Find Academic Supervisors

• AI for Networking
• Edge Computing
• Federated Learning
• +4 more

Prof. Xiaoming Fu is a Professor at the Institute of Computer Science, University of Göttingen, and Head of the Computer Networks Group. He also holds a secondary membership in the Center for Statistics. His research focuses on AI-driven networking, edge computing, federated learning, and video analytics. He teaches courses such as 'AI-Empowered Networking and Mobile Communications' and oversees multiple seminars and internships on topics like smart cities and network optimization. His work spans technical innovations in multi-agent systems, low-latency services, and resource-efficient machine learning. Recent articles highlight contributions to neural-optimized video streaming, privacy-preserving MARL, and cross-modal social media analysis. He collaborates on interdisciplinary projects involving mobility data, socioeconomic analysis, and quantum networks. Prof. Fu’s research integrates reinforcement learning, network architecture design, and distributed systems to address challenges in 5G/6G, IoT, and smart cities. His lab develops solutions for edge-cloud orchestration, video quality adaptation, and resilient resource allocation, with applications in both academia and industry.

• Optimal Transport
• Mathematical Optimization
• Machine Learning
• +3 more

Prof. Bernhard Schmitzer is a Professor at the Institute of Computer Science, University of Göttingen. He leads the Optimal Transport research group and is a member of the Campus Institute Data Science (CIDAS). His work focuses on developing mathematical frameworks and algorithms for optimal transport theory, with applications in data analysis, image processing, and computational mathematics. He teaches courses such as the Journal Club Optimal Transport for Data Analysis , Scientific Writing , and Visualization . His research integrates geometric methods, stochastic systems, and numerical optimization to address complex problems in healthcare imaging and theoretical modeling. Key contributions include advancements in entropic transport kernels, domain decomposition techniques, and applications in medical imaging (e.g., PET and tomography). Despite his extensive publication record, no scientific awards are explicitly mentioned. He collaborates on interdisciplinary projects involving CIDAS and oversees the Optimal Transport research group at the university.

Dennis SchlegelView profile

Professor

• Digital Transformation
• Project Management
• Business Consulting
• +5 more

Prof. Dr. Dennis Schlegel is a Professor of Business Informatics at the Faculty of Informatics (Fakultät Informatik) at Hochschule Reutlingen. He serves as Pro-Dean/Deputy Dean and specializes in Digital Transformation, Project Management, and Business Consulting. His academic career includes roles as a Senior Manager at KPMG (2010-2019) and a PhD from Leeds Beckett University (2014). He holds international academic credentials including degrees from DHBW Stuttgart and study periods in Sydney and Madrid. Research focuses on robotic process automation (RPA), AI integration in business processes, and data-driven cultural transformation. Key interests include evaluating risks and success factors in digital initiatives like RPA and AI projects, as well as hybrid project management methodologies. He also explores sustainability in digital applications, such as gamified mobile apps for eco-friendly grocery shopping. Publications emphasize challenges in RPA implementation, skill requirements for digital transformation, and failure factors in AI projects. Recent work proposes frameworks for corporate AI strategy and data-driven cultural change. His articles frequently analyze organizational adoption barriers and expert-driven risk assessments in emerging technologies. Teaching emphasizes foundational business administration, managerial accounting, and business consulting practices. He contributes to bachelor's and master's programs in Business Informatics, integrating practical industry insights into curriculum design. Laboratory affiliations include the Future Mobility and Software Engineering labs at Reutlingen University.

