جست‌وجوی استاد و پژوهشگر

Jan Petersمشاهده پروفایل

استاد

• Robot Learning
• Reinforcement Learning
• Imitation Learning
• +۵ مورد دیگر

Jan Peters is a full professor (W3) at the Computer Science Department of Technische Universität Darmstadt and serves as the department head of the Systems AI for Robot Learning (SAIROL) at the German Research Center for AI (DFKI) . He is also a founding faculty member of the Hessian Centre for Artificial Intelligence . Peters holds a Ph.D. in Computer Science from the University of Southern California (2007) and dual master’s degrees in Computer Science and Electrical Engineering from USC and TU Munich respectively. Research Themes : Robot Learning, Reinforcement Learning, Imitation Learning, Tactile Sensing, Human-Robot Interaction, and Safe AI. Recent Article Trends : Focus on deep reinforcement learning (Iterated Q-Networks, Adaptive Q-Networks), safe robot foundation models , tactile-enhanced imitation learning , and physics-informed machine learning . Scientific Recognition : Recipient of the Dick Volz Best PhD Thesis Award , ERC Starting Grant , IEEE Fellow , and Amazon Research Award . Leadership : Founder of the IEEE RAS Technical Committee on Robot Learning and editor for journals including Autonomous Robots and IEEE Transactions on Robotics .

• Human-Automation Interaction
• Human-Robot Interaction
• Robot Anthropomorphism
• +۶ مورد دیگر

Linda Onnasch is an Assistant Professor at Humboldt Universität zu Berlin in the Department of Engineering Psychology since 2017. She specializes in human-automation and human-robot interaction, focusing on function allocation, automation reliability, anthropomorphism, and RoboEthics. She holds a PhD in Psychology from Technische Universität Berlin (2014) and a Diplom in Psychology from the same institution (2009). PhD in Psychology (2009-2014), Technische Universität Berlin Diplom in Psychology (2002-2009), Technische Universität Berlin Her research explores the impact of anthropomorphic robot design on trust and attention, flexible automation concepts, and ethical implications of human-robot collaboration. Recent work examines social loafing with robots, taxonomy development for interaction models, and the role of system transparency in trust recovery. Linda’s publications emphasize automation bias, human error identification, and empirical validation of human-robot interaction paradigms. She has contributed to journals like ACM Transactions on Human-Robot Interaction and Science Robotics , with a 2021 meta-analysis on anthropomorphism in robotics. HFES Europe Chapter Best Paper Award She has served as an ad-hoc reviewer for journals like IEEE Transactions on Human-Machine Systems and is a member of organizations including the Human Factors and Ergonomics Society Europe Chapter and the German Association of University Professors and Lecturers (DHV).

Felix Balzerمشاهده پروفایل

استاد

• Medical Data Science
• Health Informatics
• Artificial Intelligence in Healthcare
• +۷ مورد دیگر

Prof. Felix Balzer is a Professor for Medical Data Science and Chief Medical Information Officer (CMIO) at Charité - University Medicine Berlin . He serves as Director of the Institute of Medical Informatics, leading digitalization efforts for patient care and overseeing implementation of the hospital's electronic medical record (EMR) systems. Medical Data Science professorship (2021) Director of Institute of Medical Informatics Acting Chief Information Officer (2024-2025) Deputy Chief Medical Officer for Clinical Digitalization (2025) His research focuses on: Digital healthcare transformation Machine learning in critical care Alarm fatigue mitigation Interoperability standards (FHIR, OMOP) Electronic health records (EHR) optimization Patient monitoring systems The 2025-2026 publications reveal expertise in ICU data analysis, predictive modeling for postoperative delirium, and pandemic response technology. His work bridges clinical practice with technical implementation through: Interdisciplinary teams Multi-center trials Real-time clinical data architectures Human factors in healthcare AI

