most citedConcurrence: A dependence criterion for time series, applied to biological data

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Micro-DualNet: Dual-Path Spatio-Temporal Network for Micro-Action Recognition

Naga VS Raviteja Chappa, Evangelos Sariyanidi, Lisa Yankowitz +4

Micro-actions are subtle, localized movements lasting 1-3 seconds such as scratching one's head or tapping fingers. Such subtle actions are essential for social communication, ubiq…

cs.CV2025

Bitbox: Behavioral Imaging Toolbox for Computational Analysis of Behavior from Videos

Evangelos Sariyanidi, Gokul Nair, Lisa Yankowitz +8

Computational measurement of human behavior from video has recently become feasible due to major advances in AI. These advances now enable granular and precise quantification of fa…

eess.SP2025★ 1 cited

Concurrence: A dependence criterion for time series, applied to biological data

Evangelos Sariyanidi, John D. Herrington, Lisa Yankowitz +8

Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often exhibit complex non-linear interactions…

cs.HC2025

Developer Insights into Designing AI-Based Computer Perception Tools

Maya Guhan, Meghan E. Hurley, Eric A. Storch +5

Artificial intelligence (AI)-based computer perception (CP) technologies use mobile sensors to collect behavioral and physiological data for clinical decision-making. These tools c…

eess.SP2025

Measuring Dependencies between Biological Signals with Self-supervision, and its Limitations

Evangelos Sariyanidi, John D. Herrington, Lisa Yankowitz +6

Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often exhibit complex non-linear interactions…

cs.HC2025

Stakeholder Perspectives on Humanistic Implementation of Computer Perception in Healthcare: A Qualitative Study

Kristin M. Kostick-Quenet, Meghan E. Hurley, Syed Ayaz +7

Computer perception (CP) technologies (digital phenotyping, affective computing and related passive sensing approaches) offer unprecedented opportunities to personalize healthcare,…