Johannes ReuterView profile

Professor

• Control Engineering
• Autonomous Systems
• Maritime Control
• +3 more

Prof. Johannes Reuter is a Professor in the Department of Control Engineering at Konstanz University of Applied Sciences and a member of the Institute for System Dynamics (ISD). He serves as Vice Dean and Dean of Studies for the Electrical Systems M.Eng. program. His expertise includes control engineering, tracking, and multi-sensor data fusion. Reuter holds a doctorate in Automatic Control and System Dynamics from Berlin Technical University. Before joining Konstanz in 2007, he worked at IAV GmbH, IAV Automotive Engineering (USA), and Eaton Corp.'s Innovation Center (USA). His research focuses on autonomous systems, maritime control, and optimization algorithms, with contributions to conferences like ICRA and journals such as the Journal of Ocean Engineering. He leads projects on energy-efficient autonomous vessels (Solgenia) and advanced control strategies for dynamic systems. Education: Studied Mathematics/Physics at Bielefeld University Electrical Engineering degrees from Bielefeld University of Applied Sciences and Berlin Technical University Doctorate in Automatic Control and System Dynamics, Berlin Technical University Research Interests: Reuter’s work bridges theoretical control engineering with practical applications, emphasizing autonomous systems, maritime robotics, and sensor data fusion. Key areas include model predictive control (MPC), trajectory optimization, and energy-efficient vessel design. His research often integrates advanced algorithms like MPPI (Model Predictive Path Integral) for stochastic systems and develops methods for extended object tracking using LiDAR and radar sensors. Publications: Recent work highlights energy-optimal vessel docking, trajectory planning with signal temporal logic, and extended object tracking. His articles reflect a focus on interdisciplinary solutions combining control theory, robotics, and sensor technology. Awards/Grants: No specific awards listed, but his work is supported through academic and industrial collaborations. Labs/Teams: Active in the Institute for System Dynamics (ISD), Konstanz, which focuses on control systems, signal processing, and dynamic optimization across robotics, marine systems, and energy management.

Julius KeylView profile

Physician Scientist

• Oncology
• Artificial Intelligence in Medicine
• Cancer Treatment Personalization
• +5 more

Julius Keyl is a Medical Doctor working as an oncologist at University Hospital Essen and a data scientist in the IKIM TIO group (Institute for AI in Medicine) in Germany. His primary focus is on developing personalized treatment strategies for cancer patients using large, multimodal datasets to build longitudinal prediction platforms that guide clinical decisions from initial diagnosis through a patient's treatment path. His work specifically targets identifying patients at increased risk for side effects and relapse to enable more proactive interventions. Dr. Keyl's research spans the critical intersection of clinical oncology and advanced artificial intelligence. His work integrates clinical records, imaging data, and molecular profiles to create data-driven approaches for cancer care. Key methodologies in his research include explainable AI techniques, vision transformer models for medical image analysis, and multimodal data fusion approaches that combine diverse clinical data sources into cohesive predictive frameworks. Analysis of his publication record reveals a strong trajectory in applying cutting-edge AI to oncology challenges. His research demonstrates consistent progression from foundational medical imaging analysis (CellViT series) to comprehensive pan-cancer treatment outcome prediction systems. A notable trend is his focus on clinical implementation, with multiple studies emphasizing real-world applicability and integration into clinical workflows through standards like FHIR. His work increasingly incorporates explainability to build trust in AI systems among clinicians. Dr. Keyl collaborates extensively with leading researchers across University Hospital Essen, including Professor Jens Kleesiek (Professor of Translational Image-guided Oncology), Michael Forsting (Chair of Radiology Department), and experts from Urology, Nuclear Medicine, and other clinical departments. His interdisciplinary teams consistently bridge clinical medicine with advanced computational techniques to address practical oncology challenges.

Henning SchröderView profile

Researcher

• Chemometrics
• Multivariate Curve Resolution
• Reaction Kinetics
• +7 more

Dr. Henning Schröder is a researcher at the University of Rostock, actively involved in teaching and research in the fields of chemometrics, numerical methods, and spectroscopic data analysis. He teaches courses such as Numerik 1, Numerik 2, and Mathematics for Engineers and Economics, indicating a strong foundation in applied mathematics and computational science. His research focuses on multivariate curve resolution (MCR) , reaction kinetics , and ambiguity analysis in chemical systems . He applies advanced mathematical and computational techniques to interpret complex spectroscopic data, particularly in reaction monitoring and photochemical systems. His work often addresses challenges such as rotational ambiguity, constraint optimization, and noise reduction in spectral data. The recent publication trends show a consistent focus on chemometric modeling, with applications in NMR data correction, photochemical systems, and synthetic chemistry. His interdisciplinary approach bridges chemistry, mathematics, and data science, contributing to both theoretical advancements and practical algorithms in chemical data analysis. Selected Scientific Contributions: Development of dual Borgen plots for feasible solution analysis Multi-objective optimization for NMR spectral correction Analysis of quantum yields in photoisomerization Soft constraints in MCR for ambiguity reduction Kinetic modeling under rate constant uncertainty Dr. Schröder collaborates extensively with researchers such as K. Neymeyr, M. Sawall, and A. Börner, and has contributed to book chapters in major reference works like Comprehensive Chemometrics . Although no formal advising or grant information is available, his publication record suggests active involvement in research projects and academic supervision. He maintains regular office hours and is reachable via email at the University of Rostock.

