جست‌وجوی استاد و پژوهشگر

Xin Zhangمشاهده پروفایل

استادیار

• Programming Languages
• Software Engineering
• Program Analysis
• +۶ مورد دیگر

Xin Zhang serves as an Assistant Professor in the Department of Computer Science and Technology within the School of Electronics Engineering and Computer Science at Peking University. His academic profile demonstrates deep engagement with programming languages and software engineering research communities through active participation in major conferences including ASE, SPLASH/OOPSLA, PLDI, and ICSE. Dr. Zhang's research focuses on the synergistic relationship between program analysis and machine learning. He investigates how ML/AI techniques can enhance traditional program analysis methods while simultaneously developing program analysis approaches to improve the interpretability, fairness, robustness, and safety of AI systems. His work spans probabilistic program analysis, abstraction refinement techniques, Bayesian modeling for program semantics, and applications of graph neural networks to static analysis problems. His publication record shows consistent contributions to top venues from 2016 through 2025, with recent work emphasizing Bayesian program analysis, abstraction refinement methods, and the intersection of formal methods with machine learning. The trajectory of his research demonstrates increasing sophistication in combining traditional program analysis techniques with modern AI approaches. Dr. Zhang actively contributes to the academic community as a program committee member for major conferences including ASE, SAS, PLDI, and SPLASH. His service includes reviewing, session chairing, and committee participation across multiple venues, reflecting his standing in the programming languages and software engineering communities.

Dirk Roosمشاهده پروفایل

استاد

• Machine Learning
• Robust Design Optimization
• Stochastic Analysis
• +۱۰ مورد دیگر

Prof. Dr.-Ing. Dirk Roos is a Professor for Computersimulation und Design Optimization at the Department of Mechanical Engineering and Process Engineering, Niederrhein University of Applied Sciences, where he has served since March 2011. He is also the Head of the Institute for Modeling and High Performance Computing (IMH) since December 2016. His academic career includes previous positions as Head of Robust Design Optimization at DYNARDO Dynamic Software and Engineering GmbH (2002-2011) and Technical Solutions Specialist at CADFEM GmbH (2000-2008). Prof. Roos specializes in machine learning, robust design optimization, stochastic analysis, and probabilistic modeling for virtual product development. His research focuses on developing mathematical methods for stochastic structural and fluid simulation, robustness and reliability analysis, multidisciplinary optimization, and software development for complex system development. He has established strong collaborations with academic institutions including RWTH Aachen, Ruhr-Universität Bochum, and industrial partners like Siemens AG and Robert Bosch GmbH. His recent work explores Probabilistic Intelligence, cyber-physical systems, digital twins, and Big Data Analysis, with applications spanning power plant flexibility, renewable energy, turbomachinery, automotive, aerospace, and medical technology. Prof. Roos has successfully secured numerous third-party funded research projects totaling over 1.8 million euros, including collaborations with Siemens AG, Robert Bosch GmbH, and various universities. optiSLang Award 2012 Weimar Optimization and Stochastic Days Gutachter BMBF im Programm FH-Kooperativ since 2019 Mitglied des Scientific Committee International Probabilistic Workshop since 2017 Mitgliedschaft im Graduierteninstitut für angewandte Forschung der Fachhochschule in NRW since 2017 Prof. Roos supervises multiple doctoral students and has successfully completed several cooperative PhD projects. His current research projects include AI-driven optimization for medical care, reinforcement learning for emergency room planning, and machine learning algorithms for power plant component lifetime prediction. The Institute for Modeling and High Performance Computing (IMH) under his leadership develops mathematical methods and software competence in machine learning and CAE-based robust design optimization for virtual product development.

