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.

Sabine Glasl-Tazreiterمشاهده پروفایل

مدرس

• Phytochemistry
• Biodiscovery
• Ethnomedicinal Plants
• +۴ مورد دیگر

Sabine Glasl-Tazreiter is a Lecturer at the University of Vienna's Faculty of Life Sciences , specifically within the Department of Pharmaceutical Sciences and its Division of Pharmacognosy . Her office is located in room 2E 412 on the 4th floor at Josef-Holaubek-Platz 2, Vienna, Austria (1090). Contact details include telephone number +43-1-4277-55207 and email sabine.glasl@univie.ac.at . Principal research focus: Phytochemistry & Biodiscovery Specialization: Secondary metabolites from ethnomedicinally used plants across Europe, Mongolia, and Latin America Key techniques: Isolation of bioactive compounds, structural elucidation, pharmacological evaluation Quality control expertise: Macroscopic/microscopic identification, chemical analytics Recent publications highlight her work in: 2024 - Development of the VOLKSMED Database for Austrian folk medicine wound healing plants 2025 - Advanced mucociliary clearance research in respiratory systems 2023 - Innovations in optoacoustic imaging technology 2019 - Structure-function analysis of phycobiliproteins for medical imaging 2017 - Phytochemical characterization of Latin American antidiabetic plants

Nikolaus Hautschمشاهده پروفایل

استاد

• Econometrics
• Finance
• Market Microstructure
• +۳ مورد دیگر

Nikolaus Hautsch is a full Professor at the Faculty of Economics, Institute of Statistics and Operations Research. His work focuses on econometrics, finance, and high-frequency data analysis. Research Interests : Market microstructure, volatility modeling, transaction costs, systemic risk, and machine learning applications in finance. Publication Trends (2025–2018): 2025: High-dimensional portfolio optimization, dynamic systemic risk 2024: Blockchain asset arbitrage, DeFi, polarization metrics, jump detection 2023–2022: Microstructural noise, volatility forecasting, neural networks Scientific Awards : Fellow of the Society for Financial Econometrics (2014) Projects : Artificial Intelligence in Rowing (2022–2025) Vienna Graduate School of Finance (2018–2022) Risk management of CCPs

Efstathia Buraمشاهده پروفایل

استاد

• Dimension Reduction in Regression
• High-Dimensional Statistics
• Multivariate Analysis
• +۵ مورد دیگر

Efstathia Bura is a Professor heading the Applied Statistics Research Unit (ASTAT) within the Institute of Statistics and Mathematical Methods in Economics at TU Wien's Faculty of Mathematics and Geoinformation. Her research focuses on dimension reduction techniques in regression and classification, high-dimensional statistics, and their applications in biostatistics, econometrics, and legal statistics. She leads projects like ProbInG (WWTF-funded) and the SecInt Doctoral College on statistical verification of cyber-physical systems. Her work integrates advanced statistical methodologies with interdisciplinary applications, emphasizing practical solutions for complex data challenges. Current projects explore probabilistic program analysis, security properties in cyber-physical systems, and dynamic econometric modeling. She collaborates internationally, with notable contributions to statistical theory and applications in law, healthcare, and telecommunications. Key research themes include time-varying regression models, sufficient dimension reduction for mixed predictors, and fusion of statistical methods with machine learning. Her publications bridge theoretical advancements and real-world problem-solving, reflecting her role as a leading academic in modern applied statistics. Her team includes postdocs and assistants working on WWTF and SecInt grants, focusing on probabilistic systems and statistical verification. While no formal student advisees are listed, her collaborative projects engage junior researchers in cutting-edge statistical research.

Rafał Weronمشاهده پروفایل

استاد

• Forecasting
• Agent-based modeling
• Computational economics
• +۴ مورد دیگر

Rafał Weron is a Full Professor at Wrocław University of Science and Technology, where he has held leadership roles since 2015, including Head of the Department of Operations Research and Business Intelligence and Chairman of the Scientific Discipline Council for Management and Quality Sciences. His expertise spans electricity price forecasting, computational economics, and risk management, with significant contributions to probabilistic forecasting methods. As a globally recognized scholar, he has received prestigious awards such as the Hugo Steinhaus Prize (2018) and the Tao Hong Award (2017). Key Affiliations : Wrocław University of Science and Technology; Polish Academy of Sciences (Statistics and Econometrics Committee); Polish Mathematical Society. Research Trends: Weron's work focuses on electricity price forecasting, leveraging machine learning and statistical models to enhance accuracy and reliability. His publications emphasize probabilistic forecasting frameworks, quantile regression, and hybrid modeling techniques, reflecting a commitment to methodological rigor and practical applications in energy markets. Scientific Awards: Top 1% globally ranked economist (IDEAS/RePEc, 2013-2022) World's Top 2% Most Widely Cited Scientist (2019-2021) 'Hugo Steinhaus' Prize (2018) Tao Hong Award (2017) Emerald Citation of Excellence (2017) Minister of Science & Higher Education Prize (2016) Commission of National Education Medal (2016)

