Angelika Peer is a full professor at the Bristol Robotics Laboratory, University of the West of England. She holds a Carl von Linde Junior Fellowship (2012) and previously served as a senior researcher and lecturer at Technische Universität München (TUM). Her research focuses on human-robot interaction, telepresence systems, and haptic interfaces, combining control engineering, neuroscience, and psychology. Peer leads interdisciplinary projects involving brain-computer interfaces and human motor control adaptation. Education: PhD 2008 (TUM), MEng 2004 (TUM). Professional roles include chair of IEEE RAS Technical Committee on Telerobotics, and editorial roles in haptics. Awards include IEEE Meritorious Service (2010) and Siemens Excellence Award (2004). Research emphasizes adaptive teleoperation systems, intention recognition algorithms, and human-robot collaboration dynamics. Key contributions include multi-modal telepresence systems, safety-constrained assistive robotics, and EEG-based emotion recognition frameworks. Publications span robotics journals/conferences (IEEE Transactions, ICRA, Haptics), with focus areas in haptic interfaces, shared control policies, and medical robotics applications. Active in organizing international workshops and editorial activities.
Alessandra Sciutti serves as a Tenure Track Researcher and head of the CONTACT (COgNiTive Architecture for Collaborative Technologies) Unit at the Italian Institute of Technology (IIT), where she leads cutting-edge research at the intersection of robotics, cognitive science, and human interaction. Her work fundamentally explores how humans and artificial agents can develop mutually adaptive collaborative relationships. Her educational background includes B.S. and M.S. degrees in Bioengineering followed by a Ph.D. in Humanoid Technologies, establishing a strong foundation for her interdisciplinary research approach. These qualifications directly inform her experimental methodologies and technical implementations in social robotics. Sciutti's research program centers on Human-Robot Interaction with specialized expertise in social robotics for child development , cognitive architectures for collaboration , and neuroscience-inspired human-robot interfaces . She employs rigorous experimental paradigms to investigate spatial attention mechanisms, imitation dynamics, and learning processes in human-robot teams, frequently utilizing humanoid platforms like iCub and Nao to study developmental and social phenomena. Analysis of her 2025 publications reveals a cohesive research trajectory examining bidirectional influence in human-robot systems. Key themes include the impact of robotic tutors on learning outcomes, context-dependent sensory processing in collaborative scenarios, and technical innovations for safe physical human-robot interaction. Her work consistently bridges theoretical cognitive science with practical robotic implementations, particularly in educational contexts involving children. As an influential figure in her field, Sciutti serves as Specialty Chief Editor for Human-Robot Interaction at Frontiers in Robotics and AI, while also contributing as Review Editor and Guest Associate Editor for Frontiers in Integrative Neuroscience. Her editorial leadership shapes research directions in social robotics and cognitive neuroscience. She directs the CONTACT Unit at IIT, which functions as an interdisciplinary hub developing cognitive architectures that enable natural, context-aware collaboration between humans and robots. The unit's research integrates computer vision, machine learning, and cognitive modeling to create systems that understand and respond to human social cues and physiological states during interaction.
María Eva Orantes González is a Professor in the Department of Sports and Information Technology at Pablo de Olavide University. Her work focuses on biomechanics, physical education, and sports performance, particularly in load carriage and movement analysis. She leads the research group RFYD Physical and Sports Performance and contributes to the PAIDI Area of Social and Legal Sciences.
Prof. Jörn Ostermann is a Full Professor and Head of the Institut für Informationsverarbeitung at Leibniz Universität Hannover since 2003, with prior roles at AT&T Bell Labs and AT&T Labs-Research. He served as Dean of the Faculty of Electrical Engineering and Computer Science (2011–2013) and member of the Senat (since 2020). His research spans video coding, computer vision, machine learning, 3D modeling, and computer-human interfaces , with applications in SAR imaging, predictive maintenance, children's speech analysis, and cochlear implants. Key projects include Next Generation Video Coding , Conditional Coding for Learned Compression , and GreenAutoML4FAS . Notable trends in his recent publications (2025–2023) include Neural network-based video compression Uncertainty estimation in speech recognition Zero-delay coding for cochlear implants Domain adaptation for aerial image segmentation 3D mesh compression standards Error concealment in VVC coding Scientific recognitions: AT&T Standards Recognition Award (1998) ISO Award (1998) IEEE Fellow (2005) Distinguished Lecturer, IEEE CAS Society (2002/2003) MPEG Convenor (2020–2023) He co-authored a graduate textbook on Video Communications , holds >30 patents, and has led >20 research projects. His work bridges academic research and industrial standardization, particularly in MPEG and IEEE committees.
