Pasi Liljeberg
Professor, Head of Department
pasi.liljeberg@utu.fi +358 29 450 2469 +358 40 543 3722 Vesilinnantie 5 Turku Työhuone: 1st floor ORCID-tunniste: https://orcid.org/0000-0002-9392-3589 |
Biomedical engineering, Internet of Things, edge computing, Wearable sensors, Digital health technology, Health data analytics, Approximate and adaptive computing,
Research interest fall to the areas of biomedical engineering, health technology and edge computing. Please see also: https://healthtech.utu.fi
Pasi Liljeberg received MSc and PhD degrees in information and communication technology from the University of Turku, Turku, Finland, in 1999 and 2005, respectively. He received Adjunct professorship in embedded computing architectures in 2010. Currently he is working as a full professor in University of Turku in the Digital Health Technology unit. At the same time he serves as head of the Department of Computing, Faculty of Technology, University of Turku. His research interests are biomedical engineering, Internet of Things, edge computing, approximate and adaptive computing, wearable sensors, digital health technology and health data analytics. Liljeberg is the (co-)author of around 300 peer-reviewed publications.
My research interest fall in the field of biomedical engineering, health technology and Internet-of-Things. This is in the context wearable biomedical, wearable technology, applied machine learning, bio-signal processing, health informatics and edge computing. Special attention is paid to novel biomedical sensing applications, wearable computing, analytics, informatics, communication, and networking paradigms, especial focus onhealthcare and wellbeing applications.
Teaching interest in the field of Health Technology in general.
- Exploiting Approximation for Run-time Resource Management of Embedded HMPs (2025)
- ACM Transactions in Embedded Computing Systems
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - HiDP: Hierarchical DNN Partitioning for Distributed Inference on Heterogeneous Edge Platforms (2025)
- Proceedings : Design, Automation, and Test in Europe Conference and Exhibition
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - ISCA: Intelligent Sense-Compute Adaptive Co-Optimization of Multimodal Machine Learning Kernels for Resilient mHealth Services on Wearables (2025)
- IEEE Design and Test
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Multimodal Pain Recognition in Postoperative Patients: Machine Learning Approach (2025)
- JMIR Formative Research
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Multitask learning approach for PPG applications: Case studies on signal quality assessment and physiological parameters estimation (2025)
- Computers in Biology and Medicine
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Respiration Rate Estimation via Smartwatch-based Photoplethysmography and Accelerometer Data: A Transfer Learning Approach (2025)
- Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Adaptive Workload Distribution for Accuracy-aware DNN Inference on Collaborative Edge Platforms (2024)
- Proceedings of the Asia and South Pacific Design Automation Conference
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Attention-Based Explainable AI for Wearable Multivariate Data: A Case Study on Affect Status Prediction (2024)
- International Conference on Wearable and Implantable Body Sensor Networks
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - EA2: Energy Efficient Adaptive Active Learning for Smart Wearables (2024) ISLPED '24: Proceedings of the 29th ACM/IEEE International Symposium on Low Power Electronics and Design Alikhani, Hamidreza; Wang, Ziyu; Kanduri, Anil; Liljeberg, Pasi; Rahmani, Amir M.; Dutt, Nikil
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - ECG Unveiled: Analysis of Client Re-identification Risks in Real-World ECG Datasets (2024)
- International Conference on Wearable and Implantable Body Sensor Networks
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Impact of Physical Activity on Quality of Life During Pregnancy: A Causal ML Approach (2024)
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Improved sleep stage predictions by deep learning of photoplethysmogram and respiration patterns (2024)
- Computers in Biology and Medicine
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Preterm birth risk stratification through longitudinal heart rate and HRV monitoring in daily life (2024)
- Scientific Reports
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Robust CNN-based Respiration Rate Estimation for Smartwatch PPG and IMU (2024) ICBRA '23: Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications Kazemi Kianoosh, Azimi Iman, Liljeberg Pasi, Rahmani Amir M.
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - SEAL: Sensing Efficient Active Learning on Wearables through Context-awareness (2024)
- Proceedings : Design, Automation, and Test in Europe Conference and Exhibition
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Tango: Low Latency Multi-DNN Inference on Heterogeneous Edge Platforms (2024)
- Proceedings : IEEE International Conference on Computer Design
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Work-in-Progress: Context and Noise Aware Resilience for Autonomous Driving Applications (2024)
- International Conference on Hardware/Software Codesign and System Synthesis
(O2 Muu julkaisu ) - A Deep Learning-based PPG Quality Assessment Approach for Heart Rate and Heart Rate Variability (2023)
- ACM Transactions on Computing for Healthcare
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - An energy-efficient semi-supervised approach for on-device photoplethysmogram signal quality assessment (2023)
- Smart Health
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Can Sleep Quality Attributes be Predicted from Physical Activity in Everyday Settings? (2023)
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)