Zhang Appointed Interim Chair of the Department of Computer Science

Aidong Zhang was one of the first computer scientists to apply the tools of her trade to analyzing biomedical data — an achievement that has brought the world closer to understanding and preventing disease. Today, she adds another accolade to her long list of accomplishments, this one at the University of Virginia, where she has spent the past two years continuing her important work.

Zhang, who joined the faculty of the School of Engineering and Applied Science in 2019, has been appointed the interim chair of the Department of Computer Science in the UVA School of Engineering and Applied Science.

It is a fitting accolade for a pioneer who was applying computer science tools to biomedical data well before computational biology became the bleeding edge of medicine.

Zhang, who earned a doctorate in computer science from Purdue University in 1994, embarked on her career a decade before the human genome was fully sequenced. The 2003 breakthrough — scientists discovered the complete genetic blueprint of the human species — meant biological pathways between human DNA and cells could be harnessed for targeted therapeutics.

But an understanding of how DNA works in relation to every gene in the human genome and genetic disease would have to be discovered first. The key to such a massive undertaking? Making sense out of the data that holds genetic information.

Luckily, Zhang had spent the prior decade creating tools to untangle such data.

Portrait of Dr. Aidong Zhang

Aidong Zhang, William Wulf Faculty Fellow and a professor of computer science with joint appointments in the Department of Biomedical Engineering and the School of Data Science, has been named the interim chair of The Department of Computer Science in the UVA School of Engineering and Applied Science. 

In 1994, she stepped into the intersection of mathematics and biomedicine in her first academic appointment as an assistant professor of computer science at the State University of New York at Buffalo’s School of Engineering and Applied Sciences. That is where a colleague in the School of Pharmacy asked if she could analyze some biomedical data.

“From there I realized they have a lot of data,” Zhang said. “It was the end of the 1990s, and machine learning was not that popular, but data mining was a part of data science.”

Into the mid-2000s, Zhang dedicated herself to using machine learning models for analyzing biomedical data. She was looking for patterns to pinpoint genes that behave similarly in patients with the same type of cancer. The goal was to isolate genes that play a role in disease development.

She quickly became one of the first computer scientists to specialize in this application of data science. Zhang published two books on her pioneering work: “Advanced Analysis of Gene Expression Microarray Data” in 2006 and “Protein Interaction Networks: Computational Analysis” in 2009.

“At that time, not a lot of researchers were doing this,” Zhang said. “I was one of the first to be using computer science techniques to analyze data, and we had just started. We needed a community of people in computer science and biology who were doing computational work.”

To address the need, Zhang formed the Association for Computing Machinery Special Interest Group on Bioinformatics, Computational Biology, and Biomedical Informatics in 2011. Membership tripled by 2017 just as the machine learning models Zhang had helped pioneer had evolved to become central players in the burgeoning fields that apply data science to biology.

Also during this time, Zhang authored over 300 peer-reviewed publications and obtained more than $15 million in research funding from agencies including the National Science Foundation, National Institutes of Health and the Department of Defense, in addition to stepping into leadership at SUNY.

In 2009, she was appointed chair of the SUNY Department of Computer Science and Engineering. During her six-year tenure, she hired 18 faculty members and restructured the department’s research program. In 2014, she was named a SUNY Distinguished Professor, the highest academic rank for any faculty member in the State University of New York system.

One year later, in 2015, Zhang took a leave from SUNY to serve as a program director in the National Science Foundation’s Division of Information and Intelligent Systems. She left the prestigious three-and-a-half-year appointment to return to her academic roots, joining the faculty at UVA.

Zhang was named the William Wulf Faculty Fellow and a professor of computer science with joint appointments in the Engineering School’s Department of Biomedical Engineering and the School of Data Science. Her mission at UVA is to continue her research in collaboration with biologists.

“Twenty years ago, we had the capability to measure gene expression quickly, but back then it was very expensive,” she said. “Today, gene sequencing is affordable and quick. Because sequencing data can be measured, we are generating an enormous amount of it. Biologists cannot keep up with the massive data.”

That is where Zhang’s machine learning models come into play. Her tools digest volumes of data that would be impossible as a human-only task to form understandings.

“You come up with models that you are feeding very specific biomedical information, and over time, the machine becomes smarter and is able to recognize patterns,” said Zhang, a fellow of the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery and, most recently, the American Institute for Medical and Biological Engineering.

Zhang stresses that although math is the same no matter what the task, the models that apply the math need to be customized for different types of biomedical data and to uncover different patterns. Formulating an understanding of the data, as well as the problem that is being researched, is a critical component in each of her collaborations with faculty in biomedical engineering, biochemistry and medicine.

“I work with my collaborators to build the methods that they can apply to their data,” she said. “They also use the tools in hospitals to evaluate the data. Anything we predict has to be verified.”

The collaborators’ published research adds to an arsenal of new findings that other biologists, biochemists and physicians can access — all contributing to a worldwide movement toward one day having a complete understanding of gene expression and how it contributes to disease.

“I strongly believe that we will eventually be able to prevent disease based on your DNA, because we will see what potential diseases you have,” Zhang said. “That is the long-term goal.”

Zhang began her appointment as interim chair on August 25. She succeeds Kevin Skadron, Harry Douglas Forsyth Professor of Computer Science, who is returning to the faculty after nine years of department leadership.

“Aidong contributes years of experience as a transformative department chair as well as an incredibly accomplished and respected researcher and leader in her field,” Skadron said. “I know the department will be in experienced hands and that she will provide strong leadership in all facets of managing the department.  We’re fortunate that she was willing to take on this responsibility.”