MD Anderson UTHealth Houston Graduate School Quantitative Science PhD student Alexandria Lau has been named one of the inaugural Institute for Data Science in Oncology (IDSO) Fellows. Her advisor is Yinyin Yuan, PhD who co-leads focus area one, Quantitative Analysis and Insights from Pathology and Medical Imaging.

Lau trains deep learning models to encode morphological features in solid tumor H&E images to create an annotator agnostic and data driven tumor subtyping system.

“Being an IDSO fellow means being part of the paradigm shift towards team data science at the institution to deliver AI empowered cancer care,” said Lau. “Each fellow brings a unique specialization where AI is deployed to the fellowship, and a standardized data science project lifestyle is developed through engagement from other fellows.”

On November 9, MD Anderson Cancer Center announced the launch of its Institute for Data Science in Oncology (IDSO), which integrates the most advanced computational and data science approaches with the institution’s extensive scientific and clinical expertise to significantly improve patient’s lives by transforming cancer care and research.

In connection with IDSO, a new fellowship program was created to help train the next generation of leaders in cancer care and research in the application of data science to oncology care, research, and operations. The program is designed to give junior physicians and researchers the skills they need to become data science leaders, with the ability to tailor their training to suit their individual needs for greatest impact.

The fellowship is led by MD Anderson faculty members Christopher Gibbons, Ph.D., associate professor, Symptom Research as director and Stephanie Schmidt, Ph.D., data science group leader, Genomic Medicine, as research director.

“This new program will allow our fellows to work with leading experts in data science and learn how to incorporate new tools and techniques into their own efforts,” says Gibbons. “We’re helping create the next generation of data science leaders.”

Each fellow is expected to spend two years working directly with a faculty mentor and learning from a structured curriculum that includes hands-on training and independent research collaborations. Lau is one of 17 fellows in the inaugural class.