A different kind of biology: A computer expert’s embrace of biomedical informatics

A high school biology class planted the seed of what would eventually grow into a career in informatics for Hongfang Liu, PhD. While her teacher recognized her natural aptitude for biology and encouraged her to pursue the major in college, Liu was not convinced.

“I didn’t like the wet lab where we had to actually be hands-on with things,” says Liu, now Professor and D. Bradley McWilliams Chair at McWilliams School of Biomedical Informatics at UTHealth Houston.

Drawn instead to mathematics and computer science, Liu went on to earn undergraduate and several advanced degrees in the fields. Still, the encouragement she received from her high school teacher lingered.

“When you are a teenager and your teacher says you’re good at something, it sticks with you,” she says. “I realized that with biomedical informatics, I could combine biology with my interest in computer science.”

That insight began to crystallize after she completed a master’s degree in applied mathematics. She spent a summer interning with the National Center for Biotechnology Information, an offshoot of the National Institutes of Health that provides access to biomedical and genomic information for researchers. The experience helped her gain valuable knowledge in the emerging field of biomedical informatics and set her on a path that would define her career.

Soon after, she landed a research assistant position at Columbia University, focusing on clinical natural language processing—a way to use artificial intelligence to analyze text created during clinical operations. This method addresses a singular problem: Although the nation’s health care system creates significant amounts of data, much of this information exists in text, fragmented among patient records, clinical notes, discharge summaries, and similar documents. While humans may struggle to see the big picture amidst all the pieces, artificial intelligence can extract that data, remove personal information to protect privacy, and analyze it to provide relevant insights that enhance health care.

After earning a doctorate in computer science and spending her early academic career in bioinformatics, Liu was hired as one of the first computer scientists at the Mayo Clinic, where she helped lead the institution’s new data analysis efforts.  

“We created a platform that allowed us to leverage clinical data for research, quality improvement, and clinical decision support,” she says.

Liu spent the next 12 years building and enhancing the platform until she was recruited to join the faculty at McWilliams School of Biomedical Informatics in 2023.

She found that UTHealth Houston and its clinical partners had extensive amounts of clinical data, potentially containing valuable insights that could help a wide range of patient populations. Ideally, university researchers would be able to use that data for their studies if they had tools to extract and analyze the information. Today, Liu and her team are collaborating with experts across the university to make this work possible by developing a translational artificial intelligence program and implementing the UTHealth Houston learning health system.

To guide this work, Liu developed a framework that focuses on three essential goals: building strong collaborative teams to make AI an empowering tool for health care providers; ensuring that the technology is trustworthy, transparent, and grounded in real-world needs; and using data in a way that is rigorous, ethical, and reusable across systems and studies.

“We generate a vast amount of information in the process of providing care, and we are really limiting ourselves if that data is not available for our research,” Liu says.

As the inaugural holder of the McWilliams Chair—established in 2023 by D. Bradley McWilliams as part of a commitment to name McWilliams School of Biomedical Informatics—Liu receives reliable funding from the endowment each year to support her work. For the past two years, she has used distributions from the chair endowment to organize the TMC AI Summit, an event that brings together Texas Medical Center experts to collaborate on how they can use artificial intelligence to improve health. The endowment also helps provide funds for proof-of-concept studies, generating data that can be used to gain large government grants.

Liu values UTHealth Houston’s people-first mentality and the collaborative opportunities offered by the Texas Medical Center. She believes these and other advantages provide a solid foundation for the university’s future growth in the rapidly advancing field of informatics.

“I have felt welcomed here, and I think our team has established excellent roots,” she says. “I look forward to seeing the results of our work.”