Posts by Collection

news

Pura Travel

Published:

Earned the President Undergraduate Research Award ($1500) to support my work on EEG/SSVEP sensing!

Urop Symposium

Published:

Glad to share my work about non-laboratory SSVEP recognition at Georgia Tech’s Undergraduate Research Symposium!

Msu Intern

Published:

I am glad to share that I will start working as a professional research assistant with Dr. Jinxing Li at Michigan State University!

Snel

Published:

Joined SNEL! Advised by Dr. Chethan Pandarinath and Dr. Samuel R. Nason-Tomaszewski.

Flexegg

Published:

FlexEGG, our skin-conformal electronics for wearable electrogastrography, is out in IEEE Journal on Flexible Electronics.

Adapskin

Published:

AdapSkin, our age-adaptive polymeric skin electronics for better neural data and ML accuracy, is published in Device!

projects

publications

Towards a high-frequency SSVEP-BCI system

Yunnuo Zhang

Published in Undergraduate Thesis, Georgia Institute of Technology, 2025

Summary

A high-frequency SSVEP-based brain-computer interface designed for use outside the lab. It combines dry-contact spring-loaded electrodes with active buffering, an actively driven guard, and a driven-right-leg circuit, plus an LED stimulus flickering above the threshold of visual perception for more comfortable everyday use.

Brain-Computer Interface, EEG, Wearable Electronics Thesis

Contrastive Time Series Representation Learning for Neurochemical Concentration Prediction

Na Dai, Abdallah Daha, Joshua Labbe, Zhengxu Tang, Yunnuo Zhang, Jinxing Li

Published in NeurIPS 2025 Workshop on Learning from Time Series for Health, 2025

Summary

A metadata-aware contrastive learning framework for predicting neurochemical concentrations from fast-scan cyclic voltammetry (FSCV). It models batch identity, scan sequence, and scan rate, and uses preference-based ranking losses to learn discriminative voltammetry features, improving accuracy over traditional baselines.

FSCV, Machine Learning, Time Series OpenReview

Skin-conformal electronics for wearable electrogastrography monitoring

Liuxi Xing, Yulu Cai, Yunnuo Zhang, Vittorio Mottini, Linux Heller, Jinxing Li

Published in IEEE Journal on Flexible Electronics, 2025

Summary

FlexEGG is a soft, stretchable abdominal electrode array built from a hybrid conductive-polymer and silver-nanowire conductor, enabling high-fidelity electrogastrography (EGG) monitoring of gastric myoelectrical activity in clinical and real-world settings.

Electrophysiological Sensing, Wearable Electronics IEEE Xplore

Age-adaptive polymeric skin electronics enhance neural data and machine learning accuracy

Vittorio Mottini, Liuxi Xing, Yulu Cai, Charlie Meilinger, Soham Inamdar, Xiang Calvin Chen, Bahareh Tajvidi Safa, Jiaqi Wang, Yi Xing, Jack Darbonne, Zhengxu Tang, Yunnuo Zhang, Christopher H. Contag, Ruiguo Yang, Mi Zhang, Jinxing Li

Published in Device, 4(1), 2026

Summary

AdapSkin is a stretchable, bioadhesive conductive-polymer skin interface that adapts to age-related changes in skin such as dryness and wrinkles. By improving skin-electrode contact, it reduces variation in impedance, signal-to-noise ratio, and motion artifacts, yielding higher-quality surface EMG and better machine learning accuracy for neuromuscular assessment.

Electrophysiological Sensing, Machine Learning, Wearable Electronics Paper Preprint

A generalizable speech neuroprosthesis

Zachery M. Fogg, Nicholas S. Card, Maitreyee Wairagkar, Aparna Srinivasan, Tyler Singer-Clark, Xianda Hou, Elizaveta Okorokova, Hamza Peracha, Carrina Iacobacci, Tiffany Brailow, Justin Jude, Hadar Levi-Aharoni, Trung Le, Domenick Mifsud, Pranav I. Deevi, Samuel R. Nason-Tomaszewski, Anna L. Pritchard, Yunnuo Zhang, Brice Richards, Payton Bechefsky, Leigh R. Hochberg, Ziv Williams, Kiarash Shahlaie, Nicholas AuYong, Daniel B. Rubin, Chethan Pandarinath, David M. Brandman, Sergey D. Stavisky

Published in bioRxiv (preprint), 2026

Summary

A transformer-based decoder trained jointly across six intracortical speech BCI participants outperforms single-user models for every participant, cutting relative word error rate by over 50% on average. A new user can reach under 7% word error rate after finetuning on fewer than 200 sentences.

Brain-Computer Interface, Machine Learning, Speech Neuroprosthesis bioRxiv

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.