• Dependable computing
• Networking algorithms
• Cloud computing
• +۳ مورد دیگر

Alex X. Liu is a Professor in the Department of Computer Science & Engineering at Michigan State University (2016-2022), currently serving as Chief Information Security Officer and President of Midea Software Engineering Institute. His academic career includes roles as Associate Professor (2012-2016) and Assistant Professor (2006-2012) at the same institution. He holds a Ph.D. and M.S. in Computer Science from The University of Texas at Austin, and a B.S. in Computer Science from Jilin University, China. Education Ph.D. in Computer Science (UT Austin, 2006) M.S. in Computer Science (UT Austin, 2002) B.S. in Computer Science (Jilin University, 1996) Liu's research focuses on Dependable computing , Networking algorithms , Cloud computing , Mobile computing , Privacy computing , and Computer/network security . His work spans secure systems, network protocols, and resource optimization in distributed environments. Recent publications address quantum neural networks , microservices autoscaling , RFID tag recognition , network traffic classification , and hybrid physical-layer authentication , demonstrating expertise at the intersection of AI and network security. Key trends include deep learning applications for cloud systems and robust security protocols. Scientific Awards IET Fellow (2021) IEEE Fellow (2019) ACM Distinguished Scientist (2019) Withrow Distinguished Scholar Awards (Senior 2019, Junior 2011) NSF CAREER Award (2009) IEEE & IFIP William C. Carter Award (2004)

• Bayesian Statistics
• Cluster Analysis
• Data Science
• +۵ مورد دیگر

Bettina Grün is an Associate Professor and Deputy Head of the Institute for Statistics and Mathematics at Vienna University of Economics and Business (WU). Her research focuses on Bayesian mixture models, cluster analysis, and applying statistical methods to sustainability, tourism, and environmental studies. She has led multiple research projects, including studies on environmental behavior in tourism and advanced text modeling in economics. Grün holds a PhD in Technical Mathematics from TU Wien (2006) and a Habilitation in Statistics from Johannes Kepler University Linz (2012). She has authored over 150 publications in top journals like Journal of Environmental Management and Expert Systems with Applications . Her work emphasizes practical applications, such as reducing hotel waste through behavioral interventions and developing R packages like movMF and circlus for statistical clustering. Grün has received awards including the AIEST Best Contribution Award (2019) and the MRS Silver Medal (2016). Grün teaches courses on statistical modeling and leads projects like Analysis of Central Bank Communication (2022–2026) and Environmentally Friendly Behavior in Tourism (2019–2024).

• Analytical Chemistry
• Elemental and Isotopic Analysis
• Inductively Coupled Plasma Mass Spectrometry (ICP-MS)
• +۷ مورد دیگر

Anastassiya Tchaikovsky is a postdoctoral researcher at the Institute of Analytical Chemistry, Department of Natural Sciences and Sustainable Resources, University of Natural Resources and Life Sciences, Vienna (BOKU). She holds a PhD in analytical chemistry and has an extensive research background in elemental and isotopic analysis, particularly using ICP-MS techniques. Her work spans food authentication, environmental forensics, and trace metal speciation. Her research interests include: Inductively Coupled Plasma Mass Spectrometry (ICP-MS) Chemometrics and multivariate data analysis Isotopic and elemental fingerprinting for provenance determination Metrology and method validation Separation techniques coupled to mass spectrometry Applications in food science, ecology, and human health Her recent publications demonstrate a strong trend toward interdisciplinary applications of analytical chemistry, particularly in verifying the geographical origin of food products (e.g., carrots, caviar, fish) using combined isotopic, elemental, and metabolomic fingerprints. She frequently employs chemometric modeling and data fusion techniques to enhance discrimination power. Her work also extends to biomedical applications, such as iron metabolism in neurodegenerative diseases and lead detoxification. She has received multiple scientific awards, including: Scholarship for a postdoc mentoring program (2019) Best talk award at DocDay, Tulln (2014) ESF-Studienabschluss scholarship (2013) Merkur scholarship from TU Vienna (2013) Best student lecture award at ICPMS Anwendertreffen (2012) Science scholarship from TU Vienna (2012) She has been involved in several research projects funded by the European Commission, Austrian federal and local governments, and private institutions. Her collaborative work includes advising on fish migration, caviar traceability, and citizen science initiatives like IsoPROTECT. She actively presents her research at international conferences and contributes to knowledge transfer in food safety and analytical methodology. She is affiliated with the Institute of Analytical Chemistry at BOKU and has no listed advisees, though she collaborates extensively with senior researchers and interdisciplinary teams.