• Software Engineering
• Agile Methods
• Embedded Systems
• +3 more

Adilson Marques da Cunha is a Professor at the Brazilian Aeronautical Institute of Technology (ITA), with a focus on software engineering and computational systems. His career spans academic research and development in embedded systems, real-time applications, and machine learning methodologies. Affiliation: Brazilian Aeronautical Institute of Technology Research Interests: Dr. da Cunha's work centers on agile software development , embedded system optimization , and numerical integrator frameworks . He has contributed to deep reinforcement learning for robotics and recommender systems for news, while also exploring climate prediction models using big data. Publication Trends : 2025 papers focus on universal numerical integrators and Python testing frameworks; 2024 work involves autonomous air navigation; 2022 studies include humanoid robotics and climate modeling

Sarvarbek EltazarovView profile

Researcher

• Agricultural Insurance
• Climate Change
• Risk Management
• +5 more

Sarvarbek Eltazarov is a Researcher at the Institute of Agricultural Development in Central and Eastern Europe (IAMO) , affiliated with the Department of Agricultural Markets, Marketing and World Agricultural Trade. He joined IAMO in 2018 and holds a Ph.D. in Agricultural Science from Martin-Luther-University of Halle-Wittenberg. Ph.D., Agricultural Science, Martin-Luther-University of Halle-Wittenberg (Germany) M.Sc., Agricultural Science, Wageningen University (Netherlands) B.Sc., Agricultural Engineering, Tashkent Institute of Irrigation and Melioration (Uzbekistan) His research focuses on climate resilience , index-based agricultural insurance , and earth observation , with expertise in machine learning and geographic information systems (GIS) . Recent work explores spatial downscaling of climate data to improve insurance risk models. Publications highlight his innovative use of satellite-based climate data , machine learning , and GIS in agricultural insurance development across Central Asia. He contributes to projects like DETECCT (climate crisis management) and KlimALEZ (agricultural insurance innovation).

Anna WolfView profile

Researcher

• Economic Analysis
• Industry Analysis
• Macroeconomic Forecasting
• +5 more

Dr. Anna Wolf serves as Specialist for Industry Analyses at the ifo Center for Innovation Economics and Digital Transformation since January 2021, following her role as Specialist for Forecasts and Industry Analyses at the ifo Center for Macroeconomics and Surveys (2012-2020). Her expertise spans economic analysis, industry studies, and business climate assessment with particular focus on retail, manufacturing, and crafts sectors across the German economy. Her academic foundation includes: PhD (Dr. oec. publ.) in Economics from Ludwig-Maximilians-Universität München (2005-2009) Diploma in Statistics and Developmental Sociology (1996-2002) with thesis on "Factors Influencing Subjective Poverty in Russia" State-certified translator for Russian language from Universität Erlangen-Nürnberg Study abroad at National University of Ireland, Galway (2000-2001) Dr. Wolf's research centers on macroeconomic forecasting, industry-specific analysis, and digital transformation impacts. She has established herself as a leading expert on business climate indicators, particularly for the chemical industry, with regular commentary on economic trends. Her recent work examines blockchain adoption (rising from 6.9% to 9.7% of German companies 2023-2025) and AI implementation (13.3% of companies as of 2023), analyzing how emerging technologies reshape business processes. Analysis of her publication record reveals consistent focus on real-time economic challenges, from the global financial crisis through pandemic disruptions to current geopolitical tensions. Her research methodology combines quantitative economic analysis with sector-specific surveys, producing actionable insights for policymakers and industry stakeholders. The thematic evolution shows increasing attention to digital transformation alongside traditional macroeconomic forecasting. Her major research projects include: "Web3-Durchdringung in der deutschen Wirtschaft" (2023), commissioned by Hanseatic Blockchain Institute e.V. for Federal Ministry for Economic Affairs and Climate Action "Gemeinschaftsdiagnose 2016-2018" funded by Federal Ministry for Economic Affairs and Energy As a prominent economic commentator, Dr. Wolf regularly interprets business climate data for media outlets and policymakers, bridging academic research with practical business applications through her industry expertise and methodical analysis approach.

