4 citations · 7 across the 8 of their papers we have counts for
8 papers
ConSensus: Multi-Agent Collaboration for Multimodal Sensing
Hyungjun Yoon, Mohammad Malekzadeh, Sung-Ju Lee +2
Large language models (LLMs) are increasingly grounded in sensor data to perceive and reason about human physiology and the physical world. However, accurately interpreting heterog…
CLEF: Clinically-Guided Contrastive Learning for Electrocardiogram Foundation Models
Yuxuan Shu, Peter H. Charlton, Fahim Kawsar +2
The electrocardiogram (ECG) is a key diagnostic tool in cardiovascular health. Single-lead ECG recording is integrated into both clinical-grade and consumer wearables. While self-s…
Contrastive Self-Supervised Learning at the Edge: An Energy Perspective
Fernanda Famá, Roberto Pereira, Charalampos Kalalas +4
While contrastive learning (CL) shows considerable promise in self-supervised representation learning, its deployment on resource-constrained devices remains largely underexplored.…
AdaBet: Gradient-free Layer Selection for Efficient Training of Deep Neural Networks
Irene Tenison, Soumyajit Chatterjee, Fahim Kawsar +1
To utilize pre-trained neural networks on edge and mobile devices, we often require efficient adaptation to user-specific runtime data distributions while operating under limited c…
PRIMUS: Pretraining IMU Encoders with Multimodal Self-Supervision
Arnav M. Das, Chi Ian Tang, Fahim Kawsar +1
Sensing human motions through Inertial Measurement Units (IMUs) embedded in personal devices has enabled significant applications in health and wellness. Labeled IMU data is scarce…
SoundCollage: Automated Discovery of New Classes in Audio Datasets
Ryuhaerang Choi, Soumyajit Chatterjee, Dimitris Spathis +3
Developing new machine learning applications often requires the collection of new datasets. However, existing datasets may already contain relevant information to train models for…
PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai, Dimitris Spathis, Fahim Kawsar +1
Photoplethysmography (PPG) is the leading non-invasive technique for monitoring biosignals and cardiovascular health, with widespread adoption in both clinical settings and consume…
Salted Inference: Enhancing Privacy while Maintaining Efficiency of Split Inference in Mobile Computing
Mohammad Malekzadeh, Fahim Kawsar
In split inference, a deep neural network (DNN) is partitioned to run the early part of the DNN at the edge and the later part of the DNN in the cloud. This meets two key requireme…