XPRES - Excellence in Production Research
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The initiative for Excellence in Production Research, XPRES, is a joint initiative between KTH, MDH and Swerea. XPRES was elected as one of two strategic initiatives within Manufacturing engineering in Sweden by the government in 2010. XPRES will establish a long term internationally competitive platform for production research to meet future challenges of world leading Swedish industry. By complementing each others scientific competences and roles, the unique research and education consortium of KTH, MDH and Swerea covers the fields of Production processes, Production systems and Digital engineering. The industrial partners represent world leading Swedish manufacturing industries including: heavy vehicle, machine, component manufacturing and aircraft.
Modeling and Evaluating an Intelligent Health Monitoring System for Detecting Atrial Fibrillation (Mar 2026) Petter Nordin, Hossein Fotouhi, Miguel Leon Ortiz, Oana Cramariuc , Tiberiu Seceleanu, Maryam Vahabi International Journal of Network Dynamics and Intelligence (IJNDI)
Real-Time Inference for IIoT Using Distributed Low-Power Edge Clusters (Dec 2025) Dinesh Sah, Maryam Vahabi, Hossein Fotouhi World Forum on Internet of Things (WF-IoT'2025)
Federated learning at theedgeinIndustrial Internet of Things: Areview (Feb 2025) Dinesh Sah, Maryam Vahabi, Hossein Fotouhi Sustainable Computing: Informatics and Systems (SUSCOM)
Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels (Jan 2025) Mohammad Hassan Adeli, Dariush Abbasi-Moghadam , Hossein Fotouhi, S. Mohammad Razavizadeh IEEE Open Journal of the Computer Society (OJ-CS)
An Improved Worst-Case Response Time Analysis for AVB Traffic in Time-Sensitive Networks (Dec 2024) Daniel Bujosa Mateu, Julián Proenza , Alessandro Papadopoulos, Thomas Nolte, Mohammad Ashjaei 45th IEEE Real-Time Systems Symposium (RTSS 2024)
Forte: Hybrid Traffic-Aware Scheduling for Mobile TSCH Nodes (Oct 2024) Iliar Rabet, Hossein Fotouhi, Mário Alves , Maryam Vahabi, Mats Björkman IEEE Conference on Local Computer Networks (LCN)
| Partner | Type |
|---|---|
| KTH Royal Institute of Technology | Academic |
| Swerea IVF | Industrial |
