جستجوی استاد راهنمای دانشگاهی

• Data Visualization
• Human-Computer Interaction
• Big Data Analytics
• +۱۳ مورد دیگر

Huamin Qu is a Chair Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST). He serves as the Founding Dean of the Academy of Interdisciplinary Studies (AIS), Founding Head of the Division of Emerging Interdisciplinary Areas (EMIA), and was the Founding Acting Head of Computational Media and Arts (CMA) at HKUST(GZ). Qu directs the VisLab and coordinates the Human-Computer Interaction (HCI) group. He obtained his BS in Mathematics from Xi'an Jiaotong University and MS/PhD in Computer Science from Stony Brook University. Qu's research integrates Data Visualization , Human-Computer Interaction , and Human-Centered AI , with applications in urban informatics, social networks, and explainable AI. His work focuses on developing interactive systems for big data analytics, visual storytelling, and AI-driven decision support. Research extends to multimodal communication, fintech, and augmented reality applications. His publications emphasize visual analytics for complex datasets (mobility, social media, financial), interaction techniques for immersive environments, and AI-enhanced visualization tools. Recent works explore explainable AI interfaces and large-scale data communication frameworks. IEEE Visualization Academy (2020) IEEE VGTC Technical Achievement Award AI 2000 Most Influential Scholar (2019, 2023, 2024) 21 Best Paper/Honorable Mention awards IBM Faculty Award (2009) APICTA Merit Award (2015) Yelp Dataset Grand Prize (2018) Qu has advised 48 PhD graduates (21 now faculty at institutions like UC Davis, University of Minnesota, Texas A&M) and 30 MPhil students. He secured major grants including RGC theme-based projects (digital citizenship, air pollution), UGC AoE (slope safety), and China's 973 Program. As VisLab director, he leads 20+ researchers in visualization/HCI projects adopted by Microsoft, IBM, Huawei, and Tencent.

Wojciech Rytterمشاهده پروفایل

استاد

• Design and analysis of computer algorithms
• Automata and formal languages
• Parallel algorithms
• +۵ مورد دیگر

Wojciech Rytter is a full professor at the Institute of Informatics, Department of Mathematics and Informatics at the University of Warsaw, Poland, holding this position continuously since October 1971. His academic career includes significant international appointments as full professor at New Jersey Institute of Technology (2002-2004), Liverpool University (1997-2002), and Bonn University (1994-1995), and as visiting professor at University of California, Riverside (1992-1993) and University of Warwick (1985-1986). He earned his MSc in 1971, PhD in 1975, habilitation in 1985, and was awarded the scientific degree of professor in 1997, all from Warsaw University. Professor Rytter's research focuses on the design and analysis of computer algorithms, with particular expertise in automata and formal languages, parallel algorithms, and text algorithms. His work spans efficient sequential and parallel algorithms, automata theory, complexity of recognition and parsing of context-free languages, pattern matching, algorithmics of WWW, parallel combinatorial computing, graph-theoretic algorithms, and algorithmics of highly compressible objects. His theoretical contributions have practical applications in computational biology, bioinformatics, and text processing systems. His recent publications (2022-2025) demonstrate continued activity in string algorithms, particularly in pattern matching, string covers, and combinatorics on words, with a strong focus on theoretical computer science with applications in bioinformatics. 200 problems on automata, languages, computations (Cambridge University Press 2023) 125 Problems in Text Algorithms (Cambridge University Press, 2021) Jewels of Stringology (World Scientific, 2002) Fast parallel algorithms for matching problems in graphs (Oxford University Press 1998) Text algorithms (Oxford University Press 1994) Professor Rytter has collaborated extensively with researchers including Jakub Radoszewski, Tomasz Walen, Tomasz Kociumaka, and Maxime Crochemore. He is a member of the Academy of Europe (elected 2011, Informatics section) and has authored or co-authored more than 130 publications. He maintains an active research laboratory focused on string algorithms and combinatorics on words at the University of Warsaw.