Philipp Allgeuerمشاهده پروفایل

پژوهشگر

• Robotics
• Humanoid Robotics
• Bipedal Locomotion
• +۵ مورد دیگر

Dr. Philipp Allgeuer is a Postdoctoral Research Associate at the Knowledge Technology Research Group within the Department of Informatics at the University of Hamburg. His work focuses on humanoid robotics, bipedal locomotion, and sensor fusion. He holds a PhD from the Autonomous Intelligent Systems Group at the University of Bonn, alongside dual bachelor's degrees in Mechatronic Engineering and Mathematical/Computer Sciences (both with First-Class Honors). His research contributions include the development of the igus Humanoid Open Platform and the NimbRo-OP series of humanoid robots, recognized with awards like the RoboCup HARTING Open Source Award (2016) and the Best Humanoid Award (2018). He has authored influential papers on fused angles for robot balance, tilt phase space representations, and neuro-inspired control architectures. Allgeuer's teams have dominated RoboCup competitions, winning titles in AdultSize and TeenSize leagues multiple times. His open-source software frameworks (e.g., rot_conv_lib , attitude_estimator ) and hardware designs are widely used in robotics research. Recent work explores multimodal human-robot interaction and AI-driven robotic task coordination. He is affiliated with the Knowledge Technology Research Group and contributes to projects like the NICOL humanoid robot, bridging social interaction and reliable manipulation. His research spans from low-level control algorithms to high-level behavior planning systems.

• Information Theory
• Wireless Communications
• Signal Processing
• +۳ مورد دیگر

Prof. Slawomir Stanczak is a Full Professor in Network Information Theory at Technische Universität Berlin and Head of the Wireless Communications and Networks department at Fraunhofer Heinrich-Hertz-Institut (HHI). His expertise spans wireless communications, signal processing, and machine learning, with a focus on 5G/6G networks and reconfigurable intelligent surfaces. He has held visiting roles at RWTH Aachen University and Stanford University, and leads initiatives like the 6G Research & Innovation Cluster and the xG-Incubator project. Education: Dipl.-Ing. in Electrical Engineering, TU Berlin (1998) Dr.-Ing. (summa cum laude), TU Berlin (2003) Habilitation (venia legendi), TU Berlin (2006) Research & Awards: Recipient of the Best Paper Award from the German Communication Engineering Society (2014) Research grants from the German Research Foundation Co-authored over 200 peer-reviewed papers and two books Chair of the ITU-T Focus Group on Machine Learning for Future Networks (2017-2020) Leadership & Projects: Chairman of 5G Berlin association since 2020 Coordinator of 6G Research & Innovation Cluster and CampusOS flagship project Project lead of xG-Incubator (StartUpConnect initiative) Teaching: Offers courses on Machine Learning and Wireless Communication at TU Berlin.

• Robotics
• Artificial Intelligence
• Space Robotics
• +۵ مورد دیگر

M.Sc. Maximilian Mühlbauer is a researcher at the Chair of Sensor-Based Robot Systems and Intelligent Assistance Systems at Technische Universität München (TUM), part of the Faculty of Computer Science. His work focuses on robotics, artificial intelligence, and space robotics, particularly in areas like in-orbit manufacturing, virtual fixtures, and human-robot interaction. He contributes to projects such as the ACOR initiative and the AI-In-Orbit-Factory, exploring fault-tolerant processes and adaptive robotic systems for space applications. Research Interests: Maximilian’s research emphasizes AI-driven robotics , space robotics , and control systems . He develops methodologies for virtual fixtures , reconfigurable robotic systems , and teleoperation with shared control . His work integrates probabilistic models and machine learning for resilient systems in challenging environments like space. Publications: His recent work spans topics from in-orbit manufacturing and force-sensitive space manipulators to multi-modal haptic teleoperation , reflecting a focus on practical robotic applications in aerospace and industry. Grants/Advising: Maximilian oversees available theses on topics like mixture of experts fixture learning and virtual fixture adaptation , inviting collaboration on AI-driven robotics projects. He collaborates with Prof. Alin Albu-Schäffer and contributes to TUM’s research initiatives in autonomous systems. Labs: He is part of the Sensor-Based Robot Systems lab, advancing robotics for human-centric and space-oriented applications.

Wolfgang Nejdlمشاهده پروفایل

استاد

• Web Science
• Information Retrieval
• Artificial Intelligence
• +۴ مورد دیگر

Prof. Dr. Wolfgang Nejdl is a Professor at the Institute for Data Science within the Faculty of Electrical Engineering and Computer Science at Leibniz University Hannover. He serves as Executive Director of the L3S Research Centre and Leibniz Forschungszentrum Inclusive Citizenship. Web Science Information Retrieval Artificial Intelligence Deep Learning His recent research focuses on AI applications in medicine , multimodal data fusion , and ethical AI systems . Projects include CAIMed (AI in Causal Medicine) and DAISEC (AI & Cybersecurity). His publications span conferences like AAMAS, WWW, and SIGIR. Notable awards include membership in the National Academy of Science and Engineering (acatech) . Former students hold positions at institutions like Stanford, TU Dresden, and ETH Zürich. Current projects involve climate resilience AI , federated learning for healthcare , and quantum-inspired data science .

