activity
20242026
most citedCough-E: A multimodal, privacy-preserving cough detection algorithm for the edge

7 citations · 7 across the 8 of their papers we have counts for

collaborators

9 papers

cs.NI2026

Dot-Flik: A Scalable Edge AI Architecture for Distributed Insect Monitoring

Mattia Consani, Denisa-Andreea Constantinescu, Åse Håtveit +4

Global insect population declines necessitate scalable, continuous monitoring systems, yet existing vision-based solutions remain constrained by high hardware costs, energy demands…

cs.DC2026

GridPilot: Real-Time Grid-Responsive Control for AI Supercomputers

Denisa-Andreea Constantinescu, David Atienza

At global scale, data-center electricity demand is growing faster than the grids that supply it, while system operators increasingly require large flexible loads that can adjust po…

cs.DC2025

astroCAMP: A Community Benchmark and Co-Design Framework for Sustainable SKA-Scale Radio Imaging

Denisa-Andreea Constantinescu, Rubén Rodríguez Álvarez, Jacques Morin +7

The Square Kilometre Array (SKA) will operate one of the world's largest continuous scientific data systems, sustaining petascale imaging under strict power envelopes. Current radi…

cs.LG2025

AquaCast: Urban Water Dynamics Forecasting with Precipitation-Informed Multi-Input Transformer

Golnoosh Abdollahinejad, Saleh Baghersalimi, Denisa-Andreea Constantinescu +2

This work addresses the challenge of forecasting urban water dynamics by developing a multi-input, multi-output deep learning model that incorporates both endogenous variables (e.g…

cs.AR2025

CEO-DC: Driving Decarbonization in HPC Data Centers with Actionable Insights

Rubén Rodríguez Álvarez, Denisa-Andreea Constantinescu, Miguel Peón-Quirós +1

The rapid growth of data centers is increasing energy demand and widening the carbon gap in the ICT sector, as fossil fuels still dominate global energy production. Addressing this…

cs.CV2025

FADE: Forecasting for Anomaly Detection on ECG

Paula Ruiz-Barroso, Francisco M. Castro, José Miranda +3

Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances i…

eess.SP2024

Enabling Efficient Wearables: An Analysis of Low-Power Microcontrollers for Biomedical Applications

Dimitrios Samakovlis, Stefano Albini, Rubén Rodríguez Álvarez +4

Breakthroughs in ultra-low-power chip technology are transforming biomedical wearables, making it possible to monitor patients in real time with devices operating on mere μW. Altho…

eess.AS2024★ 7 cited

Cough-E: A multimodal, privacy-preserving cough detection algorithm for the edge

Stefano Albini, Lara Orlandic, Jonathan Dan +4

Continuous cough monitors can greatly aid doctors in home monitoring and treatment of respiratory diseases. Although many algorithms have been proposed, they still face limitations…

cs.LG2024

BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables

Dimitrios Samakovlis, Stefano Albini, Rubén Rodríguez Álvarez +4

The design of low-power wearables for the biomedical domain has received a lot of attention in recent decades, as technological advances in chip manufacturing have allowed real-tim…