Lam Jamesمشاهده پروفایل

استاد

• Networked control systems
• Vibration control
• Control theory
• +۷ مورد دیگر

Lam James is a Chair Professor of Control Engineering at the University of Hong Kong (HKU), affiliated with the Faculty of Engineering. He holds a BSc (1st Hons.) in Mechanical Engineering from the University of Manchester, and MPhil/PhD degrees from the University of Cambridge. His academic journey includes roles as a Croucher Fellow, Lecturer at the University of Melbourne, and faculty member at City University of Hong Kong before joining HKU in 1993. Professor Lam serves as Editor-in-Chief for four international journals including IET Control Theory and Applications and Journal of The Franklin Institute . His research focuses on networked control systems, vibration control, control theory, and multi-agent systems. With 600+ peer-reviewed publications, he maintains an H-index of 102 (Web of Science) and 108 (Scopus), recognized as a Highly Cited Researcher in multiple fields. Education: BSc Manchester (Mechanical Engineering), MPhil/PhD Cambridge Editorial Roles: 20+ journals, including leadership roles since 2012 His awards include Foreign Membership of Academia Europaea (2024), National Academy of Artificial Intelligence membership (2025), and two State Natural Science Awards (2015, 2019). He is a Fellow of multiple institutions including IEEE, IMechE, and HKIE.

Vladimir Kazeevمشاهده پروفایل

استادیار

• Numerical Analysis
• Tensor Methods
• Partial Differential Equ to the data-driven solution of PDEs
• +۳ مورد دیگر

Vladimir Kazeev is an Assistant Professor at the Faculty of Mathematics, University of Vienna , where he has held a faculty position since 2019. He also held previous academic appointments as a Szegő Assistant Professor at Stanford University (2017–2019), a postdoctoral researcher at the University of Geneva (2015–2017), and research positions at ETH Zurich (2011–2015), Russian Academy of Sciences (2008–2011), and Moscow Institute of Physics and Technology (2009). His research focuses on adaptive, data-driven numerical methods for differential equations, nonlinear low-parametric approximation, and numerical linear algebra. His work intersects computational mathematics, tensor methods, and high-dimensional problem-solving, particularly in the context of partial differential equations (PDEs) and stochastic modeling. The 15 most recent publications reveal a strong emphasis on quantized tensor-structured methods for PDEs, low-rank approximations, and high-dimensional numerical analysis. His research spans theoretical advancements in tensor decomposition, practical applications in chemical reaction networks, and novel discretization techniques for multiscale and degenerate diffusion problems. Scientific awards include the prestigious ETH Medal for outstanding doctoral theses (2016) Russian Academy of Sciences Medal for outstanding student works in mathematics (2011) Advising and teaching activities include supervising Jason Zhu (Stanford, 2019) and Simon Etter (ETH Zurich, 2014), as well as teaching advanced courses in tensor methods, numerical analysis, and PDEs at the University of Vienna, Stanford University, and the University of Geneva. His service to the community includes peer review for 15+ journals and co-organizing minisymposia at SIAM meetings.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Professor Thomas Lukasiewicz is a Full Professor and Head of the Artificial Intelligence Techniques research group at the Faculty of Informatics, Vienna University of Technology (TU Wien). His research focuses on enabling machines to mimic human-like intelligence through techniques spanning deep learning, symbolic reasoning, and predictive coding. Key areas include explainable AI, hybrid neurosymbolic systems, and applications in healthcare and law. He teaches courses such as Deep Learning for Natural Language Processing, Scientific Research and Writing, and multiple seminars in artificial intelligence and knowledge representation. His research projects include Explainable AI in Healthcare (2023–2027) and foundational work on predictive coding networks. His publications (15+ recent articles) address medical image segmentation, neurosymbolic frameworks, and language model evaluation in mathematics. Notable work includes neurosymbolic hybrid models (CCN⁺), reinforcement learning for medical report generation, and theoretical foundations of predictive coding networks.

Borivoje Dakicمشاهده پروفایل

دانشیار

• Quantum Information Theory
• Quantum Foundations
• Quantum Tomography
• +۵ مورد دیگر

