruption-tolerant networks. He has advised 39 Ph.D. students and secured funding from agencies like NSF, DARPA, and industry partners such as Cisco and IBM. Education : S.B. and S.M. from MIT, Ph.D. from the University of Waterloo. Research Interests : Network architectures, mobile cloud computing, overlay networks, video streaming, and network simulation. His work bridges theoretical advancements with practical implementations, emphasizing scalable and efficient network solutions. Publications : Over 214 publications with a focus on network virtualization, mobile edge computing, and distributed systems. Recent work explores encrypted traffic analysis and femto-cloud resource sharing. Awards : ACM/IEEE Fellowships (2002–2003), Best Paper Awards (2012, 2018), and multiple teaching excellence recognitions. Service : Editor-in-Chief of IEEE/ACM Transactions on Networking (1999–2003), conference co-chair roles, and steering committee memberships. Advising & Grants : Mentored 39 Ph.D. students and secured multi-million-dollar grants. His research has influenced industry standards and academic curricula. Labs/Teams : Active in Georgia Tech’s networking research groups, contributing to open-source network simulators and collaborative projects with global institutions.

• Data Mining
• Machine Learning
• Clustering Algorithms
• +۳ مورد دیگر

Anna Beer is a researcher in the Faculty of Computer Science, specializing in data mining and machine learning with a focus on density-based clustering, spectral clustering, and interactive clustering frameworks. She holds a BSc and MSc in computer science and maintains an ORCID profile (https://orcid.org/0000-0002-6890-997X) for her research contributions. Research Themes: Development of clustering algorithms (e.g., DISCO, Scar, LUCKe), fairness in density-based clustering (FairDen), and applications to molecular dynamics and climate research (DROPP). Collaborations: Works with colleagues like Ira Assent, Christian Plant, and Lars Krieger, with recent contributions to conferences like ICLR 2025. Activities: Presented research on density-connectivity distance at a 2023 oral contribution. Publications: 9 publications since 2019, including 3 in 2025 and 6 in 2024, covering topics from cluster evaluation to deep active learning strategies.

• Databases
• Artificial Intelligence
• Query Optimization
• +۱ مورد دیگر

Alexander Selzer is a PreDoc Researcher in Databases and Artificial Intelligence at Vienna University of Technology. His research focuses on query optimization, database systems, and AI-driven data processing. His work bridges theoretical computer science and practical database engineering, emphasizing efficient algorithms for modern data challenges. Recent projects explore machine learning applications in query performance and distributed computing frameworks. He mentors students in database optimization research, including projects on structure-guided query techniques and SQL-based system enhancements.

• Neurosymbolic AI
• Answer Set Programming
• Visual Question Answering
• +۳ مورد دیگر

Nelson Nicolas Higuera Ruiz is a PreDoc Researcher at the Vienna University of Technology, affiliated with the Faculty of Informatics' Knowledge-Based Systems research group. His work bridges logic programming and deep learning for explainable AI. Research Focus: Neurosymbolic AI, Visual Question Answering (VQA), Answer Set Programming (ASP), and hybrid reasoning systems Projects: Leads optimization research in the LCS (2017–2025) project, developing neurosymbolic approaches for intelligent systems Key Contributions: Pioneering adaptive large-neighbourhood search algorithms for ASP optimization, modular neurosymbolic architectures, and contrastive explainability frameworks for VQA Collaborations: Active in international workshops and conferences including IJCAI, AAAI, and CLeaR, frequently collaborating with researchers like Thomas Eiter and Johannes Oetsch Publications: Focus on neurosymbolic integration, optimization algorithms, and explainability across AI, logic programming, and computer vision domains

Rafail Ostrovskyمشاهده پروفایل

استاد

• Algorithms
• Cryptography and Computer Security
• Theoretical Computer Science
• +۳ مورد دیگر

Rafail Ostrovsky is a Professor of Computer Science and Mathematics at UCLA , affiliated with the Center for Information and Computation Security at the Henry Samueli School of Engineering and Applied Science. He earned his Ph.D. in Computer Science from MIT in 1992 under Silvio Micali. Research Focus: His work spans cryptography, algorithms, and theoretical computer science, emphasizing secure multi-party computation, zero-knowledge proofs, oblivious RAM, and high-dimensional data analysis. Applications include privacy-preserving data mining, systems security, and quantum cryptography. Article Trends: Recent publications address concurrent security protocols, robust secret sharing via expander graphs, and efficient multi-party computation. Topics intersect computational complexity, cryptographic reductions, and practical security implementations. Awards: Recipient of the 2018 RSA Conference Excellence in Mathematics Award , 2017 IEEE Fellow , and multiple IEEE/ACM honors. Holds 14 U.S. patents and over 290 refereed papers. Advising: Supervised 27 Ph.D. students, many now professors at top institutions. Served on 40+ program committees, including FOCS 2011 Chair. Labs: Leads the CICS research center, fostering interdisciplinary work in information security and cryptographic systems.

Zhang Yi-Chengمشاهده پروفایل

استاد

• Econophysics
• Information economics
• Statistical physics
• +۲ مورد دیگر

Zhang Yi-Cheng is a Full Professor of Theoretical Physics at the University of Fribourg, Switzerland, since 1992. His academic career includes visiting professorships at Nordita (Denmark) and INFN (Italy), and postdoctoral research at Brookhaven National Lab (USA). He specializes in interdisciplinary fields such as Econophysics , Statistical physics , and Complex network sciences , focusing on applications in financial markets, social systems, and global trade networks. His research explores topics like market dynamics, network structures, and algorithmic ranking systems. Notable awards include the 2011 Honorary Director of the Complexity Sciences Research Center and recognition as a 2011 Chinese '1000 Talents' awardee . His work bridges physics-based methodologies with socio-economic systems, addressing challenges in information-driven economies and networked societies. Zhang has contributed to influential studies on ranking algorithms, percolation theory in networks, and the interplay between economic complexity and trade. His interdisciplinary approach has led to advancements in understanding systemic risks, market inefficiencies, and the role of information in shaping global economic interactions.

Kurt Mehlhornمشاهده پروفایل

استاد

• Data Structures
• Graph Algorithms
• Computational Geometry
• +۴ مورد دیگر

Kurt Mehlhorn is a distinguished academic in computer science, affiliated with the Universität des Saarlandes and the Max-Planck-Institut für Informatik . He has served as Professor of Computer Science since 1975 and as Director of the Max Planck Institute since 1990. His work bridges theoretical and applied computer science, with a focus on algorithmic design and implementation. Born : 29 August 1949, Ingolstadt, Germany Education : TU München (1968–1971), Cornell University (1971–1974), PhD in Computer Science (1974) Mehlhorn’s research spans foundational and applied domains, including Data Structures , Graph Algorithms , Computational Geometry , and Software Libraries . His contributions to algorithm engineering and EU-funded projects like ALCOM and GALIA have advanced the field. He co-founded Algorithmic Solutions GmbH in 1995 to commercialize algorithmic tools. Notable scientific awards : Leibniz-Award (1986) Humboldt-Award (1989) ACM Paris Kanellakis Theory and Practice Award (2011) Academia Europaea Erasmus Medal (2014) His editorial leadership includes roles at Algorithmica , SIAM Journal of Computing , and ACM Transactions on Algorithms . He has held advisory positions at institutions like IST Austria , ETH Zürich , and Simons Foundation , while directing research clusters such as the Cluster of Excellence in Multimodal Computing and the Indo Max Planck Center .