Shahriar Nirjon is an Associate Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. His research focuses on Embedded Intelligence, developing end-to-end systems that make resource-constrained real-time and embedded sensing systems capable of learning, adapting, and evolving. Dr. Nirjon received his Ph.D. from the University of Virginia in 2014. Before joining UNC Chapel Hill in 2015, he worked as a Research Scientist at HP Labs (2014-2015) and as a Research Intern at Microsoft Research (Summer 2013) and Deutsche Telekom Lab (Summer 2010). His primary research interest is Embedded Intelligence, with recent works broadly categorized into embedded deep learning and multi-modal sensing techniques. Applications of his research span wearables and implantables, long-term monitoring and control systems, smart home environments, and mobile health solutions. Dr. Nirjon's research bridges theoretical foundations with practical implementations, resulting in systems that have real-world impact in healthcare, safety, and everyday computing. His work has been highlighted in prominent media outlets including IEEE Spectrum, The Economist, New Scientist, and BBC. Dr. Nirjon's publication record demonstrates a strong focus on mobile computing systems, embedded sensor networks, and wireless technologies. His recent work shows increasing integration of machine learning and artificial intelligence with embedded systems, particularly in healthcare applications. There's a clear trajectory toward more sophisticated, energy-efficient systems capable of on-device intelligence, with growing emphasis on privacy-preserving techniques and real-world deployments in healthcare settings. Best Paper Award, Challenges in AI and Machine Learning for IoT (AIChallengeIoT '20) Best Presentation Award, Pervasive and Ubiquitous Computing (Ubicomp '20) Best Paper Award, Distributed Computing in Sensor Systems (DCOSS '19) Best Presentation Award, Vehicular Networking Conference App Contest (VNC '18) Best Demo Runner Up, Vehicular Networking Conference App Contest (VNC '18) Best Paper Nomination, Embedded Wireless Systems and Networks (EWSN '17) Best Demo Runner Up Award, Embedded Networked Sensor Systems (SenSys '16) Best Paper Award, Mobile Systems, Applications, and Services (MOBISYS '14) Best Paper Award, Real-Time and Embedded Technology and Applications Symposium (RTAS '12) Dr. Nirjon has advised numerous PhD students including Chong Shao (Google), Shiwei Fang (Assistant Professor at Augusta University), Tamzeed Islam (Research Staff at Amazon), Bashima Islam (Assistant Professor at Worcester Polytechnic Institute), Seulki Lee (Assistant Professor at UNIST, Korea), and Yubo Luo (Black Sesame Technologies Inc.). He currently advises Mahathir Monjur, Zhenyu Wang, and Louie Lu who are in various stages of their PhD programs. His research is supported by significant grants including an NSF CAREER award ($561K), an NSF SCH grant ($941K), and multiple other NSF-funded projects totaling over $2 million. His active projects include Audio Privacy, Pedestrian Safety, IoT Data Privacy, and HVAC Acoustic Fingerprinting. Dr. Nirjon leads research in the Embedded Intelligence Lab at UNC Chapel Hill, where his team develops cutting-edge technologies in mobile computing, embedded systems, and wireless networks. His work spans multiple domains including healthcare (mobile health systems), safety (pedestrian safety applications), and smart environments (smart homes). He collaborates with researchers across disciplines, particularly in healthcare through the Carolina Health Informatics Program (CHIP), and is actively involved in the Be-A-Maker (BeAM) network of makerspaces at UNC.
