Cécile Paris is a researcher at CSIRO , focusing on interdisciplinary applications at the intersection of Artificial Intelligence , Cybersecurity , and Human-AI Collaboration . Her work spans domains such as biomedical informatics, social media analysis, and robotics. Research Interests: Developing collaborative frameworks for human-AI teams Explainable AI in cybersecurity Trust modeling in social networks Fake news detection via temporal and graph-based networks Image captioning with multimodal learning Stance classification across domains Article Trends: Recent publications emphasize adaptive alert prioritization (2025), systematic reviews on cybersecurity challenges (2024), and foundational work in NLP for epidemic intelligence (2018-2020). Key methodologies include graph neural networks, transformer models, and adversarial training.
Mojtaba Joodaki is a Professor of Computer Science & Electrical Engineering at Constructor University Bremen, affiliated with the School of Computer Science & Engineering. His research focuses on nanoelectronics, bridging high-frequency engineering with nanoscale devices and materials. His work spans the development of devices for memories , sensors , energy harvesting , and communication systems . Recent publications highlight advancements in metasurfaces , electromagnetic energy harvesting , and waveguide modeling , with applications in microwave engineering and sustainable technologies. The 15 most recent articles reflect trends in metasurface design , electromagnetic compatibility , and memory device optimization . Topics include polarization-insensitive energy harvesters, GSTC modeling, and strain effects in organic solar cells. Collaborations span institutions in Germany, Iran, and beyond, with a focus on experimental validation and analytical frameworks. Prof. Joodaki earned his PhD in Electrical and Electronics Engineering from the University of Kassel (1999–2002), with a dissertation on Quasi-Monolithic Integration Technology for Microwave and mm-Wave Applications . Prior roles include professorship at Ferdowsi University of Mashhad and engineering positions at Qimonda Dresden GmbH, Infineon Technology, and ATMEL Germany GmbH.
Dr.-Ing. Maxim N. Cherkashin is a Researcher at the Photonics and Terahertz Technology Team within the Faculty of Electrical Engineering and Information Technology at Ruhr University Bochum. His work focuses on advancing optical and biomedical imaging techniques through innovative uses of ultrasonics and wavefront shaping. Research interests include: Ultrasound-guided light manipulation in scattering media Photoacoustic imaging and wavefront shaping for medical diagnostics Development of multimode fiber-based sensing systems Recent articles emphasize breakthroughs in: Enhancing fluorescence detection in hidden targets via ultrasound waveguiding Reconfigurable ultrasound systems for deep-tissue optical imaging Optical fiber integration with ultrasonic sensors His team collaborates on projects like "Ultrasonic wave guidance of light deep into scattering media" , advancing applications in biomedical optics and photonics. Labs/Teams: Active member of the Photonics & Terahertz Technology research group, contributing to state-of-the-art imaging systems and sensor development.
Gabriel Kerekes serves as a Postdoctoral Researcher and Group Leader of 3D Data Acquisition and Monitoring at the Institute of Engineering Geodesy Stuttgart (IIGS), part of the Faculty of Aerospace Engineering and Geodesy at the University of Stuttgart. He is actively affiliated with the Cluster of Excellence IntCDC (Integrative Computational Design and Construction for Architecture), contributing to cutting-edge research in computational construction methodologies. Dr. Kerekes specializes in terrestrial laser scanning (TLS), engineering surveying, and 3D data acquisition systems. His research addresses critical challenges in point cloud processing, stochastic modeling of geodetic measurements, and robotic total station networks for real-time construction monitoring. He develops innovative solutions for deformation analysis, geometric quality control of bio-based building elements, and integration of multi-sensor systems in architectural applications, with significant contributions to biomimetic shell construction and infrastructure monitoring projects. No scientific awards or fellowships were documented in the provided materials. Dr. Kerekes has supervised ten Master's and Bachelor's students since 2018, with research spanning TLS intensity analysis, atmospheric error modeling, and robotic positioning systems. His grant-funded projects include RP 16-2 (Spider Crane Robotic Platform) and AP 7 (Integrated Space-Time Point Cloud Modeling) under the IntCDC cluster. As leader of the 3D Data Acquisition and Monitoring team, he drives advancements in geodetic measurement technologies for next-generation construction processes.
