جستجوی استاد راهنمای دانشگاهی

Janis Nötzelمشاهده پروفایل

پژوهشگر

• Quantum Information Theory
• Machine Learning
• Sensor Networks
• +۳ مورد دیگر

Dr. Janis Nötzel is a senior researcher at the Chair of Theoretical Information Technology (Technische Universität München) and leads his independent Emmy Noether research group. Previously, he held a postdoctoral position at Universitat Autónoma de Barcelona and contributed to 5G practical implementations at TU Dresden's 5G Lab. His research spans quantum information theory, physical layer security, and machine learning applications. Key focuses include Quantum channel capacities under adversarial conditions Entanglement-assisted communication Quantum software frameworks (QuNetSim, QuReed) Interplay between classical and quantum communication Security analysis for 6G networks Resource optimization in quantum systems Recent publications (2023-2025) showcase innovations in Quantum satellite communication architectures Hybrid quantum-classical clustering algorithms Photonic processor instability modeling Covert capacity of compound channels Quantum key distribution resilience Free-space Bessel beam communication He actively collaborates with 6G-life research hub and contributes to quantum network simulation tools. Grants include funding from DFG (Leibniz Program), BMBF (6G-life, Q.Link.X), and StMWi (6G Zukunftslabor Bayern).

Karl-Erik Årzénمشاهده پروفایل

استاد

• Control Engineering
• Cyber-Physical Systems
• Real-Time Systems
• +۹ مورد دیگر

Karl-Erik Årzén is Professor and Head of the Department of Control Engineering at Lund University's Faculty of Engineering. He is also Co-director of the Wallenberg AI, Autonomous Systems and Software Program (WASP) and a key member of ELLIIT, the excellence center in information technology. His roles include leadership in AI and digitalization profile areas at both LTH and Lund University. His research lies at the intersection of control engineering and computer science, with a focus on cyber-physical systems, real-time systems, embedded control, and resource management in cloud and edge computing environments. He has pioneered methods for predictable performance in cloud applications and dynamic resource allocation using control-theoretic approaches. The recent publications highlight a strong trend in control over the cloud and edge, real-time scheduling co-design, distributed camera systems, and reinforcement learning for auto-scaling. Key topics include model predictive control, LQG-based scheduling, bandwidth allocation, and robustness in cyber-physical systems. The work spans theoretical control design and practical implementation in distributed systems. His scientific awards include multiple Best Paper Awards from IEEE and ACM conferences in 2018, 2016, and 2004, recognizing excellence in autonomic computing, edge computing, and real-time systems. Best Paper Award, IEEE International Conference on Autonomic Computing, 2018 Best Paper Award, IEEE International Conference on Edge Computing (EDGE), July 2018 Best Paper Award - RTNS 2016 Best Paper Award - RTCSA 2004 Årzén has supervised over 20 PhD students, including Mikael Johansson, Anton Cervin, Yang Xu, and Per Skarin, and currently supervises Ahmed Al Bayati and Max Nyberg Carlsson. His grant portfolio includes major projects such as WASP, AORTA (VINNOVA), and ELLIIT's 'Robust and Secure Control over the Cloud'. He has also contributed to innovation through tools like TrueTime and Jitterbug. He leads the RobotLab LTH initiative and is involved in the Nordic University Hub on Industrial Internet of Things (HI2OT). His work bridges academia and industry, with collaborations on adaptive control, cloud-native systems, and autonomous robotics.

