Find Academic Supervisors

• Natural Language Processing
• Artificial Intelligence
• Machine Learning
• +3 more

Wenjie Li is a Professor at the Department of Computing, Hong Kong Polytechnic University, and holds a PhD from the Chinese University of Hong Kong (1997). His research spans Natural Language Processing, Artificial Intelligence, and Machine Learning , focusing on Large Language Models (LLMs) Multimodal Systems Dialogue and Recommender Systems Speculative Decoding and Inference Optimization Chain-of-Thought Reasoning Recent work emphasizes generative retrieval , personalized web agents , and error-resilient LLM frameworks . Key contributions include the JobFormer for skill-aware recommendations, STeCa for trajectory calibration, and TokenSkip for controllable reasoning compression. Publications reveal a trend toward enhancing multimodal alignment and safety mechanisms in aligned LLMs. Li actively collaborates with institutions like Queen's University , Tsinghua University , and Nanjing University , working on projects such as text-image interleaved retrieval and speculative decoding surveys . His 2024-2025 output includes 15+ papers at venues like ACL, CVPR, ICLR , and journals like IEEE Transactions on Neural Networks .

• Data Visualization
• Digital Humanities
• Urban Complexity
• +7 more

Prof. Dr. Marian Dörk is a Research Professor for Information Visualization & Management at the Potsdam University of Applied Sciences , where he co-directs the Urban Complexity Lab (UCLAB) since 2013. His work bridges data visualization , digital humanities , and critical design through projects like GraDiM (2023–2025) and Restaging Fashion (2020–2023). He teaches interface design and urban futures , supervising students on topics like OpenStreetMap cartography and graph-based narratives . PhD in Computer Science (2008–2012) from University of Calgary, supervised by Sheelagh Carpendale and Carey Williamson Prior roles: Research Associate at Newcastle University (2012–2013), internships at Google, Microsoft, and IBM His research focuses on critical data visualization , cultural heritage , and urban complexity , with a specific emphasis on ethical design , intersectional frameworks , and collaborative tools . Recent publications explore unfoldable graph visualizations (2023), climate journalism (2023), and discursive annotations (2025). Collaborators include institutions like Jewish Museum Berlin , SMB/SPK , and Open-Access-Büro Berlin . Key scientific awards include the Best Paper Award at VDA 2011 and Best Poster Award at AITF Tech Futures Summit 2011. His projects often involve students, exemplified by the Close-Up Cloud (2018–2020) and Amazonien as Future Lab (2021–2024). He advocates for freelance web development in academic contexts since 2001.

Alex WaibelView profile

Professor

• Speech Recognition
• Machine Learning
• Artificial Intelligence
• +5 more

Alex Waibel is a Professor of Computer Science at the Karlsruhe Institute of Technology (KIT) and Carnegie Mellon University in Pittsburgh. As head of the Interactive Systems Lab (ISL) at KIT, he pioneered groundbreaking work in language technology, including the world's first automatic simultaneous translation service for university lectures. His research focuses on speech recognition, speech processing, language translation, and neural networks, aiming to bridge global communication gaps through artificial intelligence. Waibel's innovations include the Time-Delay Neural Network (TDNN) in 1987, the JANUS spoken language translation system (1991), translation glasses (2004), and Jibbigo (2009), the first commercial mobile translation system. These technologies have been applied in humanitarian missions and international education, enabling students with limited German proficiency to access KIT's lectures via real-time translation into English, Spanish, or French. His work emphasizes neural networks' ability to emulate human cognitive processes, significantly advancing machine translation accuracy. Despite noting translation imperfections, he highlights the system's value for international and hearing-impaired students. Waibel's collaboration with Skype in 2015 further demonstrated the mass-market viability of real-time translation systems.

• Sensory control of locomotion
• Active sensing in insects
• Insect sense of touch
• +3 more

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.

• Robotics
• Artificial Intelligence
• Human-Robot Interaction
• +3 more

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.

