activity
20242026
collaborators

9 papers

cs.AI2026

MoE Router-Guided Clustering for Heterogeneous Federated Instruction Tuning

Ankita Sharma, Bahar Farahani, Sanaz Rahimi Moosavi +3

Federated instruction fine-tuning enables Large Language Models (LLMs) to adapt to decentralized, privacy-sensitive data without requiring data sharing. Recent Mixture-of-Experts (…

cs.LG2026

Membership Inference Attacks Expose Participation Privacy in ECG Foundation Encoders

Ziyu Wang, Elahe Khatibi, Ankita Sharma +4

Foundation-style ECG encoders pretrained with self-supervised learning are increasingly reused across tasks, institutions, and deployment contexts, often through model-as-a-service…

cs.LG2026

CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation

Elahe Khatibi, Ziyu Wang, Ankita Sharma +4

Large language models (LLMs) enable waveform-to-text ECG interpretation and interactive clinical questioning, yet most ECG-LLM systems still rely on weak signal-text alignment and…

cs.AR2026

H3PIMAP: A Heterogeneity-Aware Multi-Objective DNN Mapping Framework on Electronic-Photonic Processing-in-Memory Architectures

Ziang Yin, Aashish Poonia, Ashish Reddy Bommana +7

The future of artificial intelligence (AI) acceleration demands a paradigm shift beyond the limitations of purely electronic or photonic architectures. Photonic analog computing de…

cs.LG2025

Exploration of Low-Power Flexible Stress Monitoring Classifiers for Conformal Wearables

Florentia Afentaki, Sri Sai Rakesh Nakkilla, Konstantinos Balaskas +6

Conventional stress monitoring relies on episodic, symptom-focused interventions, missing the need for continuous, accessible, and cost-efficient solutions. State-of-the-art approa…

cs.CR2025

Linkage Attacks Expose Identity Risks in Public ECG Data Sharing

Ziyu Wang, Elahe Khatibi, Farshad Firouzi +3

The increasing availability of publicly shared electrocardiogram (ECG) data raises critical privacy concerns, as its biometric properties make individuals vulnerable to linkage att…