Florian Brandlمشاهده پروفایل

دانشیار

• Microeconomics
• Social Choice Theory
• Decision Theory
• +۴ مورد دیگر

Florian Brandl is an Argelander Professor (associate professor with tenure) at the University of Bonn, holding positions in both the Department of Economics and the Hausdorff Center for Mathematics. Previously, he was a postdoctoral research scholar at Princeton University and Stanford University. His academic career demonstrates a strong foundation in mathematical economics and game theory, with affiliations spanning multiple prestigious institutions. Brandl earned his Doctoral degree in Mathematics (summa cum laude) from the Technical University of Munich in 2018, following a Master's degree (2013) and Bachelor's degree (2011) from the same institution. His doctoral work focused on "Zero-Sum Games in Social Choice and Game Theory" under the supervision of Felix Brandt, establishing the foundation for his research trajectory. Prof. Brandl's research spans microeconomic theory with a focus on social choice theory, decision theory, and game theory. He is particularly interested in decision-making under uncertainty, connections between social choice and game theory, and dynamic processes converging to equilibrium. His work employs mathematical tools to analyze interactions of multiple entities in economic contexts, often incorporating algorithmic approaches and methods from theoretical computer science. He has made significant contributions to fair division, mechanism design, and probabilistic social choice. His publication record shows consistent contributions across multiple subfields, with recent work focusing on patience effects in fair division, social learning barriers, and axiomatic characterizations of equilibrium concepts. Brandl's research demonstrates strong interdisciplinary connections between economics, mathematics, and computer science, with publications in top journals across all three disciplines. Best Student Paper Award at WINE 2021 for "Funding Public Projects: A Case for the Nash Product Rule" Associate Editor for Theoretical Economics Co-organizer of the COMSOC Video Seminar Prof. Brandl actively contributes to academic service and community building. He co-organizes the COMSOC Video Seminar and will host a Trimester Program on "Advances in Mechanism Design" in Bonn in summer 2026. He serves on program committees for major conferences including COMSOC 2023 and EC 2023. His research has been supported through his position as a Bonn Junior Fellow at the Hausdorff Center for Mathematics since 2021. Based at the Institute for Microeconomics and affiliated with the Hausdorff Center for Mathematics, Brandl collaborates with a broad network of researchers across economics and computer science. His work often involves interdisciplinary collaboration, as evidenced by his numerous co-authored publications with researchers from various institutions worldwide. He maintains strong connections with the University of Oxford's Global Priorities Institute as a Research Affiliate.

Nicole Megowمشاهده پروفایل

استاد

• Combinatorial optimization
• Discrete optimization
• Mathematical optimization
• +۱۱ مورد دیگر

Nicole Megow is a Professor holding the chair for Combinatorial Optimization in the Faculty of Mathematics and Computer Science at the University of Bremen since 2016. She is affiliated with several research clusters including Humans on Mars Initiative, Minds, Media, Machines, and Dynamics in Logistics. Her academic journey includes positions at TU Berlin, Max Planck Institute for Informatics, TU Darmstadt, and TU Munich. Professor Megow's research focuses on mathematical optimization, algorithm design and analysis, and operations research. Her specific interests span combinatorial and discrete optimization, efficient algorithms, scheduling theory, resource allocation, packing problems, network design, routing, and uncertainty models including online, stochastic, robust, and explorable approaches. Her work bridges theoretical foundations with practical applications in logistics and decision-making systems. Her recent publications demonstrate a strong trend toward integrating prediction models with traditional optimization frameworks, particularly in scheduling and matching problems. She has made significant contributions to understanding the role of uncertainty in optimization problems, developing algorithms that work effectively with incomplete or uncertain information. Her work spans multiple prestigious venues including Mathematical Programming, Algorithmica, SODA, STACS, and NeurIPS. Dissertation Award by the German Operations Research Society (2007) Berlin Science Award for Young Researchers (2013) Heinz Maier-Leibnitz Prize (2013) Listed among Germany's top 40 researchers below 40 (Capital, 2014, 2015) Professor Megow actively supervises PhD students and postdocs, including Max Stahlberg, Joes Biburger, Sarah Morell, Bart Zondervan, Zhenwei Liu, and Alexander Lindermayr. She serves on numerous program committees for major conferences including SODA, IPCO, and STOC, and holds editorial positions for several prestigious journals. Her current research projects include Optimization under Explorable Uncertainty (DFG funded), How robots learn how to use structure (seed grant from MMM research cluster), and Scheduling Invasive Multicore Programs Under Uncertainty (within TCRC 89).

