Find Academic Supervisors

Helmar BaumView profile

Professor

• Media Management
• Media Economics
• Film and TV Production
• +3 more

Prof. Dr. Helmar Baum is a Professor of Media Management at Mediadesign University (mdh) since 2007, leading the Media Management department. He holds a PhD from Freie Universität Berlin (2003) on film selection decision parameters. As a film producer, he has produced seven feature films and multiple short films through Valerian Film GmbH, collaborating with studios like Warner Bros. and ProSiebenSat1. His teaching areas include Media Management, Financial Management, Marketing, and Digital Media Production. His research focuses on media economics, TV project management, and communication strategies. He co-authored key publications like the 2014 and 2013 Jahrbuch Medienmanagement , and explores scripted TV formats' sustainability. Active in academic governance as a member of the academic senate. Education: Dual degree in Business Administration (HWR Berlin) and Philosophy (TU Berlin), followed by a PhD at Freie Universität Berlin. Professional experience spans film production and academic leadership. His interdisciplinary approach bridges media theory and industry practice.

Christina BaderView profile

Part-Time Lecturer

• Curriculum development
• Didactic annual planning
• Teacher training
• +4 more

Dr. Christina Bader is a part-time lecturer at the Chair of Business Education (Prof. Dr. Karl-Heinz Gerholz) at the Otto-Friedrich University of Bamberg , where she teaches Practical School Studies and Didactics of Economics modules since 2023. She holds a Doctorate in Social Sciences (2020, Friedrich-Alexander University Erlangen-Nuremberg) and has been recognized with a Teaching Award in 2017. Education: M.Sc. in Business Education (Friedrich-Alexander University Erlangen-Nuremberg, 2015) B.A. in Economics (Friedrich-Alexander University Erlangen-Nuremberg, 2013) Research interests focus on curriculum development, teacher cooperation, didactic design in vocational education, and mathematics pedagogy. Her work explores digital transformation, resonance theory, and practical learning arrangements. Key projects include the EdUSchool triple helix model and tabletBS.dual studies on digital media effectiveness. Publications (2020–2024) address virtual learning, AI integration, and collaborative teaching practices. She contributes to the WisoVirtuell blog on remote learning strategies and has co-authored policy documents for European University School concepts. Scientific Awards: Teaching award of Friedrich-Alexander University Erlangen-Nuremberg (2017) Current roles include student teacher supervision at vocational secondary schools and research assistant experience (2015–2020) at Friedrich-Alexander University. She participates in the EdUSchool project and explores resonance research in educational contexts.

• Control Engineering
• Automation
• Model Predictive Control
• +5 more

Martin Steinberger is an Associate Professor at the Institute of Control and Automation (IRT) at Graz University of Technology (TU Graz). His work focuses on advanced control systems, networked control, model predictive control (MPC), and automation in manufacturing and autonomous systems. He leads research into real-time optimization, fault diagnosis, and safety-critical applications in industries like pharmaceuticals and automotive. Research interests include: Networked Control Systems Model-Based Control Autonomous Vehicle Trajectory Planning Process Automation Robotics and Industrial Automation His work bridges theoretical control engineering with practical applications in manufacturing lines, chemical processes, and autonomous driving. Recent studies emphasize digital real-time release testing for pharmaceuticals, universal control concepts for manufacturing systems, and safety-aware trajectory optimization for automated vehicles. His publications frequently address challenges in time-varying delays, packet loss mitigation, and robust observer design for nonlinear systems. Steinberger collaborates on EU-funded projects and regularly contributes to conferences like the International Workshop on Variable Structure Systems. His research often involves experimental validation, as seen in work with compact pharmaceutical manufacturing setups and small-scale autonomous vehicle testing platforms.

