جستجوی استاد راهنمای دانشگاهی

• Financial Enterprise Management
• Enterprise Risk Management
• IT-based Enterprise Management
• +۳ مورد دیگر

Prof. Walter Schwaiger is a Full Professor at TU Wien’s Faculty of Mechanical and Industrial Engineering, leading the Institute of Management Science. His academic roles include serving as Head of the Faculty Council since 2010 and holding various curriculum committee positions. He teaches critical courses such as Financial Management, Enterprise Risk Management, and IT-based Management across bachelor’s and master’s programs. His research focuses on three core areas: Financial Enterprise Management (stochastic NPV modeling for renewable energy investments), Enterprise Risk Management (risk maturity assessments via ERMMA studies), and IT-based Management (ontology-driven accounting frameworks like OntoREA). Recent work includes predictive analytics applications in credit risk scoring and pandemic-driven default prediction studies. Prof. Schwaiger has authored influential textbooks like IFRS-Finanzmanagement series and pioneered the REA-based ERP-Control system. He actively contributes to management control research, publishing in venues like Controlling and WingBusiness , and collaborates with institutions like Funk Stiftung on large-scale ERM maturity studies. His professional service includes leading faculty strategy groups and quality management initiatives at TU Wien, reflecting his commitment to institutional governance and academic excellence.

Christa Cuchieroمشاهده پروفایل

استاد

• Mathematical Finance
• Stochastic Processes
• Risk Management
• +۶ مورد دیگر

Christa Cuchiero is a Professor at the Department of Statistics and Operations Research , University of Vienna , and an elected member of the Austrian Young Academy (Junge Akademie) since 2020. Her research bridges rigorous mathematics and cutting-edge applications in finance, machine learning, and stochastic analysis. Education: Christa earned her M.Sc. in 2006 from TU Wien with a thesis on affine interest-rate models, her Ph.D. in 2011 from ETH Zürich on affine and polynomial processes, and completed her Habilitation at the University of Vienna in 2018 on high-dimensional finance beyond classical paradigms. Research Interests: Her work centers on affine and polynomial processes , stochastic portfolio theory , signature methods , and infinite-dimensional stochastic analysis . Recent projects explore signature-based neural SDEs for option calibration, measure-valued diffusions for energy markets, and universal approximation properties of signature transforms. Awards & Recognition: Among her accolades are the FWF START Award 2019 , the Bruti-Liberati Visiting Fellowship 2018 , the ETH Medal 2012 for an outstanding Ph.D. dissertation, and the Prix de l’Institut Europlace de Finance 2017 for the best paper in finance. Contact: christa.cuchiero@univie.ac.at , Kolingasse 14-16, 05.47, 1090 Wien, Austria.

Anja Feldmannمشاهده پروفایل

استاد

• Internet Measurement
• Network Performance Debugging
• Software-Defined Networking
• +۷ مورد دیگر

Anja Feldmann is Director at the Max Planck Institute for Informatics in Saarbrücken and Professor of Internet Network Architectures at Technische Universität Berlin (since 2006). Previously she held a full professorship at Technische Universität München (2002–2006) and conducted research at AT&T Labs Research , Saarland University , and Carnegie Mellon University , where she earned her Ph.D. in 1995. Education Ph.D. in Computer Science, Carnegie Mellon University, 1995 M.Sc. in Computer Science, Carnegie Mellon University, 1991 Diplom in Computer Science, Universität Paderborn, 1990 Research Interests Anja Feldmann’s research centers on measurement-driven understanding of the Internet. She tackles challenges such as software-defined networking , cloud-network interactions , performance debugging , and traffic characterization . A growing focus is the privacy and security of networked systems, evidenced by recent studies on online tracking, DNS security, and disinformation ecosystems. Her group designs scalable measurement platforms that combine passive and active monitoring , programmable data planes , and machine-learning analytics to dissect phenomena ranging from terabit-scale traffic to covert tracking on illegal streaming sites. Recent Publication Themes The 2021-2025 publications reveal a methodological evolution toward large-scale, longitudinal measurement . Topics include: Impact of global events (COVID-19, CrowdStrike outage) on Internet traffic Cross-country tracking ecosystems and privacy leaks DNS root and routing plane stability and security ML-driven real-time monitoring at terabit speeds Disinformation campaigns on encrypted messaging platforms Scientific Awards Gottfried Wilhelm Leibniz Prize (2011) – Germany’s highest research honor Berliner Wissenschaftspreis (2011) Elected Member of the German National Academy of Sciences Leopoldina (2009) Advising & Grants While individual student names are not listed, Prof. Feldmann leads a vibrant team at MPI-INF’s Internet Architecture department. She has supervised numerous doctoral candidates and post-doctoral researchers whose work is reflected in the co-authored papers. Funding sources include the German Research Foundation (DFG) via the Leibniz Prize and EU Horizon projects, although explicit grant numbers are not provided in the source material. Labs & Teams She heads the Internet Architecture department at MPI-INF, located at the Saarland Informatics Campus . The department operates state-of-the-art measurement infrastructure—including programmable switches, honeynets, and global vantage points—to support empirical network science.