• Machine Learning
• Reinforcement Learning
• Bandit Algorithms
• +۵ مورد دیگر

Dr. Kevin G. Jamieson is a faculty member at the University of Washington , School of Computer Science , with prior affiliations at the University of California, Berkeley (Department of Electrical Engineering and Computer Sciences) and the University of Wisconsin-Madison (Department of Electrical and Computer Engineering). His work spans machine learning, reinforcement learning, bandit algorithms, and robotics. Current university: University of Washington Academic rank: Professor His research focuses on: Bandit algorithms and sequential decision-making Optimization in non-stationary environments Reinforcement learning with real-world applications Multi-agent systems and game theory Efficient data selection for multimodal learning Human-in-the-loop AI systems Recent publications highlight his expertise in pure exploration strategies, robotic manipulation, and bridging simulation-to-reality gaps in RL. He has mentored numerous collaborators, though formal student advising details are not explicitly listed here. No scientific awards are mentioned in the provided data.

Tibor Szabóمشاهده پروفایل

استاد

• Combinatorics
• Extremal Graph Theory
• Random Structures and Algorithms
• +۵ مورد دیگر

Tibor Szabó is a Professor in the Combinatorics and Graph Theory group at the Department of Mathematics, Freie Universität Berlin. He holds a PhD from The Ohio State University, advised by Ákos Seress. Prior to his current position, he held roles at McGill University, ETH Zürich, the Institute for Advanced Study (Princeton), and the University of Illinois (UIUC) as a J.L. Doob Research Assistant Professor. Research Interests: His work focuses on combinatorics and combinatorial optimization, including extremal problems, random structures and algorithms, pseudorandom graphs, positional games, and the combinatorics of linear programming. He explores tools from algebra, probability theory, and topology applied to combinatorics. Teaching: He teaches courses such as Algorithmic Combinatorics, Extremal Combinatorics, and runs the Combinatorics Seminar. His lecture notes include works on positional games and explicit constructions in extremal combinatorics. Students & Postdocs: Notable PhD advisees include Yamaan Attwa, Silas Rathke, Simona Boyadzhiyska, and Patrick Morris. Postdoctoral fellows include Olaf Parczyk and Anurag Bishnoi. His research has involved collaborations with over 50 co-authors. Funding & Grants: Supported by grants from the Swiss National Science Foundation (SNF) and German Research Foundation (DFG), focusing on topics like positional games and extremal graph theory.

Konstanze Schiemannمشاهده پروفایل

پژوهشگر

• Cultural History of the Roman Empire
• Environmental History of Antiquity
• Human-Animal Relationships in Antiquity
• +۲ مورد دیگر

Konstanze Schiemann is a Research Associate in the Department of Ancient History and Cultural History of Antiquity at Johannes Gutenberg University Mainz since April 2021. Her work integrates teaching and research, focusing on the cultural history of the Roman Empire, particularly games and popular culture, environmental history, human-animal relationships, and early Christianity's influence on societal norms. Doctorate : University of Amsterdam (2024), thesis on animal hunts in late antiquity. Master's : Binational History program (Paris/Heidelberg, 2014–2016). Bachelor's : History and Economics at University of Mannheim (2010–2014). Her research examines contested cultural practices like animal hunts, analyzing how late antique societies navigated Roman tradition and Christian ethics. Publications include peer-reviewed reviews, science communication articles, and conference contributions. Key Research Themes : Cultural conflict, human-animal dynamics, political symbolism in spectacles. Trends : Focus on late antiquity (4th–6th centuries), interdisciplinary analysis of environmental and religious shifts. She received a Heinrich Böll Foundation Doctoral Scholarship (2017–2020) and is active in academic networks including the Cultural and Literary Animal Studies (CLAS).