Ralf Beckمشاهده پروفایل

استاد

• Control Engineering
• Automation Technology
• Regulation Systems
• +۵ مورد دیگر

Prof. Dr.-Ing. Ralf Beck serves as Professor for Control and Regulation Technology and Automation Technology at Hochschule Düsseldorf University of Applied Sciences within the Faculty of Electrical Engineering & Information Technology. His academic responsibilities span multiple degree programs including BEng Electrical Engineering, BEng Industrial Engineering, and MSc Electrical Engineering and Information Technology. His educational background includes Mechanical Engineering studies at TU Braunschweig (1998-2004), followed by doctoral research at RWTH Aachen's Institute of Control Engineering where he earned his Dr.-Ing. in 2010 with a dissertation on predictive energy management for hybrid vehicles. Prior to his current professorship, he held progressive roles at FEV Europe GmbH from 2009-2018, culminating as Senior Project Manager for Vehicle and Powertrain Electronics. Beck's research focuses on control engineering systems with particular emphasis on automation technology, regulation systems, and model-based development approaches. His work bridges theoretical control methodologies with practical automotive applications, especially in hybrid vehicle energy management, multi-robot systems, and intelligent air path control. The Modellfabrik Fab21 serves as his primary experimental platform for model-based development applications. His publication record since 2005 demonstrates consistent contributions to control engineering, particularly in hybrid vehicle systems, emission control optimization, and calibration methodologies. Recent work shows increasing focus on distributed robotics and intelligent transportation systems, reflecting evolving research directions while maintaining core expertise in control theory applications. As an educator, Beck teaches foundational and advanced courses including Electrical Engineering III, Control and Regulation Technology, Model-Based Development, Technical Mechanics, and Advanced Control Engineering at the Master's level. His teaching integrates theoretical concepts with practical laboratory applications through the university's Moodle platform, emphasizing hands-on implementation of control algorithms and system modeling techniques.

Bo Xiongمشاهده پروفایل

پژوهشگر

• Machine Learning
• Knowledge Graphs
• Graph Neural Networks
• +۴ مورد دیگر

Bo Xiong is a researcher at the University of Stuttgart in the Analytic Computing group. His research focuses on machine learning and knowledge graphs , with a particular emphasis on geometric embeddings and hyperbolic neural networks. His research interests include: Knowledge graph embeddings Hyperbolic and pseudo-Riemannian geometry in AI Temporal knowledge graph reasoning Structured multi-label prediction Recent publications highlight his work on geometric relational embeddings, complex query answering, and temporal fact reasoning using advanced manifold-based techniques.

• 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 .

Xieyuanli Chenمشاهده پروفایل

دانشیار

• Robotics
• Autonomous Systems
• Computer Vision
• +۳ مورد دیگر

Xieyuanli Chen is an Associate Professor at the National University of Defense Technology (NUDT), China. He holds a Dr.-Ing. (summa cum laude) from the University of Bonn (2022), a Master's in Robotics from NUDT (2017), and a Bachelor's in Electrical Engineering from Hunan University (2015). His research focuses on robot learning, perception, and navigation, with an emphasis on LiDAR-based SLAM, autonomous systems, and semantic perception. Education: PhD: University of Bonn, 2018-2022 (supervised by Prof. Cyrill Stachniss) Master's: NUDT, 2015-2017 Bachelor's: Hunan University, 2011-2015 Research interests include robotics, autonomous systems, computer vision, and LiDAR perception. He has authored over 90 papers in top venues like TRO, RSS, ICRA, and CVPR. He serves as an Associate Editor for IEEE RA-L, ICRA, and IROS, and is a member of the RoboCup Rescue Robot League Technical Committee. Awards include the RSS Pioneer Award (2021), Best-in-Class RoboCup awards, and recognition as a World’s Top 2% Scientist (2024). His work spans LiDAR localization, moving object segmentation, and efficient semantic mapping. He advises students in robotics and autonomous systems. Labs/Teams: Active in the PRBonn group (University of Bonn) and leads research at NUDT on LiDAR-based perception systems.