Chunming QiaoView profile

Professor

• Cyber-Physical Systems
• Optical Networks
• Wireless Networks
• +6 more

Dr. Chunming Qiao is a SUNY Distinguished Professor and Chair of the Department of Computer Science and Engineering at the University at Buffalo (SUNY) , leading the Lab for Advanced Network Design, Evaluation and Research (LANDR) since 1993. His work spans cyber-physical systems , optical networks , and Internet of Things (IoT) , with a focus on safety, reliability, and protocol design. Education: PhD in Computer Science from the University of Pittsburgh (1993) BS in Computer Science and Engineering from the University of Science and Technology of China (1985) Dr. Qiao’s research interests combine theoretical and applied network design, including autonomous vehicles , quantum computing , and cloud services . He pioneered optical burst switching (OBS) and iCAR systems for wireless convergence, cited in BusinessWeek and Wireless Europe . His recent publications emphasize quantum networking , federated learning , and autonomous driving security , with projects on entanglement routing , edge inference optimization , and LiDAR adversarial attacks . Articles span IEEE and ACM venues , and include best paper awards . Scientific Awards: TC-CSR Distinguished Technical Achievement Award (2015) SUNY Chancellor's Award for Excellence (2013) IEEE Fellow (2009) UB Exceptional Scholar-Sustained Achievement Award (2005) Dr. Qiao has secured over two dozen NSF grants and collaborations with Google , Cisco , and NEC Labs . His 7 US patents and consulting experience highlight his industry impact, while his editorial roles and conference leadership underscore academic influence. He actively contributes to multi-disciplinary research through the New York State Center of Excellence in Bioinformatics and Life Sciences and CEDAR , advancing high-performance computing and document analysis .

• Innovative Learning Environments
• Educational Philosophy
• Education Policy
• +3 more

Leon Benade is a Professor in the School of Education at Edith Cowan University (ECU). He holds a Doctor of Education from New Zealand (2012) and has established a national and international reputation in learning environments research. His work focuses on 21st-century learning imperatives, innovative teaching practices, and bicultural education policy. Benade is a Co-Investigator in the 2021 Marsden Fund project exploring Māori flexible learning spaces. He has received several awards, including the 2017 Emerging Researcher Award from AUT. **Research Interests** Innovative Learning Environments Educational Philosophy Teachers' Work Educational Policy Cultural Spaces in Education **Awards** 2017 Auckland University of Technology Emerging Researcher Award 2021 Marsden Fund Co-Investigator 2016 Innovation in Teaching Award Benade supervises PhD/Master's students on topics like sustainability education and rural Colombian education policy. He has held editorial roles at journals like New Zealand Journal of Educational Studies and New Zealand Journal of Teachers' Work . His recent publications (2021–2025) address Māori spatial pedagogy, flexible learning spaces, and peer review ethics in academic publishing.

• Pervasive Computing
• Wireless Sensor Networks
• Healthcare Informatics
• +3 more

John Herbert is a Senior Lecturer in Computer Science at University College Cork (UCC), Ireland. His research focuses on pervasive computing, wireless sensor networks, and healthcare informatics, with notable projects like the CARA framework for falls assessment in the elderly. He holds a PhD in Computer Science from Cambridge University and has held visiting roles at institutions including SRI International and the University of Cambridge. Education: BSc (Experimental Physics), MSc (Experimental Physics), Postgraduate Diploma (Computer Science) from UCC; PhD (Computer Science) from Cambridge University. Research Grants: Led projects funded by Science Foundation Ireland (€163,726) and the Irish Research Council (€71,250), focusing on cloud computing and healthcare applications. His work emphasizes context-aware systems, data quality in medical environments, and real-time analysis. Selected awards include an International Fellowship from Digital Systems Research Center (1989) and visiting fellowships at Cambridge (2008-2009). Teaching: Courses include Advanced Software Engineering, Formal Methods, and Model-Based Software Development. Outreach: Advisor to award-winning student teams (e.g., IEEE mobile app contest) and collaborator with industry partners in China and Europe.

