BioSIS Lab

Advancing health and human performance through AI and multimodal sensing.

Discover Our Mission

Our Research Pillars

From human data to real-world outcomes.

Sensing

Capturing human health, behaviour and performance through physiological, neural, visual and movement sensing.

Physiological sensing

Neural sensing

Computer vision

Motion & IMUs

Embedded systems

Intelligence

Transforming multimodal human data into knowledge through signal processing and responsible AI.

Signal processing

Machine learning

Deep learning

Explainable AI

Data fusion

Impact

Translating research into better health, human performance and safety outcomes.

Healthy Ageing

Pain Assessment & Management

Human Performance & Safety

Sensing  →  Intelligence  →  Impact

Explore the framework

Featured Projects

See how we combine multimodal sensing and intelligent analysis to create real-world impact in health, performance and safety.

Multimodal Signal Processing for Objective Human Pain Assessment

Multimodal Signal Processing for Objective Human Pain Assessment

Objective pain assessment using bio-signal analysis and AI.

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Detection of dementia using neuroimaging and machine learning

Detection of dementia using neuroimaging and machine learning

Early detection of dementia using neuroimaging and machine learning.

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EEG-based cognitive workload assessment workflow and physiological features

Multimodal Sensing for Cognitive Workload and Affective State Monitoring in Human–Machine Interaction

Multimodal sensing and AI for objective monitoring of cognitive workload and affective states during human–machine interaction.

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Meet Our Team

Dedicated researchers and students driving innovation.

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Recent Publications

Latest research findings from our laboratory.

66

Research outputs

36

Journal articles

26

Q1 journal papers

2026

Preprint · arXiv preprint arXiv:2608.09088

A Multi-Scale Temporal Framework with Dynamic Fusion for EEG-Based Emotion Recognition

S Gkikas, Y Guo, G Li, RF Rojas, G Giannakakis, R Gomez

2026

Preprint · arXiv preprint arXiv:2607.19722

ReFace: Reorganizing Facial Spatiotemporal Representations for Improved Pain Assessment

S Gkikas, Y Fang, CA Cruz, MU Khan, RF Rojas

2026

Preprint · arXiv preprint arXiv:2607.19716

A Unified Tokenization Framework for Pain Recognition using Heterogeneous 3D Modalities

S Gkikas, CA Cruz, V Becchetti, MU Khan, A Giuseppi, RF Rojas

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Ready to Collaborate?

Join us in our mission to advance biosensing technology and improve global health outcomes.

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