• Singular Stochastic Optimal Control
• Optimal Stopping and Free-Boundary Problems
• Stochastic Games
• +۶ مورد دیگر

Giorgio Ferrari is a Full Professor for Mathematical Finance at the Institute for Mathematical Economics (IMW), Faculty of Economics, Bielefeld University. His research bridges stochastic control theory with applications in economics, finance, actuarial science, and epidemiology. Education: B.Sc. and M.Sc. in Physics and Mathematical Physics from the University of Rome La Sapienza, Ph.D. in Mathematics for Economic-Financial Applications (2012). Academic Appointments: Post-Doctoral Researcher (2012–2015), Substitute Full Professor (2015), Junior Professor (W1) (2016–2017), Associate Professor (2017–2023), and Full Professor (2023–present) at Bielefeld University. Research Interests focus on Singular Stochastic Control , Optimal Stopping , and Stochastic Games , with applications to economic policy, financial markets, and epidemic modeling. His work extends to Mean-Field Games for large-scale strategic interactions and Free-Boundary Problems for investment decision-making under uncertainty. Scientific Contributions include groundbreaking publications in Stochastic Processes and their Applications , Mathematical Finance , and SIAM Journal on Control and Optimization . His research projects, such as the DFG SFB 1283 subproject C4 and the Research Training Group 2865 , address uncertainty in dynamic economies through game-theoretic and stochastic frameworks. Notable Awards: AMASES Best Young Researcher Paper (2014), YITP Research Prize (2017), and multiple research fellowships from the University of Padova. Leadership: Director of the Bielefeld Graduate School in Theoretical Sciences (2023–present) and Principal Investigator in major DFG-funded initiatives.

• Machine Learning
• Fairness in Artificial Intelligence
• Federated Learning
• +۷ مورد دیگر

Yang Liu is an Assistant Professor in the Department of Electrical and Computer Engineering at the Baskin School of Engineering, University of California, Santa Cruz. Previously, they were affiliated with Harvard University and earned their PhD in 2015 from the Department of EECS at the University of Michigan, Ann Arbor. Their research lies at the intersection of machine learning, fairness, and trustworthy AI, with a strong focus on large language models, federated learning, and causal reasoning. Their research interests include: Machine Learning and Fairness Federated and Privacy-Preserving Learning Large Language Model Safety and Unlearning Causal Inference and Counterfactual Reasoning Anomaly Detection and Robust Forecasting Human-AI Interaction and Ethical AI Recent publications (2024–2025) demonstrate a strong trend in developing methods for machine unlearning, fairness in LLMs, and robustness under label noise and distribution shifts. Their work frequently appears in top-tier venues such as NeurIPS, ICLR, ICML, AAAI, and KDD, often in collaboration with researchers like Zhaowei Zhu, Mingyan Liu, Jiaheng Wei, and Kun Zhang. Themes include algorithmic fairness, model accountability, and human-aligned AI systems. Scientific contributions include: Frameworks for LLM unlearning and model editing Methods for fair classification and recourse Robust time series forecasting under anomalies Test-time adaptation in multimodal models Causal approaches to debiasing and policy learning While no formal advising list is provided, the depth and volume of collaborative work suggest active mentorship of graduate students and postdocs. Their research program is highly active, with numerous ongoing projects in trustworthy and socially responsible AI.

Andreas S. Schulzمشاهده پروفایل

استاد

• Mathematical Optimization
• Algorithm Design
• Operations Research
• +۵ مورد دیگر

Prof. Dr. Andreas S. Schulz is a faculty member at Technische Universität München (TUM), holding a chair in the Department of Mathematics and the Department of Business and Economics. He previously served as the Patrick J. McGovern Chair of Management and Professor of Mathematics at MIT. His research focuses on mathematical optimization, algorithm design, and their applications in logistics, production, healthcare systems, and online advertising. He has held visiting professorships at institutions such as the Sauder School of Business (UBC) and ETH Zurich. Prof. Schulz’s research bridges operations research, theoretical computer science, and economics. He develops analytical methods to solve complex decision-making problems in business, including scheduling, resource allocation, and network optimization. A key interest is applying mathematical approaches to enhance healthcare delivery and system efficiency. Education: PhD in Operations Research (MIT), prior academic roles at MIT and visiting institutions. Key Achievements: Alexander von Humboldt Professorship (2014), Humboldt Research Award (2010), Glover-Klingman Prize (2006). Research Themes: Robust optimization, approximation algorithms, scheduling theory, and algorithmic game theory. His publications span topics like integer programming, optimal transport, and congestion games. He collaborates across disciplines, emphasizing practical applications of theoretical insights.