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.

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.

Georgios B. Giannakisمشاهده پروفایل

استاد

• Data Science
• Power Systems
• Network Science
• +۷ مورد دیگر

Georgios B. Giannakis is a Full Professor, Endowed Chair, and Presidential Chair in the Department of Electrical and Computer Engineering at the University of Minnesota since 1999. He directs the Digital Technology Center and has held academic roles at the University of Virginia (1987-1999) and USC (1982-1986). His research spans Data Science, Wireless Communications, Network Science, and Statistical Signal Processing , with applications to IoT and power systems. Diploma in Electrical Engineering, NTUA (1981) MSc in Electrical Engineering, USC (1983) MSc in Mathematics, USC (1986) PhD in Electrical Engineering, USC (1986) His publications (470+ journals, 770+ conferences, 34 patents) focus on fading channel modeling, UWB localization, blind signal estimation, and cross-layer wireless design . Articles emphasize multicarrier systems, time-varying channels, and ultra-wideband communication , with citations exceeding 76,000 (H-index 145). Scientific Awards : EURASIP 'Athanasios Papoulis' Society Award (2020) IEEE Fourier Technical Field Award (2015) Gugliermo Marconi Prize Paper Award (2003) 9 Best Journal Paper Awards (IEEE/SPS & ComSoc) IEEE SPS Technical Achievement Award (2001) He has mentored over 50 PhD students and 25 postdocs, served IEEE as Distinguished Lecturer, and contributed to Greek university accreditation panels. His work bridges theoretical signal processing and practical communication systems .

• Optimization and optimal control
• Inverse problems
• Mathematical imaging
• +۵ مورد دیگر

Karl Kunisch is a Professor at the Department of Mathematics and Scientific Computing at the University of Graz and serves as Scientific Director of the Radon Institute of the Austrian Academy of Sciences in Linz. With a distinguished career spanning several decades, he has established himself as a leading researcher in optimization and control theory. Prof. Kunisch completed his PhD and Habilitation at the Technical University of Graz in 1978 and 1980, respectively. His academic journey includes significant positions at Brown University's Lefschetz Center for Dynamical Systems, INRIA Rocquencourt, Universite Paris Dauphine, and he previously served as a professor of numerical mathematics at the Technical University of Berlin. Research Interests: Prof. Kunisch's research focuses on optimization and optimal control, inverse problems and mathematical imaging, numerical analysis and applications, with current emphasis on life sciences applications. His specific areas include Optimal Control of Partial Differential Equations, Nonsmooth Optimization in Function Spaces, and Applications of Optimization and Control in the Life Sciences. His work bridges theoretical mathematics with practical applications across various scientific domains. His recent publications demonstrate a continued focus on advancing the theoretical foundations of optimal control while developing practical numerical methods. Key trends include work on infinite horizon control problems, feedback stabilization techniques, applications to PDE-constrained optimization, and the integration of machine learning approaches with traditional control theory. His research group actively explores connections between theoretical developments and applications in the life sciences. Scientific Recognition: W.T. and Idalia Reid Prize 2021 SIAM Fellow (2017) European Research Council Advanced Grant (2015) Alwin Walther Medaille (2008) SIAM Outstanding Paper Prize (2006) Prof. Kunisch has made substantial contributions to the mathematical community through his editorial work, serving as editor for prestigious journals including SIAM Journal on Control and Optimization, SIAM Journal on Numerical Analysis, and the Journal of the European Mathematical Society. He leads the Research Group on Optimization and Optimal Control at the Johann Radon Institute for Computational and Applied Mathematics (RICAM) and is involved in the ERC-Project OCLOC "From Open to Closed Loop Control".