Hans-Arno Jacobsen is a Professor at the Faculty of Computer Science (Technische Universität München, TU Munich) and affiliated with the Department of Electrical and Computer Engineering at the University of Toronto. His work spans Computer Science , Distributed Systems , and Artificial Intelligence . Research interests include Blockchain Technology , Consensus Algorithms , Graph Neural Networks , and Quantum Computing . Recent projects focus on decentralized consensus , energy-efficient databases , and federated learning in edge environments. His 15 most recent articles (2024–2025) explore topics such as dynamic resource orchestration , CRDT-based blockchains , and multimodal depression recognition . Collaborates with researchers like Ruben Mayer , Gengrui Zhang , and Shiqiang Wang on systems for federated computing , blockchain benchmarking , and distributed GNN training .
Simone Cardarelli is a Research Fellow in the Department of Electrical Engineering at Eindhoven University of Technology. His work focuses on photonics and optical communication systems, particularly in advancing electro-optical beam steering and fiber alignment technologies. PhD Thesis: Electro-optical beam steering in an InP optical waveguide (2019) Key Projects: AUTOALIGN (electronically aligned fiber arrays), METRO (5G optical networks) Research Interests Photonics and optical communication systems Beam steering and angle-of-arrival detection Waveguide and photonic integrated circuit design Energy-efficient optical networking Research Trends Cardarelli's work spans optical device design, manufacturing precision, and sensor development. His recent contributions include proximity-sensing surfaces and advancements in InP-based optical switches, aligning with broader goals of reducing energy consumption in photonic systems. Collaborations & Impact Collaborated on projects like METRO (5G optical networks) and AUTOALIGN (fiber array manufacturing) Research outputs include 13 publications, 4 patents, and 3 press/media mentions Technologies adopted by TU/e spinoff MicroAlign
Deng Cai is a Professor at Zhejiang University's College of Computer Science, working in the State Key Laboratory of CAD&CG in Hangzhou, China. He also maintains an affiliation with Tencent AI Lab, demonstrating his strong connection between academic research and industry applications in artificial intelligence. His academic background includes a PhD from the University of Illinois at Urbana-Champaign, Department of Computer Science (2009). Professor Cai's research spans multiple domains within artificial intelligence, with particular emphasis on computer vision, deep learning, and their applications. His work shows strong focus on 3D object detection, lane detection for autonomous vehicles, and the application of large language models to various vision tasks. He has made significant contributions to traffic forecasting, trajectory prediction, and CAD generation systems. His recent work increasingly integrates large language models with computer vision tasks, demonstrating the evolving nature of his research interests toward multimodal AI systems. The trajectory of Professor Cai's publications reveals a clear progression from foundational computer vision and machine learning research toward increasingly complex and applied systems. His work shows strong emphasis on practical applications in autonomous driving, with numerous papers on 3D object detection, lane detection, and trajectory prediction. More recently, his research has expanded to include generative models for CAD systems and video customization, often leveraging large language models in innovative ways. The consistent publication output across top-tier venues including CVPR, ICCV, AAAI, and NeurIPS demonstrates sustained research productivity and impact. Professor Cai has established significant research collaborations, particularly with Xiaofei He (161 joint publications), Haifeng Liu (50), Zhou Zhao (42), Wenxiao Wang (41), and Binbin Lin (39). His work appears across diverse publication venues including IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, and proceedings of major AI conferences. The breadth of his publication venues reflects the interdisciplinary nature of his research spanning theoretical machine learning to applied computer vision systems. Professor Cai leads research activities within Zhejiang University's College of Computer Science, particularly focusing on the State Key Laboratory of CAD&CG. His work bridges academic research with practical industry applications through his affiliation with Tencent AI Lab. The laboratory environment supports research in computer vision, machine learning, and their applications to real-world problems in autonomous systems, content generation, and intelligent transportation.
Volker Dürr is a Professor of Biological Cybernetics at Bielefeld University , Faculty of Biology, and a member of the Center for Cognitive Interaction Technology (CITEC) . His work focuses on sensory control of locomotion , active tactile sensing in insects , and biomimetic modeling of movement systems. Education : Habilitation in Zoology (University of Cologne, 2008; Bielefeld, 2005), PhD in Biology (Bielefeld, 1998), Diploma in Biology (Tübingen, 1994) Academic Career : Professor at Bielefeld (2009-present), Junior Research Group Leader (University of Cologne, 2007-2009), Research Assistant (Bielefeld, 1998-2006) His research investigates how insects use antennal mechanosensory systems and proprioception to control locomotion in complex environments. Key themes include goal-directed movements , sensorimotor integration , and biomimetic robotics . Publications emphasize tactile sensing (15/23 articles), neural control of movement (9/23), biomechanical modeling (7/23), and cross-species locomotion analysis (4/23). Recent work explores virtual reality paradigms for locomotion studies and spiking neural networks for proprioceptive modeling.