Professor Yannick Blandin is affiliated with the University of Poitiers (Faculty of Sports Sciences) and the Center for Research on Cognition and Learning (CeRCA) . His work focuses on motor learning mechanisms, observational learning, mental imagery, and feedback systems in sensorimotor integration. Ph.D. in Physical Activity Sciences (University of Montreal, 1994, directed by Dr. Luc Proteau) Current research themes: specificity of practice, eye movement analysis, point-light display applications His publications reveal trends in sensorimotor coding , motor sequence acquisition , and visual feedback optimization , often intersecting neuroscience , psychology , and sports rehabilitation . He has developed the PLAViMoP platform for visualizing and modifying motor sequences. International collaborations include Dr. Stefan Panzer (Saarland University) and Dr. Charles Shea (Texas A&M). His research spans applications in stroke rehabilitation , athletic training , and cognitive-motor interfaces .
Mauro Murgia is an Associate Professor at the Department of Life Sciences, University of Trieste, specializing in General Psychology . He actively participates in research and teaching activities, serving as a member of the Department's Board , Boards of Studies , and Doctoral Studies Boards . His research focuses on cognitive psychology and neuroscience , particularly spatial-numerical associations, motor rehabilitation in Parkinson's disease, and perception-action integration. He leads the research project NUMERALS (Prot. 20227N2Y73) funded by the Italian Ministry of University and Research. Murgia's work explores how auditory cues influence motor control in sports, with studies on volleyball serves and penalty kicks. He investigates SNARC-like effects in temporal and emotional contexts, and examines perceptual impairments in Parkinson's patients using visual illusions. Collaborative efforts include partnerships with Carlo Fantoni , Tiziano Agostini , and institutions like Brown University and IIT@UNITN. His research utilizes VR labs , eye movement tracking , and kinematic analysis to study perceptual stability and multisensory integration.
Olivier White is a Professor at the University of Burgundy's Faculty of Sports Science (UFR STAPS), where he maintains his laboratory at Espace Marey. With extensive teaching experience across engineering and neuroscience disciplines, he supervises MSc and PhD students while leading a multidisciplinary research program focused on motor control mechanisms under normal and altered gravity conditions. His educational background spans civil engineering and neuroscience, with a BSc (1997), MSc in Computer Science (2000, summa cum laude), DEA in Applied Mathematics (2002), and PhD in Neuroscience and Applied Mathematics (2007), all from Louvain School of Engineering, Belgium. He completed his Habilitation in 2016 with research titled 'From basic motor control to applications' and earned French Qualification for the Neuroscience Section in 2020. White's research investigates how the brain controls diverse actions through innovative approaches including 3D virtual reality, haptic devices, and gravitational manipulation via parabolic flights and centrifuges. His work addresses fundamental questions about sensory information in learning, motor skill generalization, and strategy selection. He employs motion capture, force measurements, electromyography, fMRI, and mathematical modeling approaches including optimal control and fractal analyses. His publication record reveals a consistent focus on gravity-related motor adaptation, with recent work exploring sensorimotor control in inverted postures, resonance phenomena in rhythmic movements, and spaceflight effects on operational performance. His research bridges theoretical physics with practical neuroscience applications, particularly in space physiology and rehabilitation contexts. Dr. White maintains an active teaching portfolio across multiple institutions including University of Burgundy, King's College London, and ESTP Engineering School. His courses range from basic computer science to advanced topics in computational motor control, space physiology, and deep learning applications. Motor control and learning mechanisms Altered gravity effects on human movement Virtual reality and haptic applications Fractal analysis of movement patterns Space physiology and neurorehabilitation Mathematical modeling of motor control He actively supervises research projects at undergraduate and graduate levels, building a laboratory that combines behavioral, neuroimaging, and mathematical methods to understand movement planning and execution. Through international collaborations, particularly in space-related research, he develops applications with societal benefits in rehabilitation and human performance enhancement.
Maximillian Van Wyk de Vries is an Assistant Professor in Natural Hazards at the University of Cambridge, jointly affiliated with the Department of Geography and the Department of Earth Sciences. He leads the Cambridge Complex and Multihazard research group (CoMHaz), focusing on interactions between natural hazards and human activity impacts. His research integrates remote sensing, numerical modeling, and fieldwork to study: Hazard/risk at ice-clad volcanoes under climate change Large-scale landslide detection via satellite imagery Novel methods for glacial/landslide motion tracking Bidirectional glacier-landslide interactions Multihazard modeling using AI approaches Recent publications (2024-2025) demonstrate strong emphasis on: Landslide monitoring techniques (InSAR, optical feature tracking) Multihazard cascades in Nepal/Himalayas Glacial-volcanic interactions in Alaska/Patagonia Climate-hazard feedbacks and AI applications Regional focus on South Asia and Andes He directs the CoMHaz research group conducting interdisciplinary work on complex hazard systems. No awards or student advisees are mentioned in available sources.
