6 papers
Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning
Reza Rahimi Azghan, Gautham Krishna Gudur, Giulia Pedrielli +2
Large language models generalize well to individual tasks but lack an inherent mechanism for learning them sequentially, leading to catastrophic forgetting. To mitigate this, LoRA-…
Gated Adaptation for Continual Learning in Human Activity Recognition
Reza Rahimi Azghan, Gautham Krishna Gudur, Mohit Malu +4
Wearable sensors in Internet of Things (IoT) ecosystems increasingly support applications such as remote health monitoring, elderly care, and smart home automation, all of which re…
CLAD-Net: Continual Activity Recognition in Multi-Sensor Wearable Systems
Reza Rahimi Azghan, Gautham Krishna Gudur, Mohit Malu +4
The rise of deep learning has greatly advanced human behavior monitoring using wearable sensors, particularly human activity recognition (HAR). While deep models have been widely s…
GluMind: Multimodal Parallel Attention and Knowledge Retention for Robust Cross-Population Blood Glucose Forecasting
Ebrahim Farahmand, Reza Rahimi Azghan, Nooshin Taheri Chatrudi +9
This paper proposes GluMind, a transformer-based multimodal framework designed for continual and long-term blood glucose forecasting. GluMind devises two attention mechanisms, incl…
Automatic Temporal Segmentation for Post-Stroke Rehabilitation: A Keypoint Detection and Temporal Segmentation Approach for Small Datasets
Jisoo Lee, Tamim Ahmed, Thanassis Rikakis +1
Rehabilitation is essential and critical for post-stroke patients, addressing both physical and cognitive aspects. Stroke predominantly affects older adults, with 75% of cases occu…
AttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset
Ebrahim Farahmand, Reza Rahimi Azghan, Nooshin Taheri Chatrudi +6
Diabetes is a chronic metabolic disorder characterized by persistently high blood glucose levels (BGLs), leading to severe complications such as cardiovascular disease, neuropathy,…