Michael RitterView profile

Researcher

• Combinatorial Optimization
• Integer Programming
• Operations Research
• +4 more

Dr. Michael Ritter is a researcher and academic staff member at the Technical University of Munich (TUM), affiliated with the TUM School of Computation, Information and Technology and the Department of Mathematics. His primary role involves advising Master's students in Mathematics programs and coordinating administrative duties for academic affairs. He is part of the Discrete Optimization research group and collaborates with professors like Stefan Weltge and Peter Gritzmann on advanced optimization projects. His research focuses on Combinatorial Optimization, Integer Programming, and real-world applications such as flight schedule design, semiconductor manufacturing optimization, and logistics systems. He has contributed to projects involving automated driving systems, production network resilience, and low-power semiconductor design. Ritter teaches courses on Discrete Optimization and Case Studies in Optimization, balancing theoretical instruction with practical problem-solving. He has co-advised numerous theses on topics ranging from supply chain optimization to timetabling algorithms, demonstrating his commitment to both academic research and student mentorship. His work bridges mathematical theory with industrial applications, addressing challenges in manufacturing, transportation, and electronics through rigorous optimization frameworks. He maintains an active publication record in reputable journals and conferences, reflecting his expertise in interdisciplinary optimization research.

Karim BoutibaView profile

Research Fellow

• 5G Networks
• 6G Networks
• Network Slicing
• +4 more

Karim Boutiba is a Research Fellow at EURECOM's Communication Systems department, specializing in 5G/6G networks and advanced wireless technologies. His work focuses on optimizing network performance through machine learning, resource management, and network slicing. He contributes to both theoretical advancements and practical implementations, such as the 5G INSTRUCT forge pipeline and the GoSimRIS framework for 6G networks. His research interests span dynamic radio resource allocation, energy-efficient communication, and the integration of artificial intelligence in next-generation networks. Notable projects include leveraging deep reinforcement learning (DRL) for optimizing TDD patterns, O-RAN architectures, and edge computing solutions to enhance video streaming and latency-critical applications. Boutiba's publications emphasize the practical deployment of theoretical models, such as network slicing in Radio Access Networks (RAN) and anomaly detection using machine learning. His work bridges gaps between academic research and industry-ready solutions, with active participation in initiatives like the 6G-BRICKS architecture project.

Donatella SciutoView profile

Professor

• Electronic Design Automation
• Embedded Systems
• Multiprocessor Systems
• +5 more

Donatella Sciuto is a Full Professor of Computer Science and Engineering at Politecnico di Milano, serving as Executive Vice Rector overseeing research strategies. She holds a PhD from the University of Colorado, Boulder and an MBA from Bocconi University. Her research focuses on embedded systems design, low-power electronics, and cyber-physical systems, with contributions to smart cities and ICT infrastructure. Education: Bachelor's in Electronic Engineering, Politecnico di Milano (1984) PhD in Electrical and Computer Engineering, University of Colorado, Boulder MBA, SDA Bocconi School of Management Research Interests: Embedded systems, multiprocessor architectures, hardware/software co-design, power-efficient computing, and building automation via IoT technologies. She leads the Embedded Systems Design research group at Politecnico di Milano and coordinates EU-funded projects in smart cities and reconfigurable systems. Awards: IBM Women Leaders in AI (2021) IEEE Fellow (2011) EDAA Fellow (2010) Outstanding Contribution Award, IEEE Computer Society (2009) Professional Roles: Board Member: Bank of Italy, Istituto Italiano di Tecnologia, STM, Avio Former President, IEEE Council of Electronic Design Automation (2011-2013) Executive Committee Member, Design Automation and Test in Europe (DATE) conference Labs/Teams: Leads the Embedded Systems Design and Design Methodologies group at Politecnico di Milano, collaborating with CEFRIEL on executive education programs in embedded systems and IoT.

