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High-caliber contributors: Dissertation Award winners ready to make big impacts

The Dean’s Dissertation Award recognizes graduating doctoral students who excel as researchers and leaders. This year, the Ira A. Fulton Schools of Engineering honors the work of Bing Si, who will be awarded her doctorate in industrial engineering, and Hoi-To Wai, who received his doctorate in electrical engineering.

“Because of the caliber of our doctoral students, selecting the recipients for the Dean’s Dissertation award is one of the most difficult things we do each year,” says Kyle Squires, dean of the Ira A. Fulton Schools of Engineering at Arizona State University. “Bing and Hoi-To are both excellent students, and are making significant contributions in the way technology, particularly big data, impacts the lives of all people.”

Photo of Bing Si holding a plaque next to Kyle Squires. Caption: Bing Si received the 2017 Dean's Dissertation Award from Dean Kyle Squires at the Fulton Schools' Fall 2017 Convocation. Photographer: Jessica Hochreiter/ASU

Bing Si received the 2017 Dean’s Dissertation Award from Dean Kyle Squires at the Fulton Schools’ Fall 2017 Convocation. Photographer: Jessica Hochreiter/ASU

Bing Si

In her research, Si developed data fusion and system informatics approaches that can improve the quality and performance of health care systems, from diagnosis to care to system-level decision-making. Health care is now a data-rich environment, thanks to technology advancements in diagnostic imaging, smart sensing and health information systems.

“It is now possible to track every piece of information related to a patient’s diagnosis, treatment and care,” Si explains. “This offers a great opportunity for precision medicine: the ability to offer the right medical decision to the right person at the right time.” But, she adds, the size and complexity of the data overwhelm the modeling capability of existing statistical methods.

In her dissertation, Si focuses on the emerging problems in health care and develops novel statistical models and machine learning algorithms to tackle these problems. Her work could impact the understanding of conditions such as migraine disorder and traumatic brain injury, and could lead to personalized diagnostic biomarker optimization for Alzheimer’s disease. It might also enable joint data mining of electronic medical records and hospital operational data to improve the quality and safety of health care delivery.

Si’s advisor, Associate Professor Jing Li, is co-director of ASU-Mayo Imaging Informatics Lab. She said Si is the top industrial engineering doctoral student at ASU and is a leader in the lab. She won the Grace Hopper Award for her role in championing female and minority students in analytics, computing and health care. Li added that Si has already published in premier journals, and “her research has also generated translational impact on medicine and health care.”

Hoi-To Wai

Photo of Hoi-To Wai holding a plaque next to Kyle Squires. Caption: Hoi-To Wai received the 2017 Dean's Dissertation Award from Dean Kyle Squires at the Fulton Schools' Fall 2017 Convocation. Photographer: Jessica Hochreiter/ASU

Hoi-To Wai received the 2017 Dean’s Dissertation Award from Dean Kyle Squires at the Fulton Schools’ Fall 2017 Convocation. Photographer: Jessica Hochreiter/ASU

Hoi-To Wai commenced his doctoral studies in electrical engineering at the University of California, Davis, and later moved with his advisor, Professor Anna Scaglione, and her lab to the Fulton Schools in 2015. One of the most important contributions of Hoi-To Wai’s doctoral dissertation is that it makes network science research more efficient. Wai studies social networks: the internet and other platforms where people interact every day. He developed new algorithms that run on networks to solve machine learning and estimation problems.

The work provides theoretical guarantees to certain aspects of network science.

“My results can be used to learn the amount of ‘trust’ between you and your friends on Facebook, or they can be used to guide biologists in designing experiments for understanding the interaction between the genes in organisms — without wasting their time on performing more experiments,” he explains. “It can also provide guaranteed ways to solve machine-learning problems effectively over a computer network.”

“Hoi-To Wai is one of the brightest and most prolific students I have ever had the privilege to guide,” says Scaglione.

Other students in her lab look up to him and consult with him when they confront tough problems.

“He is self-directed and his mastery of the techniques and concepts of optimization and in statistical signal processing is exceptional. This is what allows him to solve a variety of problems with ease.” Scaglione points to the high number of journal articles Wai has already published, and the international network of collaborators he has already established. “I am confident that a wonderful career as a scholar awaits him.”

Going forward, Wai will be a postdoctoral scholar at ASU, continuing his research on network science and data analytics. In spring 2019 he will join his undergraduate alma mater, Chinese University of Hong Kong, as an assistant professor.

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Fulton Schools

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