Dr. Borivoje Dakic is an Associate Professor at the University of Vienna , affiliated with the Faculty of Physics and the Quantum Optics, Quantum Nanophysics and Quantum Information department. His research spans foundational and applied aspects of quantum theory. Operational reconstruction of quantum formalism Quantum interference as a resource for communication Tomography of large-scale quantum systems Macroscopic quantum phenomena His work includes scalable verification techniques for quantum devices and collaborations with experimental teams like Philip Walther’s and Markus Aspelmeyer’s groups. He received the Marko Jarić Prize (2025) for his contributions. Recent projects focus on diagnostics of quantum devices (FWF BeyondC SFB), information-theoretic foundations of quantum interference (FWF P36994), and local operations in quantum field theory (Cluster of Excellence QuantA). His research on quantum coherence in networks and macroscopic entanglement challenges traditional assumptions about quantum-classical boundaries. Publications emphasize resource-efficient tomography, device-independent verification, and foundational frameworks for quantum statistics and field theory. Teaching: Quantum Information (2025W), Theory in Quantum Optics (2025S), VCQ Summerschool Labs: Dakić Group at University of Vienna

Celso Grebogiمشاهده پروفایل

استاد

• Nonlinear and complex dynamical systems
• Chaos theory
• Fractal geometry
• +۵ مورد دیگر

Professor Celso Grebogi, Sixth Century Chair in Nonlinear & Complex Systems at the University of Aberdeen, is a globally recognized leader in nonlinear dynamics , chaos theory , and systems biology . He founded the Institute for Complex Systems and Mathematical Biology and co-founded the Aberdeen-Lanzhou-Tempe Research Centre. His career spans institutions including University of Maryland, University of São Paulo, and Max-Planck-Society (External Scientific Member since 1998).

Jiang Hongboمشاهده پروفایل

استاد

• Distributed systems
• Mobile computing
• Smart sensing
• +۵ مورد دیگر

Hongbo Jiang is a Distinguished Professor and Vice Dean of the College of Computer Science and Electronic Engineering at Hunan University, China. He holds concurrent roles as Director of the Trusted Systems and Networking Key Laboratory of Hunan Province and Director of the Hunan International Technical Cooperation Base for High-Performance Computing and Distributed Systems. His academic journey includes tenures as a Professor at Huazhong University of Science and Technology and a Hong Kong Scholar Research Fellow at The Chinese University of Hong Kong. Education: PhD in Computer Science (Case Western Reserve University, 2008), B.S./M.S. in Mathematics (Huazhong University of Science and Technology, 2002). Research Interests: Distributed systems, mobile computing, smart sensing, wireless networks, IoT, and edge computing. Ongoing projects include mobile/wireless applications, data science in IoT, and edge computing platforms. His work emphasizes practical implementations such as DriverSonar for driving safety and SmileAuth for biometric authentication. Key Achievements: Elected Member of Academia Europaea (2022), Fellow of AAIA, IET, and BCS. Notable awards include the Wu Wenjun Science and Technology Award (2020) and multiple best paper recognitions. Over 100+ publications in top venues like ACM MobiCom, IEEE/ACM Transactions. Professional Contributions: Editorial roles across 8+ journals including IEEE Transactions on Mobile Computing and ACM Transactions on Sensor Networks. Conference leadership includes co-founding ACM TURC and EAI ICECI. Active in technical committees for INFOCOM, MOBIHOC, and ICDCS. Labs/Teams: Leads research groups focused on networking, IoT, and edge computing. Current openings for PhD/MSc students and PostDoc researchers with strong mathematical and systems backgrounds.

Ljubisa Stankovicمشاهده پروفایل

استاد

• Signal Processing
• Time-Frequency Analysis
• Radar Signal Processing
• +۲ مورد دیگر

Ljubisa Stankovic is a Full Professor at the University of Montenegro with extensive academic and political experience. He has served as Rector of the University of Montenegro (2003-2008), Member of the National Academy of Sciences and Arts (CANU) since 1996, and Ambassador of Montenegro to the United Kingdom since 2010. As an IEEE Fellow (2012), he has made significant contributions to signal processing research. His research focuses on Signal Processing , particularly Time-Frequency Analysis , Data Processing in Joint Time and Frequency Domain , Analysis of Non-Stationary Signals , and Radar Signal Processing . With about 300 technical papers published (83 in leading international journals, mainly IEEE editions) and several textbooks in Signal Processing, his work has substantially influenced the field. The analysis of his recent publications reveals a consistent focus on advanced time-frequency methods applied to radar systems, non-stationary signal analysis, and emerging applications in machine learning and quantum processing. His research shows evolution from theoretical foundations toward practical implementations in communications, radar, and biomedical applications. His notable scientific achievements include: Member of the National Academy of Sciences and Arts (1996) Highest State award of Montenegro '13. jul' (1997) Fellow of the IEEE (2012) Fulbright fellowship (1984-1985) Alexander von Humboldt fellowship (1997) Volkswagen award grant (2001) Scientific Achievement Award by Montenegrin Academy of Science and Art (1991) Stankovic has held significant editorial positions including Associate Editor for IEEE Transactions on Image Processing, IEEE Signal Processing Letters, and IEEE Transactions on Signal Processing since 2003. He was also a member of the IEEE Signal Processing Society's Technical Committee on Theory and Methods (2002-2008). His research group received a Volkswagen Foundation research grant (2001-2003), demonstrating his ability to secure competitive funding. Beyond academia, he has held prominent political positions including Vice-president of Montenegro (1989-1991) and Member of Yugoslav Parliament (1992-1996).