Nenad Kosمشاهده پروفایل

دانشیار

• Game Theory
• Mechanism Design
• Theoretical Foundations
• +۳ مورد دیگر

Nenad Kos is an Associate Professor in the Department of Economics at Bocconi University. He is also an affiliate at the Innocenzo Gasparini Institute for Economic Research (IGIER) and Centre for Economic Policy (CEPR). His primary research interests include: Game Theory Mechanism Design Information Economics Corporate Finance Epidemiology Dr. Kos's research focuses on theoretical foundations of economics, particularly in mechanism design and game theory. His work explores how information asymmetry affects market outcomes, optimal pricing strategies, and auction design. He has made significant contributions to understanding signaling in markets with covert information, the design of mechanisms under ambiguity, and the economic aspects of epidemic modeling. His publications span top economics journals including Econometrica, Journal of Economic Theory, Review of Economic Studies, and American Economic Journal: Microeconomics. His research demonstrates a consistent focus on theoretical rigor while addressing practical economic problems across various domains. Dr. Kos teaches courses in computational microeconomics, specifically focusing on mechanism design, and general microeconomics at Bocconi University. His teaching reflects his research expertise, emphasizing theoretical foundations and mathematical approaches to economic problems.

• Game Theory
• Mechanism Design
• Microeconomic Theory
• +۳ مورد دیگر

Moritz Meyer-ter-Vehn is a Professor in the Department of Economics at the University of California, Los Angeles (UCLA), where he has held a faculty position since 2007. He serves as an Associate Editor for leading journals including the American Economic Review, Econometrica, and the Review of Economic Design, and holds the ECONtribute Research Fellowship since 2020. His educational background includes Mathematics studies at the University of Paris VII and the University of Freiburg, culminating in a PhD in Economics from the University of Bonn (2003). Meyer-ter-Vehn's research centers on Game Theory, Mechanism Design, and Microeconomic Theory, with significant extensions into Network Economics, Information Economics, and Organizational Economics. His work investigates strategic interactions in social networks, labor markets, and dynamic environments, often combining rigorous theoretical modeling with real-world applications like discrimination analysis and reputation systems. His recent publications (2021-2024) reveal a dominant focus on social learning in networks, labor market dynamics, and reputational mechanisms. These works frequently involve collaboration with Sven Board and appear in top-tier journals, demonstrating a consistent emphasis on information structure and optimal mechanism design across diverse economic contexts. His primary recognition includes: ECONtribute Research Fellow (2020-present) While specific student advising details are unreported, his extensive publication record and editorial roles indicate active research mentorship. He contributes significantly to grant-funded research through the ECONtribute Cluster initiative. He participates in the ECONtribute research cluster, a collaborative framework advancing economics and decision sciences through interdisciplinary projects since 2020.

Gabriele Gühringمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Anomaly Detection
• +۳ مورد دیگر

Gabriele Gühring serves as Professor at Esslingen University of Applied Sciences with dual appointments in the Faculty of Basic Sciences (since 2008) and Faculty of Computer Science and Information Technology (since 2021). She currently holds the executive position of Vice President for Research and Transfer (since September 2022), concurrently directing the Department of Research and Transfer while serving on the Science Commission and Honours Committee. Her academic foundation includes: Mathematics and Physics studies at University of Tübingen (1991-1996) Doctoral research on nonautonomous differential equations (1997-1999) Part-time Master's in Mathematical Finance at University of Oxford (2002-2004) Prof. Gühring's research centers on practical AI applications , specializing in anomaly detection systems for industrial infrastructure and multimodal learning for technical documentation. Her work bridges theoretical mathematics with real-world implementations in renewable energy, urban mobility, and medical diagnostics, demonstrating consistent evolution from pure mathematics to cutting-edge machine learning. Analysis of her 14 publications (1999-2023) reveals a strategic pivot from theoretical differential equations to industrial AI solutions. Recent work (2020-2023) focuses on anomaly detection in energy systems (power plants, vehicle fleets), multimodal neural networks for product analysis, and mobility data anonymization , with methodologies spanning spiking neural networks, graph-based approaches, and Bayesian deep learning. While no scientific awards are documented, her leadership in the BMBF-funded Anomob project demonstrates active grant acquisition in data privacy. Administrative responsibilities likely encompass significant mentorship, though no formal advisees are listed in the provided materials. Her research operates through Esslingen's Department of Research and Transfer, fostering cross-disciplinary collaborations between computer science, engineering faculties, and industrial partners in energy, transportation, and healthcare sectors.