• Optimal Transport
• Martingale Theory
• Mathematical Finance
• +۳ مورد دیگر

Mathias Beiglböck is a full Professor at the Department of Mathematics within the Faculty of Mathematics at the University of Vienna. His research spans multiple areas of mathematical analysis with a strong focus on probability theory and its applications to finance and other fields. With over 60 publications spanning from 2009 to 2024, Beiglböck has established himself as a leading researcher in his field. Beiglböck's primary research interests center around optimal transport theory, martingale theory, and their applications to mathematical finance. His work explores the deep connections between probability theory and financial mathematics, particularly in areas such as option pricing, risk management, and stochastic processes. His research also extends to epidemiological modeling, as evidenced by his contributions to SARS-CoV-2 research during the pandemic. Analysis of his recent publications (2022-2024) reveals a strong focus on advancing the theoretical foundations of optimal transport and martingale theory while finding novel applications in finance and data science. His work often bridges pure mathematical theory with practical applications, particularly in financial modeling and risk assessment. The high citation counts across his publications (some exceeding 100 citations) indicate significant impact in his field. Beiglböck has collaborated extensively with researchers across Europe, particularly with scholars from France, Austria, and the UK. His work on the COVID-19 pandemic demonstrates his ability to apply mathematical expertise to pressing real-world problems, contributing to public health policy through rigorous quantitative analysis.

• Control Engineering
• Automation
• Model Predictive Control
• +۵ مورد دیگر

Martin Steinberger is an Associate Professor at the Institute of Control and Automation (IRT) at Graz University of Technology (TU Graz). His work focuses on advanced control systems, networked control, model predictive control (MPC), and automation in manufacturing and autonomous systems. He leads research into real-time optimization, fault diagnosis, and safety-critical applications in industries like pharmaceuticals and automotive. Research interests include: Networked Control Systems Model-Based Control Autonomous Vehicle Trajectory Planning Process Automation Robotics and Industrial Automation His work bridges theoretical control engineering with practical applications in manufacturing lines, chemical processes, and autonomous driving. Recent studies emphasize digital real-time release testing for pharmaceuticals, universal control concepts for manufacturing systems, and safety-aware trajectory optimization for automated vehicles. His publications frequently address challenges in time-varying delays, packet loss mitigation, and robust observer design for nonlinear systems. Steinberger collaborates on EU-funded projects and regularly contributes to conferences like the International Workshop on Variable Structure Systems. His research often involves experimental validation, as seen in work with compact pharmaceutical manufacturing setups and small-scale autonomous vehicle testing platforms.

• Probability Theory
• Financial Mathematics
• Stochastic Processes

Paul Eisenberg is an Assistant Professor at the Institute for Statistics and Mathematics at Vienna University of Economics and Business. He holds a doctorate in Mathematics and has held positions at the University of Liverpool, Vienna University of Technology, and Technical University of Dortmund. His research focuses on probability theory and financial mathematics, particularly stochastic processes, term structure modeling, and applications to financial markets. He teaches courses in Probability, Quantitative Methods, and Business Mathematics. Research outputs concentrate on stochastic processes in finance, including term structure modeling, stochastic optimization, market microstructure, and applications to cryptocurrency markets. Recent work shows emphasis on regime-switching models and high-dimensional stochastic systems.

• Visual Analytics
• Temporal Data Analysis
• Data Cleansing
• +۳ مورد دیگر

Theresia Gschwandtner is a Researcher at TU Wien's Research Division of Visual Analytics (E193-07). Her work focuses on advancing visual analytics methodologies for temporal data, fraud detection, and uncertainty visualization. She leads the Network Lab and contributes to tools like TimeCleanser for data cleansing and NEVA for fraudulent network identification. Her research emphasizes interactive systems for guidance in data analysis, provenance tracking, and enhancing user-centric visualization frameworks. Key research interests include temporal data preprocessing, multivariate time series analysis, and the integration of automated guidance systems into visual analytics platforms. She has collaborated on projects such as Hermes (economic network exploration) and TBSSvis (temporal blind source separation), which combine algorithmic innovation with intuitive user interfaces. Guidance frameworks and user studies are central to her work, exploring how automated support impacts performance and mental state during complex data analysis tasks. She has advised students on theses addressing data quality, cyclical pattern detection, and lighting design visualization. Notable contributions include the Quantifying Uncertainty in Time Series Processing framework and the LightGuider system for interactive lighting design guidance. Her work bridges theoretical advancements with practical applications in healthcare, finance, and engineering domains.