• Artificial Intelligence
• Human-Centered Computing
• Time Series Analysis
• +3 more

Florian Martin is a Research Assistant & PhD Student at the University of Bielefeld’s Faculty of Engineering , affiliated with the Human-Centered Artificial Intelligence Group. His research focuses on processing high-burstness time series data for social interaction pattern detection, aligning with the university’s strategic Socio-Technical World research area. Education: Master in Computer Science (2018–2021) from Eberhard Karls University Tübingen Bachelor in Media Informatics (2014–2018) from Eberhard Karls University Tübingen Prior Roles: Research Assistant & PhD Student at Hasso Plattner Institute’s Chair of Digital Health - Personalized Medicine (2022–2023) Software Developer at AIRAmed GmbH (2021)

Florian MüllerView profile

Assistant Professor

• Extended Reality
• Human-Computer Interaction
• Mobile Interaction
• +4 more

Florian Müller serves as Assistant Professor for Mobile Human-Computer Interaction at Technical University of Darmstadt, leading the Urban Interaction Lab. His research pursues seamless integration of digital information, AI agents, and physical environments into unified Extended Reality (XR), with focus on novel interaction techniques for mobile XR and human-AI collaboration through body-centric, tangible, and haptic interfaces. Müller's primary research spans Extended Reality, Human-Computer Interaction, and Mobile Interaction with specialization in Haptic Interfaces, Tangible Interfaces, and Body-Centric Interaction. He investigates how multimodal sensory feedback enhances user experiences in immersive environments, particularly examining AI-driven adaptation for context-aware XR systems and the social implications of pervasive interactive technologies in urban settings. Recent publications (2024-2025) demonstrate strong interdisciplinary trends across multisensory XR (taste modulation, thermal feedback), social VR/AR applications (privacy, content sharing), and human-AI co-creation systems. Key domains include health (motor control assessment), education, and urban interaction contexts, with consistent emphasis on user experience, safety, and practical implementation challenges. Müller directs the Urban Interaction Lab at TU Darmstadt, which develops and evaluates interactive technologies for public spaces through prototyping novel mobile and XR interfaces. The lab's work emphasizes real-world deployment in urban environments, focusing on social engagement, situational awareness, and seamless interaction between physical and digital layers of city infrastructure.

Moritz HerrmannView profile

Researcher

• Empirical Machine Learning
• Manifold Learning
• Representation Learning
• +5 more

Dr. Moritz Herrmann is a postdoc researcher and Reproducibility & Open Science Transfer Coordinator at the Munich Center for Machine Learning (MCML). He is affiliated with the Biometry in Molecular Medicine working group led by Prof. Anne-Laure Boulesteix at Ludwig-Maximilians-Universität München, and contributes to initiatives like the LMU Open Science Center , Open Science Initiative in Statistics (OSIS) , and Open Science Initiative in Medicine (OSIM) . Ph.D. in Statistics from LMU (2022), M.Sc. in Statistics (2018), and B.Sc. in Mathematics/Sports Science (2014) His research focuses on Empirical Machine Learning , Manifold Learning , and Metascience , with emphasis on epistemological foundations and reliability in ML research. He advocates for open science practices and data literacy, as outlined in his ICML 2024 position paper on rethinking empirical ML research. As a member of the Empirical Machine Learning research focus group and the Statistical Learning and Data Science Chair , Herrmann bridges statistical methodology with biomedical applications. His work spans outlier detection, cluster analysis, and reproducibility frameworks, reflected in his recent publications in journals like Biometrical Journal and Data Mining and Knowledge Discovery .

Muthuraman MuthuramanView profile

Associate Professor

• Biomedical Signal Processing
• Neuroscience
• Machine Learning
• +5 more

Prof. Dr.-Ing. Muthuraman Muthuraman holds the Associate Professorship for Computer Science in Medical Technology at the University of Augsburg and maintains a secondary affiliation as Head of the Neural Engineering with Signal Analytics and AI (NESA-AI) group at the Julius-Maximilian University of Würzburg Department of Neurology. Previously, he served as Assistant Professor at Johannes Gutenberg University Mainz (2016-2024) and Senior Postdoc at Christian-Albrechts University Kiel (2013-2016). Research Focus : Mathematical time series analysis of oscillatory signals, biomedical statistics, multimodal neuroimaging (EEG/MEG/fMRI/EMG), structural and functional network analysis from MRI/DTI/PET, machine/deep learning applications, and proteomic-genomic network modeling including RNA/mRNA/Spatial transcriptomics in neurodegenerative and psychiatric disorders. Publication Trends : His recent work emphasizes neuroinflammatory biomarkers in MS, machine learning applications in multimodal data, deep brain stimulation effects on immune dysregulation, and cross-frequency coupling analysis in movement disorders. Scientific Recognition : Awarded as Best Paper of the Year in Brain Topography (2016) for cortical connectivity studies. Labs & Collaborations : Leads the Informatik für Medizintechnik (IMT) group in Augsburg and NESA-AI unit in Würzburg, collaborating extensively with German Competence Network for MS (KKNMS) and international consortia.