• Financial Mathematics
• Stochastic Processes
• Credit Risk Modeling
• +۳ مورد دیگر

Assoc. Prof. Zehra Eksi-Altay holds a position at the Institute for Statistics and Mathematics at Vienna University of Economics and Business (WU). Her research focuses on financial mathematics, stochastic modeling, and partial information control problems in finance. She has expertise in credit risk modeling, derivatives pricing, and commodity markets. Eksi-Altay has a PhD in Financial Mathematics (2011) and completed her Habilitation in 2017. She has advised one doctoral thesis and has published extensively in top-tier journals like Quantitative Finance and Journal of Computational and Applied Mathematics . Her work bridges theoretical advancements with practical applications in areas such as regime-switching models, optimal portfolio strategies, and liquidity analysis. Education: BSc, MSc (2005), PhD (2011) Habilitation: 2017 Key Research Themes: Partial Information Models, Stochastic Control, Credit Risk, Algorithmic Trading Her recent work explores regime-switching affine term structures, optimal trading strategies under uncertainty, and dark pool liquidity analysis. Eksi-Altay has received one academic prize, though its specific name is not detailed in the provided text. Her contributions span both theoretical developments and applied finance, often collaborating with institutions like WU’s Institute for Statistics and Mathematics.

Mathias Beiglboeckمشاهده پروفایل

استاد

• Optimal Transport
• Martingale Theory
• Mathematical Finance
• +۴ مورد دیگر

Mathias Beiglboeck is a Professor at the Faculty of Mathematics, University of Vienna. His research spans Probability, Optimal Transport, and Mathematical Finance, with a focus on martingale constraints and stochastic modeling. Doctorate in Mathematics (2004, TU Vienna) Diploma in Mathematics (2003, TU Vienna) His work bridges geometric and probabilistic methods in finance, addressing problems like the Skorokhod Embedding, Weak Martingale Transport, and applications to financial institutions. Preprints and publications highlight advancements in Wasserstein distances, causal transport, and stability analysis under martingale constraints. Notable projects and awards include the OeNB-Anniversary-Fund Project (2024-), FWF-Project on Mimicking Processes (2022-), a START-Prize (2014-2022), and early recognition for his Master's thesis (2003). Teaching roles at University of Vienna and TU Vienna cover Stochastic Processes, Financial Mathematics, and Mathematical Finance courses. 2024: OeNB-Anniversary-Fund Project 18983 (250,000 EUR) 2023: Mentor in Daniel Bartl's Esprit-Project (280,000 EUR) 2022: FWF-Project on Mimicking Processes (400,000 EUR) 2014-2022: START-Prize (1,000,000 EUR) 2012: Austrian Mathematical Society Prize 2003: Best Master's Thesis Award, Austrian Mathematical Society His research trends integrate adapted Wasserstein distances, disease modeling, and financial applications, with collaborations across institutions like TU Vienna, Bonn University, and MSRI Berkeley. Grants emphasize geometric and entropic transport methods in finance and public health contexts.

• 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.

