جست‌وجوی استاد و پژوهشگر

Anders Rantzerمشاهده پروفایل

استاد

• Control Systems Theory
• Scalable Control
• Adaptive Control
• +۷ مورد دیگر

Anders Rantzer is a Professor of Automatic Control at the Department of Control Engineering, Faculty of Engineering, Lund University, Sweden. He has held visiting positions at Caltech (2004–2005) and the University of Minnesota (2015–2016) as the Taylor Family Distinguished Visiting Professor. His academic journey began with a PhD from KTH Stockholm in 1991, followed by a postdoc at the Institute for Mathematics and its Applications (IMA), University of Minnesota. His research interests center on modeling, analysis, and synthesis of control systems , with a strong focus on scalability, adaptation, and applications in energy networks . He is particularly known for foundational work in positive systems and integral quadratic constraints (IQCs) . These theoretical frameworks are critical in analyzing stability and robustness of large-scale interconnected systems. His work bridges mathematical rigor with practical engineering applications, especially in sustainable energy and networked systems. The recent publications and lecture materials reflect a consistent trajectory in scalable and robust control, optimization, and distributed systems. Themes such as large-scale convex optimization , nonlinear and stochastic control , and network dynamics dominate his scholarly output, indicating a sustained commitment to advancing control theory for complex, real-world systems. Scientific honors include: Fellow of IEEE Member of the Royal Swedish Academy of Engineering Sciences (IVA) Chairman of the Swedish Scientific Council for Natural and Engineering Sciences Chairman of the Royal Physiographic Society of Lund Rantzer has supervised numerous students and contributed extensively to academic leadership and education. He has been involved in major national and international research initiatives such as WASP (Wallenberg AI, Autonomous Systems and Software Program) and ELLIIT. His work includes developing educational tools and courses in control, optimization, and machine learning. He leads and contributes to research projects on autonomous systems, cloud control, and smart energy networks. He is affiliated with the Control Lab at LTH and participates in collaborative efforts such as the Nordic University Hub on Industrial Internet of Things (HI2OT). His work integrates theoretical advances with practical implementations in robotics, biomedical systems, and industrial automation.

Björn Brandenburgمشاهده پروفایل

پژوهشگر

• Real-Time Systems
• Scheduling Algorithms
• Real-Time Operating Systems
• +۵ مورد دیگر

Björn Brandenburg is a researcher at the Max Planck Institute for Software Systems (MPI-SWS) in Kaiserslautern, Germany. His work focuses on real-time systems, scheduling algorithms, and operating system design, with a particular emphasis on predictable resource allocation and performance guarantees in multiprocessor and cyber-physical environments. His research interests include real-time response-time analysis (e.g., PROSA ), locking protocols for multiprocessor systems, side-channel mitigation in cloud environments, and the verification of real-time scheduling policies. He has contributed to foundational studies on deadline failure probabilities, self-suspending tasks, and predictable real-time Linux implementations. Scientific awards include recognition for outstanding papers on TimerShield (2017) Offline Equivalence (2017) . His work intersects with practical systems like LITMUSRT and ROS 2, aiming to bridge theoretical guarantees with real-world applications in safety-critical and distributed real-time systems.

• Medical Imaging
• Deep Learning Applications
• Ultrasound Imaging
• +۳ مورد دیگر

Mehrdad Salehi is a researcher at the Chair of Computer Science Applications in Medicine at the Technical University of Munich (TUM) . His work focuses on the intersection of computer science and medical imaging, with expertise in ultrasound technology, deep learning, and surgical navigation systems. Key research areas include sonification of medical data, 3D ultrasound reconstruction, and machine learning-based segmentation. He has contributed to innovative projects like PRO-TIP calibration phantoms and ColibriDoc autonomous docking systems. His publications highlight trends in acoustic feedback mechanisms, neural radiance fields for medical imaging, and real-time image analysis. He can be reached at mehrdad.salehi@tum.de .