• Virtual Reality
• Social Interaction
• Human-Computer Interaction
• +۴ مورد دیگر

Andrea Stevenson Won is a researcher at Cornell University in the Department of Communication , focusing on virtual reality (VR), human-computer interaction, and social dynamics in immersive environments. Her work explores avatar embodiment , nonverbal behavior , and accessibility in VR for users with disabilities. Research Themes : Virtual embodiment and its psychological effects Accessibility solutions for blind and low-vision users in social VR Nonverbal communication analysis in immersive environments Pro-social behavior through VR interventions Collaborative VR systems and AI integration Recent Article Trends : 2024: Investigated avatar behavior transformation in mixed reality ( MRTransformer ), AI-guided accessibility tools, and nonverbal cue adaptations 2023-2022: Focused on educational VR applications, 360° video narratives, and longitudinal team dynamics 2021-2014: Pioneered avatar embodiment studies, anxiety detection via movement tracking, and homuncular flexibility in VR

• Artificial Intelligence in Healthcare
• Biomedical Engineering
• Traditional Chinese Medicine Informatics
• +۳ مورد دیگر

Dr. Jing Wang is a Professor in the Department of Bioinformatics at Southern Medical University's School of Medicine, with extensive research at the intersection of artificial intelligence and biomedical applications. Her work demonstrates strong cross-disciplinary collaboration across medical institutions, engineering departments, and computer science research groups. Her primary research interests include Artificial Intelligence in Healthcare , Biomedical Engineering , and Traditional Chinese Medicine Informatics , with recent publications showing particular expertise in medical imaging analysis, diagnostic assistance systems, and clinical decision support. Her work spans both theoretical algorithm development and practical clinical implementations. Analysis of her 15 most recent publications (2025-2026) reveals a strong trend toward clinically applicable AI systems, with approximately 60% of publications focused on medical diagnostics and treatment support systems. The remaining publications demonstrate expertise in industrial applications of computer vision and fundamental AI research. Her work shows consistent collaboration with both domestic Chinese institutions and international research groups. Notable scientific contributions include: Development of 'Tianyi', a traditional Chinese medicine language model for clinical practice Innovations in bionic soft robotics for rehabilitation assistance Novel approaches to medical image analysis for cancer diagnostics Her research program appears well-funded with consistent publication output across high-impact journals in biomedical engineering, AI, and medical informatics. Current work suggests strong emphasis on translating AI research into clinical practice, particularly in diagnostic support systems and rehabilitation technology.

Karl-Erik Årzénمشاهده پروفایل

استاد

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

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

Laura Alvarezمشاهده پروفایل

استادیار

• Active matter
• Chemical Communication
• Bio-inspired microsystems
• +۳ مورد دیگر

Laura Alvarez is a Junior Chair (Tenure Track) at the University of Bordeaux since 2022, conducting research at the Paul Pascal Research Center (CRPP), a joint CNRS-University of Bordeaux unit. Her office is located at B-224, 115 Avenue du Dr Albert Schweitzer, 33600 Pessac, France, with contact via (+33) 05 56 84 30 27 or laura.alvarez-frances@u-bordeaux.fr. She leads the BIO 2.0 team's research on active matter and colloidal systems. Her educational trajectory includes: PhD at University of Bordeaux and KU Leuven (2013-2016) under Prof. MP Lettinga and Dr. Eric Grelet Postdoctoral research at ETH Zurich (2017-2021) with Prof. Lucio Isa SNSF Spark postdoctoral fellowship (2020-2021) Her research centers on Active Matter , Chemical Communication , and Bio-inspired microsystems , investigating active liposome design, colloidal-lipid membrane interactions, and collective colloidal behavior. Key methodologies include optical tweezers and microfluidics for studying enzymatic particle navigation and colloidal lattice assembly. Her publication record (2017-2023) reveals a strong focus on programmable active colloids and microfluidic applications , with significant contributions to artificial microswimmers and reconfigurable systems appearing in Nature Communications, PNAS, and Physical Review Letters. Emerging trends show increasing emphasis on biomedical applications of active matter. Key recognitions include: Spark postdoctoral grant (SNSF, 2020) IdEx PhD fellowship (2013) She secured major grants including ANR JCJ Project MYMESYS (2023) and France-Berkeley Fund (2023), while her mentoring role involves graduate student supervision through University of Bordeaux's tenure-track framework. As BIO 2.0 team lead at CRPP, she directs experimental work on active colloidal particles using microfluidic platforms and optical manipulation, maintaining active collaborations with ETH Zurich, University of Bordeaux, and international partners across Europe.