most citedFrom Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models

48 citations · 53 across the 7 of their papers we have counts for

collaborators

7 papers

cs.HC2025

SnappyMeal: Design and Longitudinal Evaluation of a Multimodal AI Food Logging Application

Liam Bakar, Zachary Englhardt, Vidya Srinivas +4

Food logging, both self-directed and prescribed, plays a critical role in uncovering correlations between diet, medical, fitness, and health outcomes. Through conversations with nu…

cs.AI2025★ 3 cited

Sustainability assessment using multimodal AI agents

Zhihan Zhang, Alexander Metzger, Yuxuan Mei +7

Reducing the rapidly growing environmental impact of the computing industry requires assessing the emissions of electronics at scale. However, a traditional life cycle assessment (…

cs.RO2025

Set Phasers to Stun: Beaming Power and Control to Mobile Robots with Laser Light

Charles J. Carver, Hadleigh Schwartz, Toma Itagaki +7

We present Phaser, a flexible system that directs narrow-beam laser light to moving robots for concurrent wireless power delivery and communication. We design a semi-automatic cali…

cs.HC2025

Incorporating Sustainability in Electronics Design: Obstacles and Opportunities

Zachary Englhardt, Felix Hähnlein, Yuxuan Mei +6

Life cycle assessment (LCA) is a methodology for holistically measuring the environmental impact of a product from initial manufacturing to end-of-life disposal. However, the exten…

cs.HC2023★ 1 cited

DeltaLCA: Comparative Life-Cycle Assessment for Electronics Design

Zhihan Zhang, Felix Hähnlein, Yuxuan Mei +4

Reducing the environmental footprint of electronics and computing devices requires new tools that empower designers to make informed decisions about sustainability during the desig…

cs.AI2023★ 48 cited

From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models

Zachary Englhardt, Chengqian Ma, Margaret E. Morris +7

Passively collected behavioral health data from ubiquitous sensors holds significant promise to provide mental health professionals insights from patient's daily lives; however, de…

cs.SE2023★ 1 cited

Exploring and Characterizing Large Language Models For Embedded System Development and Debugging

Zachary Englhardt, Richard Li, Dilini Nissanka +6

Large language models (LLMs) have shown remarkable abilities to generate code, however their ability to develop software for embedded systems, which requires cross-domain knowledge…