جستجوی استاد راهنمای دانشگاهی

Stefan Koothsمشاهده پروفایل

استاد

• Macroeconomic Forecasting
• Stabilization Policies
• Money and Banking
• +۴ مورد دیگر

Stefan Kooths is a Professor of Economics and Research Director of the Business Cycles and Growth Research Center at the Kiel Institute for the World Economy (IfW Kiel). He holds professorial roles at the University of Applied Sciences Europe (Campus Berlin) and BSP Business and Law School in Berlin/Hamburg. His expertise spans macroeconomic forecasting, stabilization policies, and computational economics. He advocates a coordinationist paradigm focusing on systemic economic mismatches and has held leadership roles including interim Vice President of the Kiel Institute (2021–2023). Education: PhD in Economics (1998), University of Muenster Master of Science in Economics (1993), University of Muenster Research Interests: Dr. Kooths prioritizes analyzing systemic distortions in economies using computational methods. His work integrates simulation software, soft computing, and knowledge-based systems to address macroeconomic imbalances. He emphasizes the role of dysfunctional social coordination mechanisms in economic crises. His recent analyses focus on inflation, supply chain disruptions, and policy responses to global shocks. Affiliations: Chairman of the Hayek Society, member of the Mont Pèlerin Society, Board Member of the World Economic Council, and advisor to the Liberal Institute (Zurich). He has held leadership roles at institutions like the Muenster Institute for Computational Economics (2002–2005) and DIW Berlin (2010). Advising & Grants: Directed the German economic outlook at the Kiel Forecasting Center (2010–2014), managed macroeconomic analysis teams, and secured grants for computational economics projects. His advisory work includes policy evaluations for inflation and growth strategies. Labs/Teams: Oversees the Business Cycles and Growth Research Center, a hub for macroeconomic modeling and policy analysis. Collaborates with international institutions on forecasting tools and crisis management frameworks.

• Artificial Intelligence
• Human-Computer Interaction
• Machine Learning
• +۴ مورد دیگر

Jeffrey P. Bigham is a researcher at Carnegie Mellon University 's Human-Computer Interaction Institute . He specializes in Artificial Intelligence , Accessibility , and Human-Computer Interaction , with a focus on Inclusive AI systems Accessible web and mobile development Large language model applications User interface engineering His recent publications explore synthetic data generation for UI/Slide understanding, LLM-based code generation , and real-time notetaking systems . Key themes include Improving accessibility through AI Interactive ML model optimization Collaborative human-AI workflows Visual and speech interface analysis Bigham's work spans Computer Science , Machine Learning , and Natural Language Processing , often addressing disability inclusion and user-centered AI . He collaborates extensively with researchers like Jason Wu Yi-Hao Peng Amy Pavel Stephanie Valencia Henny Admoni across 300+ publications since 2006. Notable contributions include automated accessibility tools (like Screen Recognition ), stuttering accommodation in speech recognition , and generative AI literacy initiatives . His research bridges technical AI innovation with social impact , particularly for marginalized user groups.

• Neural Networks
• Adaptive Resonance Theory
• Machine Learning
• +۵ مورد دیگر

Professor Ah-Hwee Tan is a distinguished faculty member at Singapore Management University's School of Computing and Information Systems, Department of Information Systems. With over 30 years of academic contributions since 1991, his research has significantly advanced neural network architectures, particularly Adaptive Resonance Theory (ART), with applications spanning multiple domains of artificial intelligence. His primary research interests include Neural Networks , Adaptive Resonance Theory , Machine Learning , Reinforcement Learning , Knowledge Graphs , Natural Language Processing , and Multi-Agent Systems . Professor Tan's work bridges theoretical neural computation with practical applications, developing novel approaches for knowledge representation, semantic understanding, and intelligent decision-making systems. His recent publications (2022-2025) demonstrate continued innovation across multiple AI subfields, with particular emphasis on hierarchical reinforcement learning, knowledge graph refinement, sentiment analysis, and federated learning architectures. The research shows a clear trajectory from foundational neural network theory toward increasingly complex real-world applications in healthcare, social media analysis, and multi-agent coordination. Professor Tan has mentored numerous researchers who have become significant contributors in their own right, including Budhitama Subagdja, Shubham Pateria, and Di Wang. His collaborative work spans international institutions, reflecting his standing in the global AI research community. His research has been consistently published in top-tier venues including IEEE Transactions, Neural Networks, ACM journals, and major AI conferences (AAAI, IJCAI), demonstrating both theoretical rigor and practical impact across computer science and interdisciplinary applications.

