activity
20162026
most citedExploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

455 citations · 893 across the 32 of their papers we have counts for

collaborators

33 papers

cs.AI2026

Towards a General Intelligence and Interface for Wearable Health Data

Girish Narayanswamy, Maxwell A. Xu, A. Ali Heydari +37

While ubiquitous wearable sensors capture a wealth of behavioral and physiological information, effectively transforming these signals into personalized health insights is challeng…

cs.LG2024

StatioCL: Contrastive Learning for Time Series via Non-Stationary and Temporal Contrast

Yu Wu, Ting Dang, Dimitris Spathis +2

Contrastive learning (CL) has emerged as a promising approach for representation learning in time series data by embedding similar pairs closely while distancing dissimilar ones. H…

cs.SD2024

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…

cs.LG2024★ 4 cited

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…

cs.LG2024

Using Self-supervised Learning Can Improve Model Fairness

Sofia Yfantidou, Dimitris Spathis, Marios Constantinides +3

Self-supervised learning (SSL) has become the de facto training paradigm of large models, where pre-training is followed by supervised fine-tuning using domain-specific data and la…

cs.LG2024★ 1 cited

A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024

Dimitris Spathis, Aaqib Saeed, Ali Etemad +6

This non-archival index is not complete, as some accepted papers chose to opt-out of inclusion. The list of all accepted papers is available on the workshop website.