Hao Xing is a scientific researcher and post-doctoral fellow at the Institute for Cognitive Systems (ICS), Technical University of Munich (TUM), working with Prof. Gordon Cheng since May 2024. Previously, he served as a research assistant at the Munich Institute of Robotics and Machine Intelligence (MIRMI) and completed his PhD under Prof. Darius Burschka from 2019. His educational background includes: Master of Science in Mechanical Engineering from Technical University of Munich Bachelor of Engineering in Mechanical Engineering from Hefei University of Technology, China Xing's research focuses on Robot Vision , Human Action Recognition , and Graph Convolutional Networks , with significant contributions to Human-Object Interaction Recognition , Scene Understanding , and Visual Depth Estimation . His work leverages machine learning to develop robust algorithms for human activity analysis and robotic perception, emphasizing spatio-temporal modeling and uncertainty handling in real-world scenarios. Analysis of his 13 recent publications (2019-2025) reveals a dominant focus on graph-based approaches for action recognition and segmentation, with increasing emphasis on open-world applications, uncertainty modeling, and healthcare integration. His research spans computer vision, robotics, and medical applications, demonstrating strong interdisciplinary impact through collaborations in surgical robotics and patient monitoring systems. Xing actively mentors students through master's thesis projects in Stereo Matching, Human Activity Segmentation, and Monocular Depth Estimation, requiring expertise in deep learning frameworks and computer vision algorithms. While no major grants are explicitly mentioned, his thesis topics indicate active research funding in geometric vision and human activity analysis. He operates within the Institute for Cognitive Systems (ICS) at TUM, a key unit in MIRMI's robotics ecosystem focused on advancing human-robot interaction through vision-based scene understanding and motion generation capabilities.
Diana Saplacan Lindblom is a Researcher at the University of Oslo's Department of Informatics, Faculty of Mathematics and Natural Sciences. She is a member of the Robotics and Intelligent Systems Research Group (ROBIN) and actively contributes to the Vulnerability in Robot Society (VIROS) research project (2021-present) and the Ethical Risk Assessment of Artificial Intelligence in Practice (ENACT) project (2023-present). Dr. Saplacan received her Ph.D. from the University of Oslo in 2020 with a thesis titled "Situated abilities: Understanding Everyday Use of ICTs" from the Design of Information Systems (DESIGN) Research Group. During Spring 2023, she was a visiting researcher at the Human-Robot Interaction Lab, Department of Social Informatics, Kyoto University, Japan, and a guest researcher at Tohoku University's Frontier Research Institute for Interdisciplinary Sciences. Her research focuses on user studies in Human-Robot Interaction (HRI) and Human-Robot cooperation, with particular emphasis on digitalization of home- and healthcare services, robots as welfare technologies, and ethics regarded through Universal Design principles. She investigates privacy, safety, and security aspects related to robots in healthcare settings, bridging legal and technical considerations. Her work often employs qualitative methods including story dialogue techniques to understand user perspectives and professional reactions to emerging technologies. Analysis of her recent publications reveals a strong interdisciplinary approach connecting computer science, social sciences, and healthcare. Her work spans technical aspects of robotics, ethical considerations in AI implementation, and practical user studies across diverse populations including elderly care recipients and healthcare professionals. She frequently examines how Universal Design principles can be applied to social and assistive robots to ensure accessibility and inclusion. Dr. Saplacan has received notable recognition including an Honorable Mention at HRI (2024) and being named among "Women changing the field of AI in Norway" (2021, 2022). She has also earned Best Paper Awards at ACHI-IARIA (2018, 2020) and a Best Paper Finalist Award at ARSO (2021). HRI Honorable Mention (2024) Women changing the field of AI in Norway (2021, 2022) Best Paper Finalist Award - ARSO (2021) Best Paper Award, ACHI - IARIA (2020) Best Paper Award, ACHI - IARIA (2018) Dr. Saplacan has served as co-supervisor for Ph.D. candidates Adel Baselizadeh (completed 2024) and Marieke van Otterdijk (defense scheduled for December 2024). Her research is supported through collaborations with multiple academic partners including SINTEF, HIOF, and NTNU, as well as industry partners such as DNB, Posten, NAV, Medsensio, and Hypatia Learning. She actively contributes to standardization efforts as a member of Standards Norway Committee on AI & Ethics (WG3) and the IEEE Artificial Intelligence Standards Committee. She is a key contributor to the ROBIN research group's work on healthcare robotics and leads efforts in the UD-Robots project, which examines how universal design principles can be applied to robotics. Her work with the Norwegian Council for Digital Ethics and participation in international workshops demonstrates her commitment to shaping ethical frameworks for emerging technologies.