• Computer Vision
• Deep Learning
• Robotics
• +۵ مورد دیگر

Hao Yang is a Professor at Southeast University's School of Computer Science and Engineering, specializing in computer vision, deep learning, and robotics. His research spans multiple domains including medical imaging, infrastructure inspection, and multimodal AI systems. His research interests focus on advancing computer vision techniques for practical applications. He develops innovative deep learning architectures for object detection, image segmentation, and quality assessment, with particular emphasis on solving challenges in complex real-world scenarios including rotated object detection, ancient character recognition, and 3D point cloud analysis. His work often integrates novel transformer variants and Mamba architectures to address domain-specific challenges. His publication record shows significant contributions across multiple IEEE and ACM journals, with a strong emphasis on practical applications of AI in engineering contexts. His recent work demonstrates expertise in adapting cutting-edge neural network architectures to solve domain-specific problems in civil engineering, medical imaging, and transportation systems. Hao Yang actively collaborates across disciplines, with publications spanning computer science, electrical engineering, civil engineering, and biomedical applications. His work frequently appears in top-tier conferences including CVPR, AAAI, and ACL, demonstrating his broad impact across multiple AI subfields.

• Wireless Communications
• Machine Learning
• Robotics
• +۶ مورد دیگر

Dr. Kwang-Cheng Chen is a Professor in the Department of Electrical Engineering at the University of South Florida. His research focuses on wireless communications, machine learning applications in networks, robotics, and smart manufacturing systems. He holds a PhD from the University of Maryland (1989) and has affiliations with institutions like National Taiwan University and National Tsing Hua University. Dr. Chen has contributed extensively to IEEE journals and conferences, with over 400 publications since 1992. His work bridges theoretical advancements and practical applications in areas such as 5G/6G networks, edge computing, and multi-agent systems. He has collaborated with global researchers and industry partners, addressing challenges in network slicing, UAV-assisted communications, and resilient production systems. Research interests include: Machine Learning for Network Optimization Smart Factory Automation Ultra-Reliable Low-Latency Communications (URLLC) Edge and Fog Computing Multi-Agent Systems and Robotics Network Slicing and Virtualization Recent articles emphasize leveraging AI and reinforcement learning to solve complex problems in wireless networks (e.g., RIS-aided interference suppression) and robotic systems (e.g., multi-robot task allocation). His work often integrates theoretical models with real-world deployments, such as blockchain-enhanced UAV communication and federated learning in open RAN systems. Grants and collaborations involve government and industry projects on 6G architectures, IoT security, and smart city infrastructure. He leads interdisciplinary teams focusing on future communication systems and industrial automation.

Thomas Kiderleمشاهده پروفایل

پژوهشگر

• Human-Centered AI
• Nonverbal Behavior Analysis
• Computational Humor
• +۴ مورد دیگر

Thomas Kiderle is a Researcher at the Chair for Human-Centered Artificial Intelligence at the University of Augsburg's Faculty of Applied Computer Science. His work focuses on nonverbal behavior synthesis, computational humor, and virtual character development. Key projects include PRESENT (photorealistic sentient entities) and ViLeArn_more (virtual learning environments). He contributes to interdisciplinary research in affective computing, social robotics, and AI ethics. Research interests span multimodal interaction design, generative AI for social agents, and real-time behavioral adaptation. Notable publications address voice conversion for virtual agents, parallel robot affective expressions, and socially-aware personality systems. His team develops emotionally intelligent systems for healthcare, education, and human-robot collaboration. Supervises topics in virtual character interaction, conditional motion synthesis, and multimodal dialogue systems. Collaborates on EU-funded projects like FORSocialRobots and MITHOS. Active in forums like FMLA (Machine Learning Augsburg). Contact: Email | Office 2038N | ORCiD

• Modern Innovation Theory
• Industrial Economics
• Complexity Economics
• +۹ مورد دیگر