Felix Motzoiمشاهده پروفایل

دانشیار

• Quantum Technologies
• Optimal Control Theory
• Machine Learning
• +۶ مورد دیگر

Prof. Felix Motzoi is an Associate Professor at the University of Cologne and Division Leader & Head of the 'Automatic Optimization, Control and Design' group at the Peter Grünberg Institute (PGI-8) in Jülich. His research focuses on advancing quantum technologies, including superconducting and semiconducting architectures, trapped cold atoms/ions, Rydberg qubits, and long-range entanglement. He leads theoretical efforts in quantum control theory, machine learning applications, hardware co-design, and error mitigation strategies. Key research areas include developing optimal control methodologies (e.g., DRAG, STA), numerical optimization, and dynamics modeling for quantum systems. His work bridges theoretical frameworks with experimental implementations, emphasizing practical solutions for scalable quantum computing. Recent publications highlight innovations in quantum gate design, error suppression via pulse shaping, and hybrid optimization techniques combining machine learning with physics-driven approaches. His team collaborates across disciplines to address challenges in qubit coherence, entanglement stabilization, and robust quantum processing.

Sylvia Kesper-Biermannمشاهده پروفایل

استاد

• Historical Education Research
• Comics and Education
• Post-Colonial Education
• +۵ مورد دیگر

Prof. Dr. Sylvia Kesper-Biermann is a Professor of Historical Educational Research at the University of Hamburg's Faculty of Education, specifically within the department of General, Intercultural and International Comparative Education and Educational Psychology (EW 1). She has held this position since 2017 and previously served in various academic roles at institutions such as Justus-Liebig University Giessen, Ludwig-Maximilians-Universität München, and the University of Cologne. Her research focuses on historical education, transnational educational spaces, comics as educational media, post-colonial education, and the history of human rights and emotions. Educationally, she studied Middle and Modern History, History Didactics, and Specialist Journalism at Universities of Siegen, Gießen, and Bristol. Her career includes roles as a research coordinator for the DFG Graduate School on Automatism, a research fellow at the University of Paderborn, and participation in multiple DFG-funded projects. Her research interests are interdisciplinary, emphasizing the intersection of education, history, and media. Recent work explores comics' role in language education for guest workers in West Germany, transnational colonial schools, and emotional dimensions of legal cultures. She has published extensively, including monographs like Einheit und Recht and edited volumes on Turkish-German educational discourse. Prof. Kesper-Biermann has received notable awards such as the Hamburger Lehrpreis 2023 and the Karl-Ferdinand-Werner Fellowship. She leads projects like PostKol (on post-colonial education) and ComBiMe (comics as educational media in West Germany). Her work bridges historical analysis with contemporary educational challenges, emphasizing visual literacy, migration studies, and transnational collaboration. Her academic contributions include organizing lecture series on pedagogy, sexuality, and body politics, as well as international conferences on education history and comics studies. She collaborates with institutions like the Comic Kolloquium Nord and the German Society for Comics Studies, fostering interdisciplinary dialogue in visual and educational historiography.

• Control Theory
• Optimization
• Machine Learning
• +۹ مورد دیگر

Andrea Iannelli is a Tenure-Track Assistant Professor at the Institute for Systems Theory and Automatic Control (IST) , University of Stuttgart, Germany. He also serves as a faculty member of the International Max Planck Research School for Intelligent Systems (IMPRS-IS) and participates in the Cluster of Excellence Data-Integrated Simulation Science (SimTech) . His research focuses on reconciling model-based and data-driven approaches for robust and adaptive control of uncertain dynamical systems. Ph.D. : Control and Dynamical Systems, University of Bristol (UK), 2019 Postdoctoral Researcher : ETH Zürich (Switzerland), 2019–2022 Harnessing the intersection of control theory, optimization, and machine learning , Iannelli’s work addresses data-driven modeling, uncertainty quantification, and robust control with applications in energy systems, intelligent transportation, and industry 4.0 . His recent publications highlight trends in LPV frameworks, online convex optimization, and hybrid control systems , emphasizing safety and efficiency. He contributes to the academic community as an Associate Editor for the International Journal of Robust and Nonlinear Control and as a member of international conference IPCs. His group, Trustworthy Autonomy for Smart Adaptive Systems (TASAS) , mentors PhD students in projects spanning adaptive control, uncertainty quantification, and reinforcement learning .