Victor Vianuمشاهده پروفایل

استاد

• Computational Logic
• Database Systems
• Database Theory
• +۴ مورد دیگر

Victor Vianu is a Professor of Computer Science and Engineering at the University of California, San Diego and holds the INRIA International Chair at INRIA-Saclay in Paris. He has maintained continuous faculty status at UC San Diego since 1983 while developing extensive international collaborations, particularly with French research institutions including INRIA, ENST-Paris, ENS-Paris, and the University of Paris. His academic credentials include a Ph.D. in Computer Science from the University of Southern California (1983) and undergraduate studies in Mathematics and Informatics at the University of Bucharest (1974-1977). Professor Vianu's research spans computational logic, database systems and theory, and automatic verification. His work uniquely bridges theoretical foundations with practical applications in XML processing, workflow systems, and data-driven applications. He has made seminal contributions to understanding the theoretical underpinnings of database query languages and their expressive power, particularly in the context of XML technologies and workflow systems. His research demonstrates a consistent trajectory from theoretical computer science to practical database systems applications. His publication record reveals significant contributions to database theory spanning over three decades, with particular emphasis on XML technologies, workflow systems, and formal methods for data-driven applications. His work shows a clear evolution from foundational theoretical work to practical applications in business processes and web technologies. INRIA International Chair (2013) Fellow of the American Association for the Advancement of Science (AAAS) (2013) ACM PODS Alberto O. Mendelzon Test-of-Time Award (2010) Fellow of the Association for Computing Machinery (ACM) (2006) Professor Vianu has held significant leadership roles including Editor-in-Chief of the prestigious Journal of the ACM, numerous program committee chair positions for major database conferences (PODS, ICDT, ASIAN), and General Chair for ACM SIGMOD conferences. He has served on the executive committees of SIGMOD (1998-2000) and PODS (1993-2004), and was a member of the ICDT Council (1997-2007), demonstrating sustained influence in the theoretical database community. His extensive invited talks at major conferences including College de France, ACM PODS, and International Conference on Database Theory highlight his international recognition.

• Probability Theory
• Statistical Mechanics
• Random Walks
• +۳ مورد دیگر

Dr. Quirin Thomas Simon Vogel is a Senior Lecturer at the Department of Statistics, University of Klagenfurt. He previously held postdoctoral positions at the Technical University of Munich, New York University Shanghai, and served as an Interim Professor at Ludwig-Maximilians University of Munich. His research bridges probability theory with statistical mechanics and algorithmic applications. Current role: Senior Lecturer (2025) Previous roles: Postdoc (TUM, NYU Shanghai), Interim Professor (LMU Munich) His research focuses on: Random walks and their geometric/stochastic properties Randomized algorithms with applications in statistical models Quantum-inspired probabilistic systems (e.g. interacting bosonic loop soups) Large deviation theory for complex systems Percolation and phase transitions in particle models The articles reflect trends in probability theory, mathematical physics, and algorithmic applications. Key topics include high-dimensional percolation, Bose gas models, neural network theory, and stochastic geometry. The work combines rigorous mathematical analysis with interdisciplinary applications in physics and computer science. Scientific awards and functions cannot be determined from the provided data, as they describe other researchers. The department's research activities include projects on statistical learning, quantum models, and algorithmic probability, though Vogel's direct involvement in these specific funded projects isn't explicitly stated.

Xu Zeshuiمشاهده پروفایل

استاد

• Information Fusion
• Decision Making
• Cluster Analysis
• +۳ مورد دیگر

Zeshui Xu is a Full Professor at the Business School of Sichuan University, China, with concurrent roles as Adjunct Professor at multiple prestigious institutions including Nanjing University of Aeronautics and Astronautics and Southeast University. He has held distinguished positions such as Chair Professor at PLA University of Science and Technology and was part of the Cheung Kong Scholars Program. His research focuses on decision-making theory, information fusion, clustering algorithms, and fuzzy systems. He is a highly cited researcher (2014–2021) and holds fellowships from IEEE, RSA, IFSA, and others. Education: M.Sc. in Operations Research and Cybernetics, Qufu Normal University Ph.D. in Management Science, Southeast University Research Contributions: Dr. Xu has authored 18 Springer monographs and 700+ SSCI/SCI papers, achieving over 73,000 citations with an h-index of 138. His work includes groundbreaking contributions to intuitionistic fuzzy aggregation operators, hesitant fuzzy systems, and probabilistic linguistic decision-making frameworks. Awards & Recognition: Member of EASA and IASCYS Fellowships: IEEE, RSA, ORS, AAIA, and others Natural Science Awards (Ministry of Education) State Council Expert with Special Allowance Editorial Roles: Associate Editor/Editorial Board Member for over 30 journals, including IEEE Transactions on Cybernetics and Fuzzy Systems. Invited to 50+ academic conferences.