Prof. Dr. Andreas Pyka is a Professor of Innovation Economics at the University of Hohenheim. His research focuses on modern innovation theory, complexity economics, and the bioeconomy, emphasizing sustainability transitions and policy design. He holds a PhD and habilitation from the University of Augsburg, with postdoctoral and visiting professorships at institutions in Grenoble, Vienna, and Bremen before joining Hohenheim in 2009. Education: Studied economics at the University of Augsburg (PhD), followed by postdoctoral research at INRA/SERD in Grenoble. Visiting professorships included the Austrian Research Centers in Vienna (2004) and a role at the University of Bremen (2006–2009). Research Interests: Pyka explores the interplay between digital and green transitions, innovation networks, and policy frameworks for sustainable development. His work addresses challenges in bioeconomy, circular economy, and the role of artificial intelligence in stakeholder capitalism models. Recent Article Trends: Focus on sustainability transitions (e.g., bioeconomy governance, food security post-Paris Agreement), digital transformation in industries (automotive, platforms), and agent-based modeling of innovation diffusion. His contributions bridge theoretical frameworks (e.g., Schumpeterian economics) with policy-relevant analysis. Awards: None explicitly listed in the provided texts. Advising & Grants: Supervised numerous dissertations and leads the Department of Innovation Economics, fostering collaborative research with visiting scholars and external doctoral teams. His work emphasizes policy laboratories and systemic interventions in regional innovation systems. Labs/Teams: Coordinates the Chair's research activities, including doctoral seminars and interdisciplinary projects on sustainability and innovation systems.

Thomas Leisnerمشاهده پروفایل

استاد

• Atmospheric Science
• Climate Research
• Aerosol Physics
• +۳ مورد دیگر

Prof. Thomas Leisner is a Professor and Deputy Scientific Spokesman at the Karlsruhe Institute of Technology (KIT), leading the Institute of Meteorology and Climate Research - Atmospheric Aerosol Research (IMK-AAF). His research focuses on atmospheric processes, particularly ice nucleation, aerosol physics, and climate intervention. He has contributed to advancing understanding of secondary ice production mechanisms, aerosol composition in urban and rural environments, and the role of aerosols in cloud formation and climate dynamics. His work integrates field measurements, laboratory experiments, and numerical modeling to address critical gaps in climate science. Research interests include the physical and chemical properties of aerosols, their impact on climate and air quality, and the development of innovative sampling technologies such as UAV-based aerosol measurement systems. He actively investigates the seasonal variability of ice-nucleating particles, biogenic and anthropogenic aerosol sources, and their implications for environmental health and climate change mitigation strategies. Key contributions include studies on the Hallett-Mossop secondary ice production mechanism, brown carbon aerosol characterization, and the role of mucin in respiratory droplet behavior. His research spans interdisciplinary topics such as urban pollution dynamics, forest ecosystem interactions, and the application of cloud chamber experiments to assess climate intervention effectiveness. Prof. Leisner collaborates on international projects, including the Pallas Cloud Experiment, and contributes to climate policy discussions through his analysis of model uncertainties and scientific knowledge gaps. His team develops advanced instrumentation for aerosol analysis and participates in large-scale atmospheric campaigns to enhance observational data for climate models.

• Human-Computer Interaction
• E-Government
• Artificial Intelligence
• +۵ مورد دیگر

Suree Funilkul is an active researcher in the fields of Human-Computer Interaction, E-Government, and Internet of Things (IoT). Her work focuses on user experience (UX) design, AI-driven conversational agents, cybersecurity in consumer IoT, and smart home technologies. She has collaborated extensively with researchers like Debajyoti Pal on studies involving voice assistants, metaverse adoption in education, and information quality frameworks for public sector systems. Her research spans both theoretical models (e.g., SEM-based analyses) and practical frameworks (e.g., CASUX scale for AI UX measurement).