Bernhard Egger is a junior professor (adidas Stiftungsprofessur) at the Chair of Visual Computing, Cognitive Computer Vision Lab at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) . His research bridges human/machine perception of faces and shapes with synthetic data generation. Formerly, he was a postdoc at MIT's Computational Cognitive Science Lab and Computer Science & AI Lab, following a PhD in facial image annotation at the University of Basel. Research Focus: 3D Morphable Models, Statistical Shape Modeling, Inverse Rendering, AI in Mental Health, Medical Imaging. Education: PhD (University of Basel, 2017), MSc/BSc in Computer Science (University of Basel), Teaching Diploma (University of Applied Sciences Northwestern Switzerland). Notable Awards: Best Poster Award (2024, Cognitive Computational Neuroscience) Best Paper Award (CVPR Workshop 2019) Honk Award (SIGBOVIK 2020) Publications Trends: Recent work spans implicit surface modeling (ICLR 2025), 3D scene decomposition (3DV 2025), medical shape models (BVM 2025), and multimodal AI (npj Mental Health 2024). Labs: FAU's Cognitive Computer Vision Lab (advisor to 8+ students/researchers).
Jonathan Matthis is an Assistant Professor in the Department of Biology at Northeastern University. His research focuses on the interplay between biomechanics, visual perception, and motor control during natural human locomotion. Research Themes: Visual control of gait, optic flow analysis, terrain navigation, motion capture technology, and sensorimotor integration. Key Contributions: Development of the FreeMoCap open-source motion capture system; studies on retinal motion statistics, gaze-foot coupling, and decision-making in complex environments. Contact: j.matthis@northeastern.edu , Mugar Life Sciences Building, Boston, MA. His work integrates eye tracking, motion capture, and photogrammetry to analyze how humans adapt to uneven terrain. Recent projects explore visual discriminability in Augmented Reality stepping tasks and phase-space planning methods for obstacle navigation.
Michaela Jeschke is a PhD researcher at the Department of Psychology and Sports Science , Justus Liebig University Giessen, Germany. Her work focuses on haptic perception , particularly the mechanisms underlying motor process optimization and multisensory signal integration during tactile exploration. Research Interests: Haptic perception of object properties Multisensory integration in sensory processing Motor effort and task demand analysis Psychophysics and virtual reality applications Publications highlight her contributions to understanding tactile adaptation effects, visual prior integration in haptics, and decision-making in exploratory behavior. She actively participates in project A5: "Prior information and predictive mechanisms in exploration and perception during active feeling" under Prof. Dr. Drewing.
Dr. Monique Flecken is an Assistant Professor in the Department of Linguistics at the University of Amsterdam, specializing in neurolinguistics and multilingualism. Her research investigates how language shapes event perception, focusing on dynamic situations like motion events and cross-linguistic cognitive differences. Current affiliation: University of Amsterdam, Faculty of Humanities Prior role: Senior Researcher at Max Planck Institute for Psycholinguistics Her work explores the interplay between linguistic structures (e.g., grammatical aspect, verb semantics) and cognitive processes such as perception, memory, and attention. Methodologies include ERP studies, eye-tracking, and virtual reality experiments. Notably, she examines how languages with varying grammatical systems (e.g., Dutch, Turkish, Persian) influence event conceptualization. Recent publications highlight her research trends, including language-specific effects on motion perception, the role of syntax in telicity judgments, and neural mechanisms underlying linguistic influence on cognition. She actively engages with interdisciplinary approaches, bridging linguistics and cognitive science.