Yelin KimView profile

Assistant Professor

• machine learning
• multimodal signal processing
• affective media analysis
• +1 more

Yelin Kim is an Assistant Professor in the Department of Electrical and Computer Engineering at the University at Albany, State University of New York (SUNY), leading the Inspire Lab for Interaction Sensing and Perception in Real Environment. Her research focuses on: machine learning multimodal signal processing affective media analysis human-machine interaction She quantifies nonverbal behavioral cues (vocal changes, facial expressions, body gestures) to analyze human behavior in real-world interactions using techniques from machine learning, computer vision, and behavioral science. Key recognitions include: Google Faculty Research Award (2018) SUNY-A Faculty Research Award (2017–2019) ACM Multimedia Best Student Paper Award (2014, lead author) Korean Government KETEP Scholarship (2011–2013) Qualcomm Scholarship (2011) She served as ACM ICMI Doctoral Consortium Co-Chair (2018) and delivered invited talks at University of Rochester HCI, RIT AI Seminar Series, and USC EE Seminar. The Inspire Lab (http://albany.edu/inspirelab) develops AI systems for sensing and interpreting affective/social signals in communication.

• Learning Analytics
• Educational Technology
• Computer-Supported Collaborative Learning
• +4 more

Dr. Matthias Ehlenz is a Researcher at RWTH Aachen University's Informatik 9 – Learning Technologies group, where he coordinates and develops concepts for the MediaLab in teacher training. He holds a Dr. rer. nat. (PhD) earned in 2023 for his work on sustainable ecosystems for computer-supported collaborative learning. His research focuses on: Learning analytics infrastructures (xAPI, multimodal data) Collaborative learning technologies (multi-touch tables, VR/XR environments) Serious game design and assessment Human-centered approaches in educational technology Open science and sustainable EdTech development Ehlenz's recent publications (2021-2025) demonstrate strong interdisciplinary trends: 40% focus on learning analytics infrastructures, 30% examine collaborative interfaces (tabletops/XR), 20% address teacher training/digital pedagogy, and 10% explore open science practices. The work shows increasing emphasis on immersive technologies and scalable systems. He actively advises graduate researchers, supervising at least six master's/bachelor's candidates on topics including: XR learning environments AI in education Learning analytics interfaces Collaborative game design Ehlenz co-leads the Learning Technologies Innovation Lab, developing open-source tools for educational research. He contributes significantly to the DELFI conference organization and promotes open science in learning technology research.

• Sustainable waste management
• Edible insect rearing
• Plant-microbe interactions
• +3 more

Dr. Wael Yakti is a scientific collaborator at the Albrecht Daniel Thaer Institute of Agricultural and Horticultural Sciences under the Faculty of Life Sciences at Humboldt University of Berlin . His research spans sustainable waste management, edible insect rearing, and plant-microbe interactions, with a focus on optimizing insect-based biorecycling systems. Current research trends include: Developing standardized protocols for insect feed trials Analyzing microbial synergy in black soldier fly rearing Investigating hemp waste valorization through solid-state fermentation Comparative studies of nutrient recycling pathways His work bridges agricultural science and biotechnology, particularly through the Urban ecophysiology of plants research group located at Lentzeallee 55-57, Room 17.

• Human Activity Understanding
• Computer Vision
• Sensor Fusion
• +6 more

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.

• Control Systems
• Robotics
• Human-Robot Interaction
• +4 more

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.

• Tactile Communication
• Multimodal Signal Processing
• Tactile Codecs
• +3 more

Wenxuan Wei is a Researcher at the Chair of Media Technology (LMT) at the Technical University of Munich (TUM), joining in November 2023. She holds a B.Sc. and M.Sc. in Mechanical Engineering from Beihang University (2020, 2023). Her work focuses on tactile communication, particularly developing multimodal tactile codecs for the Tactile Internet. Research areas: Tactile codecs, multimodal data compression, shared-private representation learning. Projects: Contributions to initiatives like the Centre for Tactile Internet (CeTI) and IEEE P1918.1.1 Haptic Codecs.