Martín Hötzel Escardóمشاهده پروفایل

استاد

• Homotopy Type Theory
• Univalent Mathematics
• Martin-Löf Type Theory
• +۱۲ مورد دیگر

Martín Hötzel Escardó is a Professor of Theoretical Computer Science in the School of Computer Science at the University of Birmingham, UK. He has been a faculty member since 2000, following previous academic positions at Imperial College London, the University of Edinburgh, and the University of St Andrews. His research bridges theoretical computer science and pure mathematics, with a strong emphasis on foundational aspects of computation. His educational background includes a BSc and MSc from Universidade Federal do Rio Grande Sul (Brazil) and a PhD from Imperial College London (1997) under Michael B. Smyth. Escardó's research interests center on topology in computation , constructive mathematics , dependent and univalent type theory (including Homotopy Type Theory and Cubical Type Theory), domain theory , locale theory , and exact real-number computation . His work explores deep connections between logic, topology, and programming, often using functional languages like Haskell and Agda to formalize and experiment with theoretical ideas. He is particularly known for his discoveries on exhaustively searchable infinite sets and the topological nature of computability. The trend in his recent publications reflects a sustained focus on univalent foundations, constructive domain and order theory, game semantics with dependent types, and the logical structure of type universes. His work consistently advances the formalization and understanding of higher-type computation and constructive mathematics within modern type theories. He has no listed scientific awards in the provided text, but his influence is evident through his extensive publication record and software developments like TypeTopology. Escardó has advised several students and collaborators, though specific names are not listed. He has been involved in significant research projects, particularly in the formalization of mathematics in type theory and the semantics of programming languages. His work often involves developing Agda libraries to formalize new mathematical results constructively. He leads and contributes to a vibrant research group in theoretical computer science at Birmingham, with a focus on logic, semantics, and type theory. His public research blog, lecture notes, and open-source Agda code (e.g., TypeTopology, HoTT-UF-in-Agda) serve as important resources for the community.

Sandra Transchelمشاهده پروفایل

استاد

• Supply Chain Management
• Inventory Control
• Revenue Management
• +۵ مورد دیگر

Prof. Dr. Sandra Transchel is a Full Professor of Supply Chain and Operations Management at Kühne Logistics University (KLU) in Hamburg, Germany. She has held this position since 2019, previously serving as Associate Professor (2011-2019) and Dean of Programs (2014-2015). Her academic journey includes appointments as Assistant Professor at Pennsylvania State University (2008-2011) and Visiting Assistant Professor at Tuck School of Business at Dartmouth (2011). Education includes: PhD in Business Administration, University of Mannheim (2008) Diploma in Business Mathematics, Otto-von-Guericke University Magdeburg (2004) Her research integrates supply chain management, inventory control, and revenue management with a strong focus on retail operations optimization and food supply chain sustainability . Key investigations examine perishable inventory systems, demand-supply synchronization, and substitution behavior. Current projects address food waste reduction through contract-based coordination in fresh food supply chains and development of urban food production networks (FabCity). Publications demonstrate consistent focus on inventory optimization under uncertainty, with recent work extending into pandemic impacts on humanitarian logistics and perishable inventory systems with lead-time variability. Research consistently bridges theoretical models with retail/manufacturing applications. Teaching includes Decision Analysis, Inventory and Warehouse Management, and Warehousing and Intralogistics across BSc, MBA, and MSc programs at KLU.