Alexander Zassمشاهده پروفایل

استاد

• Probability Theory
• Statistical Mechanics
• Mathematical Physics
• +۳ مورد دیگر

Alexander Zass is a Substitute Professor for Probability Theory at the University of Potsdam and a post-doctoral researcher in the Interacting Random Systems group at WIAS, Berlin. His research focuses on advanced topics in probability theory, statistical mechanics, and stochastic processes, with particular emphasis on Gibbs point processes, diffusion dynamics, and mathematical physics. He explores systems such as infinite-dimensional diffusions, depletion interactions in colloids, and phase transitions in interacting particle systems. His work integrates rigorous mathematical analysis with applications in physics and complex systems, as seen in studies of the free Bose gas, Widom-Rowlinson models, and the Vicsek model for collective motion. Zass also contributes to foundational aspects of Gibbs measures and their existence under unbounded interactions. His publications reflect expertise in stochastic geometry, cluster expansions, and path-space processes, often addressing existence and uniqueness theorems in probabilistic frameworks. While no awards are explicitly mentioned, his research activity spans over a decade with contributions to both theoretical and applied probability.

Alanwar Amrمشاهده پروفایل

استاد

• Cyber-Physical Systems
• Formal Verification
• Data-Driven Reachability Analysis
• +۷ مورد دیگر

Prof. Alanwar Amr is a Professor at the Chair of Cyber-Physical Systems within the TUM School of Computation, Information and Technology at Technical University of Munich (TUM). His research focuses on data-driven reachability analysis, security-assured reinforcement learning, and privacy-preserving estimation techniques using advanced mathematical frameworks like zonotopes. He holds a PhD from TUM and has held prior positions as an Assistant Professor at Jacobs University Bremen and a postdoctoral researcher at KTH Royal Institute of Technology. His work bridges formal verification, control theory, and cybersecurity in cyber-physical systems. Education: PhD in Automation and Control from TUM (under Prof. Althoff) Research Associate at UCLA and Engineer at Siemens/Morpho Research Interests: Data-driven formal verification methods Secure and resilient control systems Privacy-preserving set-based estimation Adversarial attack defense mechanisms His recent publications emphasize advancements in zonotope-based techniques for safety verification, privacy in distributed systems, and AI-driven control systems with formal guarantees. Key contributions include logical zonotopes for boolean function analysis and diffusion-based observers for multi-agent systems. Notable awards include the KTH Postdoctoral Fellowship, Qualcomm Innovation Fellowship finalist distinctions (2017/2018), and a best demonstration award at IPSN 2017. His work addresses critical challenges in autonomous systems, cybersecurity, and privacy in IoT environments.

Alexander Hübnerمشاهده پروفایل

استاد

• Supply Chain Management
• Sustainable Logistics
• Retail Operations
• +۳ مورد دیگر

Prof. Alexander Hübner is a full Professor of Business Administration at the Technical University of Munich (TUM), leading the Chair for Supply and Value Chain Management at TUM Campus Straubing. His research focuses on sustainable supply chain design, decision support systems in retail, healthcare logistics, and operations optimization. He holds a PhD from the Catholic University of Eichstätt-Ingolstadt and has held roles including Associate Professor at MIT's Luxembourg Centre for Logistics and Head of the Institute for Supply Chain Management at the European Business School. He has extensive industry experience, including six years as a project manager at McKinsey & Company. Research & Awards: Hübner’s work spans retail shelf space optimization, inventory management, and hospital logistics. Notable contributions include applying Markov Decision Processes to patient-bed allocation and exploring omnichannel retail fulfillment. He has received the Emerald Literati Award (2019) and ranks among WirtschaftsWoche's Top 50 Economists (2020). He chairs the EURO Working Group on Retail Operations and serves on editorial boards of leading journals. Education & Career: After graduating in Business Administration from Eichstätt-Ingolstadt, he earned his PhD there and became a junior professor. His career includes roles at MIT, European Business School, and McKinsey. He currently advises on logistics for the German Logistics Association (BVL) and leads interdisciplinary research on sustainable supply chain innovation.

