Xinhe Zhang

This study uses flexible electrodes to track and model representational drift in mouse visual cortex, enabling a stable decoder for brain-machine interfaces.

This paper introduces growth-adaptive spring electronics and a spike processing pipeline to enable long-term, same-neuron mapping in developing rat brains, revealing neuron-specific developmental decorrelation.

DeviceAgent is an AI agent that integrates LLMs and VLMs to automate bioelectronics research tasks, demonstrating capabilities in design, fabrication, defect inspection, and electrophysiological analysis.

This paper introduces BCI-Agent, an AI framework that classifies neuronal cell types from electrophysiological data without fine-tuning, validated in rodent and human datasets.

BehaveAgent automates cross-species behavior analysis from video input using multimodal AI without manual intervention or retraining, enabling zero-shot reasoning and end-to-end analysis.

This paper introduces FlexiSoft, a flexible and robust electronic platform for brain-computer interfaces that enables long-term neural recording and curved implantation.

The paper introduces STAgent, an AI tool that automates spatial transcriptomics analysis, revealing in vivo maturation of human stem cell-derived pancreatic cells.

SpikeAgent automates spike sorting with a multimodal LLM-based AI agent, achieving curation consistency equal to or exceeding human experts and drastically reducing expertise barriers.

This paper introduces an AI-cyborg system that uses adaptive intelligent modulation to enhance cardiac organoid maturation through real-time feedback.

This paper introduces UnitedNet, a multi-task deep learning model for analyzing single-cell multi-modality data, showing improved performance in joint group identification and cross-modal prediction.