Tung-Che Liang — accepted AI-conference papers

2021

Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning

Tung-Che Liang, Jin Zhou, Yun-Sheng Chan, Tsung-Yi Ho, Krishnendu Chakrabarty, Cy Lee

ICML 2021spotlight

Microfluidic biochips are being utilized for clinical diagnostics, including COVID-19 testing, because of they provide sample-to-result turnaround at low cost. Recently, microelectrode-dot-array (MEDA) biochips have been proposed to advance microfluidics technology. A MEDA biochip manipulates drople…

Cited by 16 Source ↗PDF ↗code ↗Scholar ↗

2020

Adaptive Droplet Routing in Digital Microfluidic Biochips Using Deep Reinforcement Learning

Tung-Che Liang, Zhanwei Zhong, Yaas Bigdeli, Tsung-Yi Ho, Krishnendu Chakrabarty, Richard Fair

ICML 2020poster

We present and investigate a novel application domain for deep reinforcement learning (RL): droplet routing on digital microfluidic biochips (DMFBs). A DMFB, composed of a two-dimensional electrode array, manipulates discrete fluid droplets to automatically execute biochemical protocols such as poin…

Cited by 37 Source ↗PDF ↗code ↗Scholar ↗