• Edge Computing
• Fog Computing
• Cloud Computing
• +4 more

Dragi Kimovski is a Habilitated Assistant Professor in Distributed Systems at Klagenfurt University, Austria, focusing on Edge Computing and AI. He previously held roles at the University of Innsbruck and the University of Information Science and Technology in Macedonia. His research spans Edge/Fog/Cloud computing, multi-objective optimization, and high-performance computing. He has coordinated major projects like 6GContinuum and KärtnerFog, and led initiatives such as DataCloud and ASPIDE. His teaching includes courses on Distributed Computing, Cloud Computing, and IoT. He is the co-creator of the Carinthian Computing Continuum and maintains a blog on Edge AI World. His work emphasizes sustainable and efficient computing solutions for emerging technologies. Education: Not explicitly listed in the provided text. Research Interests: Edge Computing, Fog Computing, Cloud Computing, Multi-objective Optimization, High-Performance Computing, AI in Distributed Systems. His work addresses challenges in resource management, latency reduction, and scalability across heterogeneous environments, with applications in healthcare, IoT, and 6G networks. Projects: 6GContinuum (Coordinator): Focuses on AI services over 6G networks. KärtnerFog (Scientific Coordinator): Develops adaptive Fog infrastructures over 5G. DataCloud (WP5 Leader): Manages Big Data pipelines on the Computing Continuum. ASPIDE (Scientific Coordinator): Advances exascale programming models for data processing. Teaching: Klagenfurt University: Courses include Distributed Computing, IoT, Cloud Computing, and Advanced Programming. University of Innsbruck: Taught Advanced Parallel and Distributed Systems. University of Information Science and Technology: Courses in High-Performance Computing and Network Architectures. Labs/Teams: Co-created the Carinthian Computing Continuum, an automated SDN testbed for Edge computing research. Active in interdisciplinary teams addressing extreme data processing and sustainable computing.

Zhuang ZhengView profile

Lecturer

• Smart Grids
• Building Energy Management
• Renewable Energy Systems
• +3 more

Dr. Zhuang Zheng is a Lecturer (Assistant Professor) at the School of Computing, Engineering & Digital Technologies, Teesside University since April 2024. Previously, he served as a Postdoc Fellow at the Hong Kong Polytechnic University’s Department of Building Environment and Energy Engineering. He holds a PhD in Architecture and Civil Engineering from City University of Hong Kong (2021). His research focuses on smart energy systems, particularly next-generation residential energy management, grid-building interactions, urban-scale energy modeling, and cyber-physical-social frameworks for low-carbon systems. Education: PhD (2021) from City University of Hong Kong; Postdoc (2021–2024) at Hong Kong Polytechnic University. Key Research Interests: Smart grids, building energy management, renewable energy integration, and decarbonization technologies. Notable contributions include novel energy modeling techniques for peak shaving, voltage regulation, and multi-scale urban energy systems. Articles Trends: His work spans smart building controls, IoT-enabled energy systems, stochastic optimization, and safety risk evaluation. Recent focus areas include distributed control strategies for HVAC clusters and voltage regulation in smart grids. Collaborations: Collaborated with Hong Kong Sun Hung Kai and AECOM on commercial building energy flexibility projects. Actively contributes to international journals and conferences, including chairing sessions at the International Conference on Applied Energy (ICAE). Future Directions: Developing intelligent digitalization for building, power, and transportation sectors to advance smart low-carbon systems through socio-technical integration.

• Combinatorial Optimization
• Approximation Algorithms
• Online Algorithms
• +3 more

Prof. Dr. Sven Oliver Krumke is a Full Professor of Mathematics and currently serves as Dean of the Faculty of Mathematics at the Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau (RPTU). His research focuses on Combinatorial Optimization, Approximation Algorithms, Online Algorithms, Complexity, Algorithmic Game Theory, and Graph Theory with Applications. He leads the Optimization Group (AG Optimierung) within the Department of Mathematics. Education and Academic Path: PhD (Dr. rer. nat.) in Mathematics, University of Würzburg (1997) Habilitation in Mathematics, Technische Universität Berlin (2002), Thesis: 'Online Optimization: Competitive Analysis and Beyond' Professor at RPTU since 2004 Research Projects: Principal investigator in the Research Training Group (GRK 2982) 'MIMO: Mathematics of Interdisciplinary Multiobjective Optimization' Project lead for 'ONE PLAN: Optimization in Emergency Medical Services in Rhineland-Palatinate' Teaching includes courses on Analysis, Mathematical Modeling in Economics, and Reading Courses. He supervises Bachelor's and Master's theses in Optimization-related topics. He has held roles such as Scientific Researcher at the Konrad-Zuse-Zentrum Berlin (1998–2004), and has extensive international collaborations, including a Fulbright-funded stay at SUNY Albany (1992–1993). His work emphasizes practical applications in healthcare logistics, emergency services optimization, and algorithmic solutions for real-world problems.

