iMOTION LAB
Human Motion Intelligence Research Lab at Adviso.Tech. We develop responsible AI for motion understanding, retrieval, generation and real-world human-centred systems.
Our lab connects computer vision, machine learning and biomechanics to build systems that understand how people move. We focus on research that is scientifically rigorous, reproducible and useful beyond the laboratory.
01 / UNDERSTAND
Recognising actions, interactions and intent from complex temporal motion data.
02 / RETRIEVE
Connecting natural-language descriptions with relevant human motion sequences.
03 / GENERATE
Creating realistic and controllable movement from language, context and constraints.
04 / ESTIMATE
Recovering accurate human pose and movement from images, video and sensor data.
05 / APPLY
Applying human-motion intelligence to pedestrian behaviour prediction, realistic motion synthesis, healthcare technologies, rehabilitation, and human–robot interaction.
06 / EVALUATE
Studying robustness, fairness, privacy and meaningful evaluation for human-centred systems.
Research leadership
A focused team combining research direction, technical leadership and hands-on experimentation.
Research Lead
Leads the lab’s research agenda across human motion understanding, retrieval, generative modelling, and their real-world applications.
Chief Technology Officer
Guides technical strategy, research engineering and the translation of new methods into dependable systems.
Our research assistants support experiments, datasets, model development and evaluation. Replace the role cards below with each members name and focus area.
NLP Research
Supports literature review, experiments and motion-data analysis.
Deep Learning Research
Develops and evaluates learning pipelines for motion intelligence.
Computer Vision Research
Works on Human motion & pose, video understanding and multimodal evaluation.
Computer Vision Research
Works on pose, video understanding and multimodal evaluation.
NLP Research
Works on pose, video understanding and multimodal evaluation.
Computer Vision Research
Works on pose, video understanding and multimodal evaluation.
HOW WE WORK
01
Frame a meaningful research question and establish reproducible success criteria.
02
Curate data, design models and run controlled experiments.
03
Benchmark rigorously, document limitations and test real-world usefulness.
We welcome research collaborations, student enquiries and industry challenges involving human motion intelligence.
We believe technology is more than just a tool
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