Dr. Robert Haschke serves as a Professor and Responsible Investigator in the Cognitive Systems and Social Interaction Group at Bielefeld University's Faculty of Engineering. He is affiliated with the Center for Cognitive Interaction Technology (CITEC) and serves on the Examination Board for the Intelligent Interactive Systems Master's program. His office is located at CITEC 2-035, and he can be reached at rhaschke@techfak.uni-bielefeld.de or +49 521 106-12122. Professor Haschke's research spans multiple domains of robotics and artificial intelligence, with particular emphasis on tactile sensing systems, robotic manipulation, and human-robot interaction. His work explores advanced methods for enabling robots to perceive their environment through touch, with applications in assistive robotics and industrial automation. He investigates how machines can learn from human interactions and adapt their behavior through reinforcement learning and sensor fusion techniques. His research bridges theoretical advances with practical implementations, focusing on transferring knowledge from simulation to real-world robotic systems. Analysis of Professor Haschke's recent publications reveals a strong trajectory toward more sophisticated tactile perception systems and their integration with language and vision for natural human-robot collaboration. His work consistently addresses the simulation-to-reality gap, developing methods for transferring control policies from virtual environments to physical robots. The research shows increasing integration of multimodal sensing (tactile, visual, linguistic) to enable more capable and adaptable robotic manipulation in unstructured environments. As an educator, Professor Haschke teaches advanced courses including Robot Manipulators (39-Inf-RM), Advanced Artificial Intelligence (39-M-Inf-AI-adv_a), Advanced Artificial Intelligence (focus) (39-M-Inf-AI-adv-foc), and Basics of Artificial Intelligence (39-M-Inf-AI-bas). His teaching reflects his research expertise, providing students with both theoretical foundations and practical skills in robotics and AI. Professor Haschke is an integral member of Bielefeld University's Cognitive Systems and Social Interaction Group within CITEC. His work contributes significantly to the university's Socio-Technical World research area, particularly in developing capabilities that enable agents (humans, robots, and AI systems) to act, communicate, and learn in complex environments. His research group focuses on creating robotic systems that can interact naturally with humans through advanced perception and adaptive control mechanisms.
Prof. Dr. Anett Bailleu is a Lecturer at the University of Applied Sciences Berlin (HTW Berlin), affiliated with the Department of Engineering - Energy and Information. Her research focuses on sensor physics , multimodal systems , and data analysis , with applications in electrical measurement technology . She also serves as a Laboratory Manager for Process Measurement and Control Technology. Her academic profile includes 5 research projects, 25 publications, and 12 lectures/events. While specific details about awards and individual publications are not provided in the text, she holds roles as Internship Coordinator, Study Advisor, and BAföG Representative across Electrical Engineering (B) and (M) programs.
Prof. Dr.-Ing. Horst Schulte is a Professor at the Department of Engineering I, HTW Berlin - University of Applied Sciences. His expertise lies in Control Systems Engineering, Electrical Engineering, and Renewable Energy Systems, with a focus on modeling, fault-tolerant control, and computational intelligence applications. Department of Engineering I, HTW Berlin Chair in Control Systems Group ResearchGate profile with 214 publications Research Interests include: Model-based and data-driven control systems Wind and photovoltaic power plants Takagi-Sugeno fuzzy systems Robust and fault-tolerant control Dynamic virtual power plants (DVPP) Computational intelligence in energy systems Scientific Awards : 10th Annual ISGAN Award (2024) HTW Berlin Research Award (2018/19) Best Paper in Control Theory (2013) Best BMBF Project of the Month (2012) Key Contributions involve power tracking control for renewables, fault reconstruction in wind turbines, and innovative converter control schemes. His work bridges theoretical control methods with practical energy system implementations.