• Quantum Information Theory
• Quantum Many-Body Theory
• Quantum Optics
• +۷ مورد دیگر

Prof. Dr. Jens Eisert is a Professor at the Free University of Berlin, where he leads the Quantum Many-Body Theory, Quantum Information Theory, and Quantum Optics research group (Eisert AG) within the Institute of Theoretical Physics at the Dahlem Center for Complex Quantum Systems. His office is located at Arnimallee 14, Room 1.3.06 in Berlin-Dahlem. His research focuses on the intersection of quantum information theory and condensed matter physics, specifically exploring what information processing tasks are possible using individual quantum systems as information carriers. His group develops mathematical-theoretical foundations of quantum information, particularly in entanglement theory and tomography, while also investigating quantum optical implementations using light modes or cold atoms in optical lattices. A major emphasis of their work is on quantum many-body systems, including static properties, efficient numerical simulation methods like tensor networks, and non-equilibrium quantum dynamics. Recent publications highlight significant contributions in thermalization of quantum systems (Communications Physics 2025), quantum thermodynamics (Nature Physics 2025), and quantum error correction (PRX Quantum 2025). The group's work is characterized by combining the rigor of mathematical physics with physically motivated applicability, frequently leading to direct collaborations with experimental groups. Quantum Information Theory Quantum Many-Body Theory Quantum Optics Entanglement Theory Tensor Networks Quantum Error Correction Prof. Eisert maintains active supervision of numerous PhD students and postdoctoral researchers, with research positions regularly available in areas including quantum error correction, quantum information theory, tensor networks, and quantum simulation. His group has published extensively in top journals including Nature Physics, PRX Quantum, and Physical Review series.

Matthias Krauledatمشاهده پروفایل

استاد

• Machine Learning
• Brain-Computer Interface
• Signal Processing
• +۳ مورد دیگر

Prof. Dr. Matthias Krauledat is a faculty member at Hochschule Rhein-Waal , specifically within the Faculty of Technology and Bionics . His academic career spans both theoretical research and industrial application, with a focus on Machine Learning and Brain-Computer Interfaces . After completing his PhD in Electrical Engineering/Computer Science at Technische Universität Berlin , he has contributed significantly to the advancement of EEG-based communication systems and neural signal processing methodologies. Born in Essen, Germany Studied Mathematics with a minor in Computer Science at University of Münster/Oxford Doctoral research at TU Berlin on Brain-Computer Interfaces Industrial experience at Henkel AG & DMT GmbH Research Interests focus on Machine Learning applications in Neuroscience and Biomedical Engineering , specifically Brain-Computer Interfaces , EEG Signal Processing , and Adaptive Classification Systems . His work explores how algorithms can be developed to enable self-learning computers to solve complex tasks involving neural data interpretation and prediction for previously unseen data in clinical and technological contexts. Publications demonstrate a consistent contribution to Neuroscience and Machine Learning fields, with particular emphasis on Brain-Computer Interface systems from 2004 through 2009. His research has focused on reducing training requirements, improving signal processing accuracy, and developing novel interaction paradigms like the Hex-o-Spell mental typewriter while addressing statistical challenges like covariate shift in neural data analysis. Professional Experience includes academic research at TU Berlin's Intelligent Data Analysis group, industrial software development roles at Henkel AG's Scientific Computing department, and TÜV Nord Group's Optical Metrology and Machine Diagnostics divisions. He maintains active research connections through collaborative publications with leading experts in the field.

• Control Theory
• Distributed Parameter Systems
• Model Predictive Control
• +۳ مورد دیگر

Lorenz Dörschel is an Adjunct Professor (Lehrbeauftragter) at the Institute of Automatic Control at RWTH Aachen University. He holds the academic title PD Dr.-Ing. habil, signifying post-doctoral research qualifications. His position is part-time, focusing on advanced control theory and applications. His primary research interests include: Control of distributed parameter systems (e.g., fluid dynamics, thermal processes) Model predictive control for industrial and automotive systems Parameter space methods for robust controller design Model reduction techniques for complex nonlinear systems Dörschel's recent publications (2018-2024) demonstrate broad applications across biomedical engineering, renewable energy, automotive systems, and industrial automation. His work consistently integrates mathematical rigor with practical implementations, emphasizing advanced control methodologies like nonlinear MPC, Lyapunov-based design, and Bayesian optimization. A recurring theme is the development of computationally efficient control strategies for distributed parameter systems. No scientific awards, student advising relationships, or research grants are documented in the available information.