• Machine Learning
• Statistical Computing
• Cluster Analysis
• +۲ مورد دیگر

Theresa Scharl-Hirsch is a Senior Scientist and Deputy Scientific Director at the Core Facility Bioinformatics, University of Natural Resources and Life Sciences, Vienna (BOKU). She holds concurrent appointments at the Institute of Statistics, BOKU, and has extensive experience in bioprocess modeling, machine learning, and statistical computing. Her work bridges biochemical engineering with advanced data science methodologies. Her research focuses on real-time monitoring of biopharmaceutical processes, clustering of high-dimensional data (particularly RNA sequencing), and application of explainable machine learning techniques. She has developed statistical models for process optimization and quality prediction in antibody capture and protein purification, with a strong emphasis on industrial implementations using R programming. Key trends in her publications include three-way data analysis, matrix-variate Gaussian mixture models, and permutation-based variable importance methods for deep learning architectures. Her work spans bioprocess engineering, bioinformatics, and industrial data science applications.

• Business Education
• Vocational Training
• Didactics of Business Informatics
• +۳ مورد دیگر

Dr. Franz-Karl Skala is a Senior Lecturer at the Vienna University of Economics and Business (WU) in the Business Education department, with over 15 years of academic and professional experience in higher education. He has held teaching and research positions at institutions including the University of Graz, University of Applied Sciences Burgenland, and Fachhochschule Wiener Neustadt. Current Senior Lecturer at WU (since 2012) Teaching focus on programming didactics and e-learning Specializes in business informatics didactics and vocational training Research interests center on curriculum development for hybrid education models, digital transformation in business training, and vocational education reform. His recent FLUENT project (2022-2025) develops flexible universal education models for AI-era learning. He has secured multiple Erasmus+ grants for international education initiatives in Central Asia. Scientific awards include four Vienna University of Economics and Business Innovative Teaching Awards (2020, 2019, 2017, 2010), University of Graz teaching excellence recognition (2020), AK Science Prize (2013), and Leopold-Kunschak Science Prize (2013). Developed modular curriculum frameworks Created e-learning platforms for entrepreneurs Conducted comparative studies on vocational vs academic degrees

Sara Merino Aceitunoمشاهده پروفایل

استاد

• Kinetic Theory
• Partial Differential Equations
• Mathematical Biology
• +۵ مورد دیگر

Prof. Sara Merino Aceituno is a Professor at the Faculty of Mathematics, University of Vienna, leading research in kinetic theory and its applications to biology, medicine, and social sciences. She holds roles as Vice-Dean of the Faculty and Head of the Institute of Mathematics. Her work bridges mathematical models with experimental data, focusing on emergent phenomena in collective dynamics, opinion formation, and cell behavior. She teaches advanced courses on kinetic theory, biomathematics, and mathematical strategies for learning. Her contributions include modeling cell delamination, nematic alignment, and swarm dynamics through PDEs and probabilistic methods. Collaborations with experimentalists drive her interdisciplinary research. She actively engages in education, advising, and public outreach, including a video series explaining mathematical patterns in nature. Her research emphasizes understanding macroscopic patterns arising from microscopic interactions in complex systems. Education: Holds a PhD in Mathematics, with expertise in kinetic theory and applied partial differential equations. Teaching and leadership roles reflect her commitment to academic excellence and student support. Her work integrates experimental and computational models to study clonal dynamics in tissues and mechanical constraints in epithelial layers. She has authored over 20 papers on topics ranging from active matter to opinion formation networks, contributing to both theoretical advancements and practical applications in biology and social sciences. Research focuses on deriving hydrodynamic and continuum models from particle systems, analyzing stability and bifurcations in collective behavior. Grants and collaborations include the Vienna Biocenter PhD Program and experimental groups in cell biology. Her lab explores how environmental factors influence particle swarms and how mechanical forces shape cell cycles in pseudostratified epithelia.

Jean Ponceمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Robotics
• +۳ مورد دیگر

Jean Ponce is a Professor of Computer Science at Ecole Normale Superieure (ENS) in Paris and a Part-Time Global Distinguished Professor at New York University's Courant Institute of Mathematical Sciences and Center for Data Science (CDS). He previously served as Director of the ENS Computer Science Department (2011-2017) and held positions at Inria (2017-2022), University of Illinois at Urbana-Champaign (1998-2006), MIT, Stanford, and Inria (1982-1985). Academic Leadership: Scientific Director of PRAIRIE Interdisciplinary AI Research Institute in Paris Startup Involvement: Co-founder and CEO of Enhance Lab (2022) Editorial Roles: Senior Editor-in-Chief of International Journal of Computer Vision (2019-2022) Conference Leadership: Chair of IEEE CVPR (1997,2000), ECCV (2008), and upcoming ICCV (2023) Research Focus: Computer vision, machine learning, robotics, and AI with applications in exoplanet imaging, 3D reconstruction, and image quality assessment. His work bridges statistical learning and deep learning approaches. Awards: IEEE Fellow (2003) ELLIS Fellow (2019) ERC Advanced Grant (2011) IEEE CVPR Longuet-Higgins Prizes (2016,2020) ICML Test-of-Time Award (2019) Patents & Publications: Co-author of influential textbook Computer Vision: A Modern Approach (translated into Chinese, Japanese, Russian). Holds two US patents and one pending French patent. Google Scholar h-index of 78 with over 55,000 citations.