Mutahira KhalidView profile

Researcher

• Semantic and Web Technologies
• Data Retrieval and Search Systems
• Neuro-symbolic AI
• +2 more

Mutahira Khalid is a Researcher at the Knowledge Infrastructures Lab under the German National Library of Science and Technology (TIB). With a Master’s degree in Information Technology from NUST Pakistan and a Bachelor’s in Information Technology from UAF Pakistan, her work focuses on neuro-symbolic AI frameworks for enhancing scientific data usability. Education: MSc & BSc in Information Technology Research: Semantic Technologies, Knowledge Graphs, Medical Data Systems Her publications highlight the application of knowledge graphs in medical data interoperability, neuro-symbolic approaches to trustworthy medical coding, and NLP-driven comorbidity risk scoring. She actively contributes to open science through her work on explainable AI systems for clinical code prediction. Contact: mutahira.khalid@tib.eu

• Production Management
• Circular Economy
• Artificial Intelligence in Manufacturing
• +4 more

Prof. Dr.-Ing. Florian Stamer is a Professor of Production Management at the Institute for Production Engineering and Systems (IPTS) at Leuphana University of Lüneburg. His work integrates AI methods with production and quality management to enhance profitability while reducing resource consumption for circular value chains . He has held academic roles at Karlsruhe Institute of Technology (KIT) and now leads research at Leuphana. Education B.Sc. Industrial Engineering (Mechanical Engineering) – RWTH Aachen University (2014) M.Sc. Industrial Engineering (Mechanical Engineering) – RWTH Aachen University (2017) Dr.-Ing. (Doctorate in Engineering Sciences) – KIT (2022, Summa cum Laude) Research Focus : Production Networks : AI-driven price/delivery time optimization, scenario simulation of global value structures Production Systems : Digital twins for layout planning, lean-digitalization integration, cognitive systems for adaptive disturbance response Quality Management : Component quality in circular production, data-driven test planning Scientific Contributions : Developed data models for process robustness in deep-drawing tools (2024-2025) Advanced AI applications in 5G-enabled manufacturing (EVOLVE5G, USIN5G) Optimized magnesium nanocomposites and fiber-metal laminates (2018-2022) Awards Summa cum Laude Doctorate – KIT (2022) Research Affiliate – CIRP (2023-present) Industry Collaboration : Works closely with industrial partners through third-party funding and consulting projects, translating academic insights into practical applications.

Alexandra ReichenbachView profile

Research Professor

• Cognitive Neuroscience
• Neuroinformatics
• Artificial Intelligence in Mental Health
• +6 more

Prof. Dr. rer. nat. Alexandra Reichenbach is a Research Professor for Neuroinformatics at Heilbronn University of Applied Sciences and an Associate Professor at Heidelberg University's Medical Faculty . As Director of the Center for Machine Learning (ZML) , she leads the "Motor Control & Artificial Intelligence in Mental Health" research group and chairs HHN's Ethics Board. Her research bridges cognitive neuroscience and artificial intelligence , focusing on: Human sensorimotor function and its neural basis AI-driven biomarker development for psychiatric disorders (depression, schizophrenia) EEG and fMRI-TMS multimodal neuroimaging Robot-assisted motor rehabilitation technologies Neuroethics of AI in clinical diagnostics Recent work includes GAN-based schizophrenia classification , EEG biomarker optimization , and Alzheimer's disease stratification models . She advocates for interdisciplinary AI education , co-developing HHN's Applied AI bachelor's program and planning its master's/doctoral expansion. Key collaborations include: Heidelberg Medical Faculty Human Robotics Group at Imperial College National Hospital for Neurology and Neurosurgery Medical Informatics Master Seminar (Heidelberg/HHN partnership) Her lab (ZML) integrates virtual AI experimentation environments for both research and public education, including interactive AI & Society installations.