Michael Finkمشاهده پروفایل

پژوهشگر

• Control Theory
• Automation and Robotics
• Agricultural Engineering
• +۴ مورد دیگر

Michael Fink is a researcher at the Chair of Automatic Control Engineering , Technical University of Munich . He holds an M.Sc. in Electrical Engineering and Information Technology (2020) and a B.Eng. in the same field from Technical University Munich and University of Applied Sciences Landshut (2018), respectively. Research Interests : Model Predictive Control (MPC) with focus on stochastic and robust variants Optimal control strategies for autonomous driving and vertical farming Constraint violation probability minimization in dynamic systems Publications span topics in: Time-optimal MPC for linear systems Stochastic and robust MPC frameworks Learning-based control for greenhouse climate systems Vertical farming optimization Contact: michael.fink@tum.de

Nicki Marquardtمشاهده پروفایل

استاد

• Industrial and Organizational Psychology
• Human Error
• Situational Awareness
• +۷ مورد دیگر

Prof. Dr. Nicki Marquardt is a Professor of Industrial and Organizational Psychology at the Rhine-Waal University of Applied Sciences , affiliated with the Faculty of Communication and Environment at the Kamp-Lintfort Campus. He has been in this role since 2010 and has played a key role in developing both the Bachelor's program in Industrial and Organizational Psychology and the English-taught Master's program in International Management and Psychology. His research and professional work focus on: Human error and error prevention Situational awareness Crew Resource Management (CRM) Safety culture Implicit cognition Business ethics He investigates how unconscious mental processes influence ethical decision-making and organizational safety, particularly in high-risk industries such as aviation, automotive, and healthcare. His recent publications highlight trends in safety culture transformation, mental readiness under stress, and the adaptation of CRM training across sectors. His work bridges experimental psychology with practical organizational interventions, emphasizing measurable improvements in human performance and safety. He has received his doctorate from Leuphana University of Lüneburg in 2009 on the topic of unconscious processes in ethical management decisions and previously contributed to research at the Institute for Experimental Business Psychology (LüneLab). He has also worked as an independent consultant, trainer, and researcher in human factors and safety culture. Prof. Marquardt actively presents at international conferences and publishes in peer-reviewed journals such as Human Factors and Ergonomics in Manufacturing & Service Industries and Journal of Business Ethics . He supports international companies in applying psychological insights to enhance performance and transform organizational cultures.

Charlotta Johnssonمشاهده پروفایل

استاد

• Automation
• Control Systems
• Production Systems
• +۷ مورد دیگر

Charlotta Johnsson is a Professor in Automatic Control and Dean of Campus Helsingborg at Lund University, affiliated with the Department of Control Engineering within the Faculty of Engineering (LTH). She has been with the department since 1993, with a brief period in industry, and has held leadership roles in education, research, and external engagement. Her research focuses on automation, control and production systems, technology management, engineering leadership, and innovation in higher education. She is actively involved in national and international standardization efforts, particularly as Chair of ISO TC184/SC5, and leads several Vinnova-funded research projects related to digitalization, smart industry, and human-centered methodologies. Charlotta has received multiple scientific awards, including the prestigious Process Automation Hall of Fame (2016) and the Carlo Guido Stella Award (2012), recognizing her contributions to industrial automation and control systems. She has also been a pedagogical consultant at LTH's Genombrottet center and led the cross-disciplinary Technology Management program from 2008 to 2015. She is engaged in entrepreneurship, serving as co-founder of SESAM-Sweden and holding board memberships in Innovation Skåne AB, Novotek AB, and the Executive Foundation Lund. Her external activities include active participation in ISO, ISA, IEC, and WBF standardization bodies, contributing to frameworks for smart manufacturing and enterprise-control system integration. Process Automation Hall of Fame, 2016 Familjen Knut och Ragnvi Jacobssons stiftelse (Stipendium), 2014 Carlo Guido Stella Award, 2012 Knut och Alice Wallenberg stiftelse (Stipendium), 2001 Charlotta supervises Master’s thesis projects and contributes to PhD-level teaching, particularly in research and value creation. She has also been involved in numerous national and international research projects funded by Vinnova and other agencies, aligning her work with Lund University’s vision and the UN’s sustainability goals. Her lab and project involvements include initiatives like 'Mind Methodology', '4S: Standards and Strategies for Smart Swedish Industry', and 'På människa för människa', emphasizing human-centered innovation and industrial digitalization.