Matthew K. Tamمشاهده پروفایل

دانشیار

• continuous optimisation and its applications
• monotone operator theory
• variational and convex analysis
• +۳ مورد دیگر

Matthew K. Tam is an Associate Professor at the School of Mathematics and Statistics, The University of Melbourne, specializing in Operations Research. He is also an investigator at the Melbourne Centre for Data Science and an associate investigator in the ARC Training Centre OPTIMA. PhD in Mathematics (2016) from University of Newcastle under Jonathan Borwein Postdoctoral research at University of Göttingen with RTG-2088 and Alexander von Humboldt Foundation Junior Professor at University of Göttingen (2017-2020) His research focuses on continuous optimization, monotone operator theory, and variational analysis, with applications in wavelet construction and inverse problems. Key trends include distributed algorithms, resolvent splitting, and convergence analysis for feasibility problems. Discovery Early Career Researcher Award (DECRA) Alexander von Humboldt Fellowship He collaborates with institutions like ANZIAM, Springer, and IEEE, with publications spanning mathematical optimization, harmonic analysis, and computational mathematics. His work emphasizes algorithmic design for complex data systems and real-world applications in imaging and industrial modeling.

• Sport Management
• Economics of Sport
• Sports Clubs Operations
• +۳ مورد دیگر

Christoph Breuer is a Professor at the Institute of Sport Economics and Sport Management at the Deutsche Sporthochschule Köln. His work focuses on sports economics, club management, and policy analysis. He leads research initiatives examining sports integrity, club ownership dynamics, and volunteer engagement. Breuer is actively involved in editorial roles for journals such as the Journal of Global Sport Management and Sport Management Review. His research spans over 800 publications, including studies on pandemic impacts on athletes and clubs, sponsorship strategies, and logistics in sports organizations. He has received the SMAANZ Best Conference Paper Award 2024. Key projects include analyzing multi-club ownerships and evaluating prevention measures against sports match-fixing. He advises PhD students like Thomas Breuer and Christoph Pott. His grants include projects funded by third parties, such as the 'Sportentwicklungsbericht' series and investigations into sports integrity. Breuer collaborates internationally, addressing topics like equipment logistics and athlete well-being. His work bridges academic research with practical applications for sports policy and management. Editorial roles: Journal of Global Sport Management, Sport Management Review Key projects: Sport Development Report (SEB 3.0), UEFA EURO 2024 evaluation Media engagements: Over 100 press contributions on topics like sports economics and club financing

• Reinforcement Learning
• Bandit Algorithms
• Learning Theory
• +۴ مورد دیگر

Claire Vernade is a Group Leader at the University of Tübingen within the Cluster of Excellence Machine Learning for Science. She holds an Emmy Noether award (2022) and an ERC Starting Grant (2024) for her projects FoLiReL and ConSequentIAL , focusing on theoretical reinforcement learning and non-stationary environments. Education: PhD from Telecom ParisTech (2017) Post-doctoral researcher at University of Magdeburg (2018) Her research bridges sequential decision making, bandit problems, and reinforcement learning theory. Recent work explores lifelong learning, distributional RL, and game-theoretic approaches to PCA, emphasizing mathematical rigor and algorithmic innovation. Recent publications highlight trends in non-stationary RL , continual learning , and bandit algorithms with complex feedback structures. Key subfields include meta-learning, adaptive control, and theoretical guarantees in dynamic programming. Scientific Awards: Emmy Noether Award (2022) ERC Starting Grant (2024) Outstanding Paper Award & Oral Presentation, ICLR (2021) She mentors PhD and master's students in theoretical machine learning, with current advisees including Nicolas Nguyen, Onno Eberhard, and Ziyad Sheebaelhamd. Her lab actively recruits candidates in bandit algorithms and RL theory through the IMPRS-IS and ELLIS doctoral programs. Claire co-leads diversity initiatives like Tübingen Women in Machine Learning and Women in Learning Theory, advocating for inclusivity in AI research. She has organized workshops at ICML and EWRL, and contributed to union activism in the tech industry.