Silvia Mikschمشاهده پروفایل

استاد

• Visual Analytics
• Information Visualization
• Interaction Design
• +۶ مورد دیگر

Silvia Miksch is a Full University Professor of Visual Analytics at TU Wien's Faculty of Informatics, leading the CVAST Center. She holds a PhD from the University of Vienna and has held roles including Head of the Department of Information and Knowledge Engineering at Danube University Krems. Her research focuses on Visual Analytics, Information Visualization, Temporal Data Analysis, and Medical Informatics. She has supervised numerous PhD and Master’s students, with notable advisees including Ignacio Baltazar Pérez Messina and Davide Ceneda. Her work bridges theory and practice, addressing challenges in Visual Analytics for healthcare, business intelligence, and digital humanities. Awards include the IEEE VGTC Technical Achievement Award (2023) and induction into the IEEE Visualization Academy (2020). She actively contributes to conferences like IEEE VIS and EuroVis as program chair and steering committee member. Her projects, such as 'VisuExplore' and 'DisCo', have received recognition for advancing visualization in medical and cultural domains. Key research areas include guidance-enriched systems, network visualization, and temporal reasoning. She explores applications in fraud detection, cultural heritage analysis, and pandemic data visualization. Her lab's tools, like 'Hermes' and 'COVIs', exemplify task-driven design for real-world data challenges.

Michael Fellowsمشاهده پروفایل

استاد

• Parameterized Complexity
• Kernelization
• Multivariate Algorithmics
• +۲ مورد دیگر

Michael Fellows is an Elite Professor of Informatics at the University of Bergen, Norway (2016–present). He has held prominent academic positions at Charles Darwin University, Australia; University of Newcastle, Australia; University of Victoria, Canada; and Victoria University, New Zealand. He is a leading figure in parameterized complexity theory and computer science education. Education : Ph.D. in Computer Science, University of California (1985) M.A. in Mathematics, University of California (1982) Research Interests : Dr. Fellows has pioneered parameterized complexity theory and kernelization algorithms. His work bridges theoretical computer science with interdisciplinary applications in mathematical sciences communication. The Google Scholar articles suggest a secondary focus on sustainability science, life cycle assessment (LCA), and regional energy systems planning. Scientific Awards : 2018 Toppforsk Award (Norwegian Research Council) 2016 Order of Australia, Companion to the Queen (AC) 2014 Honorary Fellow of the Royal Society of New Zealand 2014 Inaugural EATCS Fellow 2014 EATCS–IPEC Nerode Prize 2014 ETH Zurich International Gold Medal of Honor 2007 Alexander von Humboldt Research Prize Advising and Grants : He has supervised notable PhD students including Lars Jaffe (University of Bergen) and Elena Prieto-Rodriguez (Newcastle). Research funding includes U.S. NSF grants, Australian Research Council Discovery Grants, and the 2018 Norwegian Toppforsk Award. His editorial roles span the Journal of Computer and System Sciences and ACM Transactions on Algorithms .

Florian Huberمشاهده پروفایل

استاد

• Bayesian Econometrics
• Macroeconomics
• State Space Modeling
• +۳ مورد دیگر

Florian Huber is a Professor of Economics and Vice-Head of the Department of Economics at the University of Salzburg. His research focuses on Bayesian macroeconometrics, particularly large-scale non-linear multivariate time series modeling. He has published in top journals such as the Journal of Econometrics and the Journal of Applied Econometrics. His work integrates machine learning and nonlinear methods to analyze macroeconomic dynamics and uncertainty. Huber serves as a Scientific Consultant to the Oesterreichische Nationalbank (OeNB), European Central Bank (ECB), and European Commission. He holds roles as Associate Editor of Macroeconomic Dynamics, Senior Scientist at the International Institute for Applied Systems Analysis (IIASA), and Research Fellow of Bocconi University’s Baffi Center. His accolades include the 2024 Kurt-Zopf-Förderpreis and Fellow status in the Society for Economic Measurement. Research interests span Bayesian econometrics, state space modeling, forecasting, and financial spillovers. His recent work addresses topics like growth-at-risk, nonlinear VAR models, and real-time inflation forecasting. Huber’s contributions bridge theoretical econometrics with policy-relevant analysis, emphasizing the integration of big data and structural models.