Brigitte PolzinView profile

Lecturer

• Change Management
• Business Process Optimization
• Leadership
• +3 more

Dr. Brigitte Polzin is a lecturer at Hochschule für Wirtschaft und Umwelt Nürtingen-Geislingen (HfWU), where she contributes to teaching in the areas of leadership, change management, and business process optimization. Her academic engagement reflects a strong focus on organizational performance and innovation-driven management practices. Her research and teaching interests include: Change Management Business Process Optimization Performance and Innovation-Focused Leadership Organizational Development While no recent publications are listed in the provided text, her expertise appears centered on practical and strategic aspects of modern management and operational improvement in business contexts. Dr. Polzin has not been mentioned as receiving any scientific awards in the available information. There is no public information provided regarding student advisement, research grants, or formal academic supervision roles. Similarly, no details about labs, research teams, or collaborative projects are available in the current data.

Manfred WojciechowskiView profile

Professor

• Web Technologies
• Software Engineering
• Ambient Assisted Living (AAL)
• +3 more

Prof. Dr. Manfred Wojciechowski is a full-time Professor of Computer Science at the Düsseldorf University of Applied Sciences since April 2013. He has served as Vice President for Research and Transfer since November 2020. Research Focus: Development and implementation of Ambient Assisted Living (AAL) technologies, including context-adaptive systems, sensor networks, and non-functional feature implementation in web applications. Teaching Expertise: Web engineering, software development, and assistive technology implementation through modules like Web Engineering , Web Frameworks , and Web Apps . Publication Trends: His work spans web technologies, context-aware systems, and AAL applications, with a focus on context modeling , middleware architectures , and smart environments from 2006-2022.

• Production Engineering
• Electrical Engineering
• Industry 4.0
• +5 more

Dr. Andreas Zedler is a Researcher at Leuphana University Lüneburg's Institute for Production Engineering and Systems (IPTS), where he bridges practical craftsmanship with advanced scientific research. His unique career trajectory spans from electrical installation apprenticeship to doctoral work in technical optics, creating a distinctive perspective that informs both teaching and research. Apprenticeship: Electrical installer (1980s) Bachelor: Applied Automation Technology, Northeast Lower Saxony University of Applied Sciences Master: Applied Computing, Northeast Lower Saxony University of Applied Sciences/University of Wolverhampton Doctorate: Dr. rer. nat. in technical optics His research integrates hands-on engineering experience with cutting-edge academic inquiry, focusing on production engineering systems where he leads projects addressing Industry 4.0 challenges, material forming processes, and digital competence development. Zedler's work consistently connects theoretical frameworks with practical implementation, particularly in remote laboratory systems and AI-driven manufacturing optimization. Recent publications reveal a strong trend toward data-driven process optimization, with 60% of his recent work incorporating AI/ML methodologies applied to manufacturing challenges. His research spans materials science (particularly magnesium nanocomposites and copper conductors), sensor fusion systems, and educational technology for engineering education, demonstrating remarkable interdisciplinary range while maintaining focus on practical industrial applications. Teaching Award recognizing innovative pedagogical approaches Zedler actively mentors students through bachelor's and master's thesis supervision at IPTS, while leading multiple collaborative research initiatives including BMBF-funded projects like PROMINT_40 for women in STEM and TrICo for sustainable production communities. His work connects academic research with industry through SME partnerships focused on 5G implementation and digital transformation. He contributes to Leuphana's technical infrastructure development, particularly in remote laboratory systems for electrical engineering education and the 10 MN extrusion press facility for advanced materials research, supporting both educational programs and industrial collaboration projects.