Victor Gabriel Lopez Mejiaمشاهده پروفایل

پژوهشگر

• Control Theory
• Machine Learning
• Multi-Agent Systems
• +۳ مورد دیگر

Dr. Victor Gabriel Lopez Mejia is a postdoctoral researcher at the Institute of Automatic Control Engineering, Faculty of Electrical Engineering and Computer Science, Leibniz University Hannover. His work focuses on data-driven control systems, reinforcement learning, and multi-agent system synchronization. PhD in Electrical Engineering (2019), University of Texas at Arlington M.Sc. in Electrical Engineering (2013), CINVESTAV, Mexico B.Sc. in Telecommunications and Electronics (2010), Universidad Autonoma de Campeche Research interests include: Neural network applications in control systems Reinforcement learning for cooperative control Game-theoretic analysis of multi-agent systems Data-based modeling of nonlinear dynamics Publications highlight advancements in data-driven predictive control, Gaussian process-based estimation, and nonlinear system analysis, with recent work in IEEE Transactions on Automatic Control and conferences like CDC and ECC. He has held academic roles including Adjunct Professor at the University of Texas at Arlington and Research Assistant at UTARI (2016-2019).

• Wireless Communication
• Machine Learning
• Signal Processing
• +۴ مورد دیگر

Prof. Dr. Haris Gačanin is a faculty member at RWTH Aachen University, affiliated with the Institute for Distributed Signal Processing under the College of Electrical Engineering. His research focuses on integrating machine learning with wireless communication systems, particularly in industrial IoT, edge computing, and network optimization. Current academic rank: Professor Contact: harisg@dsp.rwth-aachen.de Research Interests: Wireless systems, machine learning, signal processing, and network optimization. Key contributions include: Adaptive resource allocation in IIoT and vehicular networks AI-driven channel estimation and feedback mechanisms Security-oriented emitter identification via metric learning Federated/transfer learning for edge environments Hardware-efficient deep learning models for mmWave and THz communications Methodological Focus: Combines reinforcement learning, attention mechanisms, and robust neural architectures with practical implementations on FPGA and vehicular systems.

Dongheui Leeمشاهده پروفایل

استادیار

• Human motion understanding
• Physical human-robot interaction
• Machine learning in robotics
• +۵ مورد دیگر

Dongheui Lee is an Assistant Professor at the Institute of Automatic Control Engineering (LSR) within the Faculty of Electrical Engineering and Information Technology at Technische Universität München (TUM). She leads the Dynamic Human Robot Interaction for Automation System Lab. Her research focuses on human motion understanding, physical human-robot interaction, and machine learning in robotics. Education: B.S. and M.S. in Mechanical Engineering from Kyunghee University (2001-2003), PhD in Mechano-Informatics from the University of Tokyo (2007). Prior roles include research scientist at KIST Korea (2001-2004) and project assistant professor at the University of Tokyo (2007-2009). Research Interests: Human-robot collaboration, probabilistic robotics, motion recognition, and incremental lifelong learning mechanisms. She has contributed to advancements in motion primitives, compliant physical interaction, and real-time object tracking. Selected Awards: Finalist for KUKA Service Robotics Best Paper Award (2009), Hirose Scholarship (2006-2007), and multiple grants from KRF, KOSEF, and international robotics competitions. Key Publications: Focus on prioritized inverse kinematics, motion imitation, and adaptive control systems. Her work bridges robotics theory and practical applications in humanoid robots and human-robot interaction.