Kaibo Liu

Kaibo Liu uses data science to develop practical systems and solutions for manufacturing, health care, energy, defense, and other applications. His research focuses on designing data acquisition systems, developing methodologies to analyze and utilize data, and applying these methods to identify root causes and make smart future degradation predictions and decisions.

Kaibo is pioneering unique data fusion algorithms that blend statistics with advanced machine learning methods. Data fusion combines large amounts of data from multiple sources to shed light on the underlying status of a system. Kaibo applies these methods in both industrial settings, where sensors collect vast amounts of data from machines, and in health care, where individual patient data is often sparse.

Kaibo has developed a series of new monitoring methodologies tailored to high-dimensional streaming data. Notably, his research has been funded and used by 3M to monitor production lines in real time, with more than 500 data streams. This has led to better product quality, reduced scrap and downtime, enhanced equipment safety, and decreased operation and maintenance costs. Kaibo has also developed methods for monitoring the progression of Alzheimer’s Disease, developing personalized methodologies to screen for this disease and predict its trajectory.

“Real impacts and real value are what I like about my work. Not only do I focus on scientific questions, but also practical impact. My aspiration is to contribute towards making the world a better place through my research.”