activity
20242026
most citedAttenGluco: Multimodal Transformer-Based Blood Glucose Forecasting on AI-READI Dataset

3 citations · 3 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

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-…

cs.LG2026

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…

cs.LG2025

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…

cs.LG2025

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…

cs.CV2025

Guiding Diffusion with Deep Geometric Moments: Balancing Fidelity and Variation

Sangmin Jung, Utkarsh Nath, Yezhou Yang +5

Text-to-image generation models have achieved remarkable capabilities in synthesizing images, but often struggle to provide fine-grained control over the output. Existing guidance…

q-bio.QM2025

CAN-STRESS: A Real-World Multimodal Dataset for Understanding Cannabis Use, Stress, and Physiological Responses

Reza Rahimi Azghan, Nicholas C. Glodosky, Ramesh Kumar Sah +4

Coping with stress is one of the most frequently cited reasons for chronic cannabis use. Therefore, it is hypothesized that cannabis users exhibit distinct physiological stress res…

cs.LG2025★ 3 cited

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,…

cs.LG2024

CUDLE: Learning Under Label Scarcity to Detect Cannabis Use in Uncontrolled Environments

Reza Rahimi Azghan, Nicholas C. Glodosky, Ramesh Kumar Sah +4

Wearable sensor systems have demonstrated a great potential for real-time, objective monitoring of physiological health to support behavioral interventions. However, obtaining accu…

cs.NI2024

Minimum-Cost Sensor Channel Selection For Wearable Computing

Ramesh Kumar Sah, Hassan Ghasemzadeh

Sensor systems are constrained by design and finding top sensor channel(s) for a given computational task is an important but hard problem. We define an optimization framework and…