• Operational Research
• Computational Optimization
• Transportation Logistics
• +3 more

Emmanouil Zachariadis serves as an Associate Professor at the Department of Management Science and Technology (DMST) within the School of Business at Athens University of Economics and Business (AUEB). He specializes in operational research and computational optimization, focusing on transportation logistics, supply chain systems, and environmental impact minimization. Education : BSc in Chemical Engineering from National Technical University of Athens (NTUA) MSc in Computing Science from Imperial College London PhD in Chemical Engineering from NTUA His research integrates mathematical programming with optimization algorithms for operational challenges in transportation and production systems. He has published 26 articles in top-tier journals, accumulating over 1200 Scopus citations by June 2024. Recent scholarly trends emphasize vehicle routing problems with complex constraints (cross-docking, loading, time windows) and optimization methods for logistics sustainability. His work spans production-routing integration, emergency evacuation planning (EVITA project), and hybrid metaheuristics. Scientific Awards : Teaching excellence award for undergraduate course 'Optimization Methods in Management Science', Dept. of Management Science & Technology AUEB (2021-22) Teaching excellence awards for postgraduate course 'Large Scale Optimization', MSc in Business Analytics AUEB (2020-21, 2021-22, 2022-23) He has participated in European and National research projects, applying his expertise in supply chain optimization and sustainability. His teaching portfolio covers quantitative methods, operational research, and supply chain optimization at both undergraduate and postgraduate levels.

Matthias Pollmann-SchultView profile

Professor

• Family Research
• Labour Market Research
• Subjective Well-Being
• +1 more

Matthias Pollmann-Schult is a Professor of Sociology at the University of Siegen's Faculty of Social Sciences, specializing in Empirical Social Research. His work focuses on family dynamics, labor market impacts, and subjective well-being. Current research includes multi-country studies on nonstandard work schedules (NONWELL project) and subjective well-being differences between parents and nonparents in Germany and Europe. Research Interests: Family structures and transitions Labor market effects on family well-being Subjective well-being across life stages Quantitative analysis of social phenomena His recent publications demonstrate strong thematic focus on parental well-being, work-life balance, and intergenerational dynamics across European contexts. Research consistently incorporates longitudinal methods and cross-cultural comparisons. Current Projects: DFG-funded NONWELL study (2023-2026) on nonstandard work schedules Subjective well-being of parents/nonparents (DFG 2021-2024)

Hongjie WangView profile

Assistant Professor

• Power Electronics
• Electric Vehicle Charging
• Resonant Converters
• +2 more

Hongjie Wang is an Assistant Professor in Electrical and Computer Engineering at Utah State University, where he serves as co-director of the Utah State University Power Electronics Laboratory and leads the NSF ASPIRE ERC Charging Stations of the Future project. His research focuses on power electronics for transportation electrification, particularly extreme fast charging systems and dynamic wireless power transfer. Research domains include: High-efficiency resonant converter design Grid integration of EV charging infrastructure Second-life battery applications in energy storage Dynamic wireless power transfer for in-motion charging Thermal management of power electronics Recent publications demonstrate innovations in unfolding-based AC-DC converters, load modeling for large-scale charging infrastructure, and reinforcement learning approaches for grid-integrated charging optimization. His work has received multiple best paper awards including recognition from IEEE ECCE and IEEE IAS.