Daniel Beßlerمشاهده پروفایل

پژوهشگر

• Knowledge Representation
• Cognitive Robotics
• Hybrid Reasoning
• +۴ مورد دیگر

Dr. Daniel Beßler is a Researcher at the University of Bremen specializing in knowledge representation and cognitive robotics. Affiliated with the Institute for Artificial Intelligence, he contributes to the Collaborative Research Center EASE (Extracting and Applying Structure from Everyday Activities) and develops frameworks bridging theoretical AI with practical robotic applications. His educational background includes a PhD in Computer Science from the University of Bremen (2022), with dissertation research on ontological representation of activity context for flexible robot task execution. This foundational work underpins his contributions to semantic reasoning in dynamic environments. Beßler's research centers on hybrid symbolic-subsymbolic reasoning systems, with leadership in developing KnowRob 2.0 – a knowledge processing framework enabling cognition-enabled robotic agents. His work extends to semantic scene representation, activity recognition in virtual reality, and game technology applications for robotics simulation. Key innovations include the SOMA ontology for socio-physical activity modeling and FailRecOnt for failure recovery in robotic planning. Recent publications (2021-2024) reveal strong trends in ontological modeling for robot introspection, user preference representation, and universal scene description translation. His work consistently addresses challenges in activity parsing, metacognition, and knowledge-driven manipulation in cluttered environments. Notable scientific recognitions include: Finalist for Best Robotics Paper Award at AAMAS 2018 Selection as one of the most important publications by IEEE Technical Committee on Cognitive Robotics Beßler has over four years of teaching experience in AI and robotics courses, and six years supervising student projects including RoboCup@Home competitions and Unreal Engine-based human modeling. He has secured research funding through CRC EASE and international collaborations focused on knowledge-driven robotics. As co-author of IEEE 1872.2 standard ontology and lead developer of openEASE cloud platform, he actively shapes robotics standardization while maintaining lab affiliations with CRC EASE and virtual reality research groups exploring GPU programming for interactive AI applications.

Manuel Bodirskyمشاهده پروفایل

استاد

• Constraint Satisfaction Problems (CSP)
• Algebraic Methods in Computer Science
• Computational Logic
• +۵ مورد دیگر

Prof. Manuel Bodirsky is a Professor of Algebra and Discrete Structures at Technische Universität Dresden since August 2014. He leads the Algebra and Discrete Structures group within the Faculty of Computer Science and is affiliated with the International Center for Computational Logic (ICCL). His research focuses on constraint satisfaction problems (CSP), algebraic methods in computer science, computational logic, Ramsey theory, model theory, and discrete mathematics. Notable projects include exploring the algebraic tractability of CSPs and applying universal algebra to classify computational complexity. His work frequently intersects with combinatorics, graph theory, and theoretical computer science. Recent publications address advanced topics like temporal CSPs, spectrahedral shadows, and resilience problems using valued CSP frameworks. He maintains active collaborations in computational algebra and logic, contributing to both theoretical foundations and algorithmic applications. Education: Not explicitly listed in provided texts but inferred to include advanced studies in mathematics and computer science. Research interests span foundational areas such as: Constraint satisfaction problem complexity classification Applications of universal algebra to computational problems Model theory and finite structures Combinatorial properties of graphs and tournaments Algorithmic approaches to algebraic and logical systems His recent articles emphasize methodological innovations, including reductions to semidefinite programming, Ramsey-theoretic techniques, and gadget-based transformations. Despite no listed academic awards in the provided data, his prolific publication record reflects significant contributions to theoretical computer science and discrete mathematics. No student advisees or grant details were explicitly mentioned, though his group likely engages in funded research projects given the institutional context.

• Artificial Intelligence
• Optimization
• Machine Learning
• +۳ مورد دیگر

Sebastian Pokutta is a Professor at Technische Universität Berlin, Vice President at Zuse Institute Berlin (ZIB), and Chair of the Cluster of Excellence MATH+ and MODAL. His research focuses on artificial intelligence, optimization, and machine learning, with emphasis on algorithmic development, decision-making systems, and real-world applications in areas like satellite data analysis, quantum computing, and combinatorial mathematics. He leads a research group exploring AI-driven methodologies and their interdisciplinary applications. He holds academic positions including leadership roles in major institutions and has contributed to numerous high-impact publications in optimization, machine learning, and quantum computing. His work has been recognized with awards such as the Science Prize of the Association for Pediatric Orthopedics (VKO). Pokutta actively engages in academic outreach, delivering talks on optimization and AI, and contributes to open-source projects like the FrankWolfe.jl library. His research bridges theoretical foundations with practical implementations, addressing challenges in computational efficiency, mathematical modeling, and AI ethics.