Rahul Chaudhari is a Senior Researcher at the Chair of Media Technology, Technical University of Munich (TUM), where he has been working since August 2019. He is affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI) and contributes to research in human-computer interaction, particularly in human activity understanding. Dr. Chaudhari earned his doctoral degree (Summa cum Laude) in Communications and Signal Processing from TUM in 2015, following a Master's degree in Communications Engineering from TUM in 2009 and a Bachelor's degree in Electronics and Telecommunications from the University of Pune, India. His academic journey reflects a strong foundation in communications engineering and signal processing that has evolved into interdisciplinary research spanning haptics, computer vision, and artificial intelligence. His research focuses on Human Activity Understanding using Computer Vision, Sensor Fusion, and AI techniques. His current work centers on understanding Human-Object Interactions using camera data (RGB and Depth) recorded in indoor environments, with potential integration of wearable sensors or environmental sensors. His work has significant applications in improving human well-being, comfort, and convenience through intelligent environments and ambient assisted living systems. Dr. Chaudhari's publication record shows a clear evolution from foundational work in haptic communications to cutting-edge research in human-object interaction and 3D pose estimation. His recent publications demonstrate expertise across multiple domains including computer vision for activity recognition, synthetic data generation for training models, and neurosymbolic approaches to human-AI collaboration. This interdisciplinary approach reflects the increasingly connected nature of modern AI research. Best student paper award for Yujun Wang (2025) LMT Spin-off Wins Third Place at euRobotics Technology Transfer Award 2025 LMT featured in Süddeutsche Zeitung (2025) Diego Fernandez Prado selected as finalist for IEEE CASE Best Paper Award (2024) Dr. Chaudhari actively supervises student research, including Master's theses on advanced topics such as 'Simulation and Optimization for 6G Network Planning using Digital Twins.' His supervision work involves guiding students through complex technical challenges in simulation software evaluation, digital twin implementation, and network optimization. He also serves on thesis committees and provides mentorship to students working on related research topics. His research group operates within the broader context of TUM's initiatives in robotics and machine intelligence, contributing to projects like the Centre for Tactile Internet with Human-in-the-Loop (CeTI) and 5G Testbed Bayern. The group maintains a strong focus on both theoretical foundations and practical implementations, with research that bridges the gap between academic innovation and real-world applications in intelligent environments.
Stefan Sosnowski is a Research Fellow at the Chair of Information-Oriented Control, Technical University of Munich (TUM). He has been affiliated with TUM since 2007, including roles as a research assistant and PhD candidate. His work spans Control Systems , Robotics , and Human-Robot Interaction . PhD in Electrical Engineering (2014), TUM Diploma Engineer (2007), TUM B.Sc. in Electrical Engineering (2005), TUM His research focuses on Data-driven Control (e.g., Koopman Operator theory, Gaussian Processes), Human-Centered Control , and Bio-inspired Design for autonomous systems. Recent publications emphasize learning-based control frameworks and stability analysis for nonlinear systems. Notable projects include SeaClear2.0 , CO-MAN , and ReHyb . He coordinates external theses at ITR and has an Erdős number of 4.
Adam Misik is a researcher at the Chair of Media Technology (Prof. Steinbach) within the College of Engineering at the Technical University of Munich. He earned a B.Sc. in 2019 and M.Sc. in 2022 in Electrical Engineering and Information Technology, with study visits at EPFL and Télécom ParisTech. Since June 2022, he has been an external PhD student at Siemens AG. His research focuses on multimodal sensor data analysis using computer vision and deep learning techniques, particularly for 3D reconstruction and localization problems. His work intersects with fields like haptic communication , indoor mapping , and human activity understanding . Key publication trends include point cloud registration , hyperbolic learning , and equivariant neural networks . Recent works address surface material classification (2025), CAD model retrieval (2025), and SLAM systems (2024). Education: B.Sc. (2019), M.Sc. (2022) in Electrical Engineering and Information Technology, TU Munich Current Role: External PhD student at Siemens AG since 2022 Research Affiliation: Chair of Media Technology at TU Munich, part of the Munich Institute of Robotics and Machine Intelligence (MIRMI)
Dr. Richard Lemoine-Rodríguez is a postdoctoral researcher at the Institute of Geography and Geology under the Chair of Remote Sensing , Faculty of Philosophy, University of Würzburg. He also collaborates with the German Aerospace Center (DLR) . His interdisciplinary research bridges urban ecology , geoinformatics , and digital humanities to advance understanding of cities as complex socio-ecological systems. Education: PhD in Geography (2017-2022, Ruhr-Universität Bochum) MSc in Geography (2013-2015, UNAM) BSc in Biology (2008-2012, Universidad Veracruz) His methodological expertise includes multimodal data analysis , social media analytics (Twitter/BlueSky), NLP , and remote sensing techniques for studying urban heat islands, green infrastructure, land use changes, and socio-spatial inequalities. Current work focuses on the Geolingual Studies project (since 2022), exploring language-urban morphology interactions. Key research partnerships include collaborations with: Jakob Schwalb-Willmann (Earth Observation Research Cluster) Hannes Taubenböck (DLR/Technical University Munich) John F. Mas (UNAM) Luis Inostroza (University of Hamburg) Recent publications examine: Urban heat patterns through social media and satellite data Global urban form homogenization Migrant mobility analysis via Twitter Geospatiality of text data Ecological integrity assessments
