2 citations · 3 across the 12 of their papers we have counts for
12 papers
PSI: Shared State as the Missing Layer for Coherent AI-Generated Instruments in Personal AI Agents
Zhiyuan Wang, Erzhen Hu, Mark Rucker +1
Personal AI tools can now be generated from natural-language requests, but they often remain isolated after creation. We present PSI, a shared-state architecture that turns indepen…
SocialPulse: On-Device Detection of Social Interactions in Naturalistic Settings Using Smartwatch Sensing
Md Sabbir Ahmed, Kaitlyn Dorothy Petz, Noah French +6
Social interactions are fundamental to well-being, yet automatically detecting them in daily life-particularly using wearables-remains underexplored. Most existing systems are eval…
WatchAnxiety: A Transfer Learning Approach for State Anxiety Prediction from Smartwatch Data
Md Sabbir Ahmed, Noah French, Mark Rucker +6
Social anxiety is a common mental health condition linked to significant challenges in academic, social, and occupational functioning. A core feature is elevated momentary (state)…
SocialPulse: An On-Smartwatch System for Detecting Real-World Social Interactions
Md Sabbir Ahmed, Arafat Rahman, Mark Rucker +1
Social interactions are a fundamental part of daily life and play a critical role in well-being. As emerging technologies offer opportunities to unobtrusively monitor behavior, the…
Understanding State Social Anxiety in Virtual Social Interactions using Multimodal Wearable Sensing Indicators
Maria A. Larrazabal, Zhiyuan Wang, Mark Rucker +4
Mobile sensing is ubiquitous and offers opportunities to gain insight into state mental health functioning. Detecting state elevations in social anxiety would be especially useful…
Personalized State Anxiety Detection: An Empirical Study with Linguistic Biomarkers and A Machine Learning Pipeline
Zhiyuan Wang, Mingyue Tang, Maria A. Larrazabal +6
Individuals high in social anxiety symptoms often exhibit elevated state anxiety in social situations. Research has shown it is possible to detect state anxiety by leveraging digit…
Wearable Sensor-based Multimodal Physiological Responses of Socially Anxious Individuals across Social Contexts
Emma R. Toner, Mark Rucker, Zhiyuan Wang +8
Correctly identifying an individual's social context from passively worn sensors holds promise for delivering just-in-time adaptive interventions (JITAIs) to treat social anxiety d…
Infinite Action Contextual Bandits with Reusable Data Exhaust
Mark Rucker, Yinglun Zhu, Paul Mineiro
For infinite action contextual bandits, smoothed regret and reduction to regression results in state-of-the-art online performance with computational cost independent of the action…
Personalized Reward Learning with Interaction-Grounded Learning (IGL)
Jessica Maghakian, Paul Mineiro, Kishan Panaganti +3
In an era of countless content offerings, recommender systems alleviate information overload by providing users with personalized content suggestions. Due to the scarcity of explic…
Eigen Memory Trees
Mark Rucker, Jordan T. Ash, John Langford +2
This work introduces the Eigen Memory Tree (EMT), a novel online memory model for sequential learning scenarios. EMTs store data at the leaves of a binary tree and route new sample…
Inverse Reinforcement Learning for Strategy Identification
Mark Rucker, Stephen Adams, Roy Hayes +1
In adversarial environments, one side could gain an advantage by identifying the opponent's strategy. For example, in combat games, if an opponents strategy is identified as overly…
Reward Shaping for Human Learning via Inverse Reinforcement Learning
Mark A. Rucker, Layne T. Watson, Matthew S. Gerber +1
Humans are spectacular reinforcement learners, constantly learning from and adjusting to experience and feedback. Unfortunately, this doesn't necessarily mean humans are fast learn…