Enrique Sentanaمشاهده پروفایل

استاد

• Econometrics
• Asset Pricing
• Financial Economics

Enrique Sentana is a Professor of Economics at CEMFI (Centro de Estudios Monetarios y Financieros) in Madrid, Spain. He is also a Research Fellow at the CEPR Financial Economics Programme and a Senior Research Associate at the LSE Financial Markets Group. His academic career spans prestigious institutions including the London School of Economics and the University of Alicante. Degrees: PhD in Economics (LSE, 1991), MSc in Econometrics and Mathematical Economics (LSE, 1987), Licenciado en Ciencias Económicas y Empresariales (University of Alicante, 1985) Dr. Sentana specializes in Econometrics , with a focus on Asset Pricing , Financial Economics , and VIX Derivatives . His methodological contributions include work on ARCH models, indirect estimation, and identification issues in econometrics, advancing volatility modeling and financial risk assessment. His research trends highlight innovations in empirical asset pricing , nonlinear time series , and financial market linkages . Notable achievements include the Rey Jaime I Prize in Economics (2014) , Fellowships at the Econometric Society and Journal of Econometrics , and prestigious prizes from the University of London and LSE. Scientific Awards: Rey Jaime I Prize in Economics (2014) Fellow of the Econometric Society (2012) Fellow of the Journal of Econometrics (2010) Sayers Prize, University of London (1992) Ely Devons Prize, London School of Economics (1987) Dr. Sentana has advised 10 PhD students at CEMFI and held editorial roles including Managing Editor of the Review of Economic Studies and Co-Editor of the Journal of Financial Econometrics . He has also served as Executive Vice-President of the Econometric Society and Treasurer of its European Standing Committee.

Joost-Pieter Katoenمشاهده پروفایل

استاد

• Model Checking
• Formal Verification
• Probabilistic Models
• +۵ مورد دیگر

Joost-Pieter Katoen is a full Professor at RWTH Aachen University and Head of its Computer Science Department since 2012. He also holds a part-time (20%) Professorship at the University of Twente . His research focuses on model checking , probabilistic verification , formal semantics , and software verification , with applications in aerospace systems. His work has led to significant tools like MRMC (probabilistic model checker), COMPASS (AADL analysis tool-set), and libalf (learning automata library). He has authored over 18 international projects (total €5.2 million) and graduated 12 PhD students. Scientific Awards : Member, German National Academy of Sciences (Leopoldina), 2024 ACM Fellow, 2020 ERC Advanced Grant, 2018 Honorary doctorate, Aalborg University, 2017 Teaching Award, RWTH Aachen, 2010 Philips Early Career Development Award, 1988 Research Trends (from articles): His recent work spans probabilistic program verification , quantitative game theory , Markov chain analysis , and parameter synthesis for stochastic systems, with applications in AI, quantum computing, and fault tree analysis. Leadership & Service : Katoen co-founded the QEST conference , chairs ETAPS steering committee, and has led numerous program committees (CONCUR, TACAS, QEST). He has served on editorial boards and organized conferences/seminars globally.

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.

Sara van de Geerمشاهده پروفایل

استاد

• Mathematics for machine learning
• High-Dimensional statistics
• Empirical processes
• +۲ مورد دیگر

Sara van de Geer is a Full Professor at the Seminar for Statistics within the Department of Mathematics at ETH Zürich since 2005. She previously held academic positions at the University of Leiden, Université Paul Sabatier (Toulouse), and others. She earned a Master's (1982) and Ph.D. (1987) in Mathematics from Leiden University. Her research focuses on high-dimensional statistics, empirical processes, and mathematical foundations of machine learning. Van de Geer has received prestigious recognitions including the Van Wijngaarden Award (2016), Knight in the Order of Orange-Nassau (2015), and membership in Leopoldina (2013). She served as President of the Bernoulli Society (2015–2017) and Chair of the Seminar for Statistics at ETH Zürich. Her contributions include landmark works on statistical learning theory and high-dimensional inference, with key publications in top journals like Annals of Statistics and SIAM/ASA Journal on Uncertainty Quantification. Her academic leadership includes organizing Saint Flour Lectures, Wald Lectures (2016), and delivering plenary lectures globally. Her research bridges theoretical statistics with applied methodologies, emphasizing rigorous mathematical frameworks for modern data analysis challenges.