Yu-Fen (Andrea) Wang completed her graduate studies in Translational Medicine at Baylor College of Medicine. She then ventured into the pharmaceutical industry honing her skills in the management of clinical studies. Wang navigated the complexities of regulatory compliance, and mastered the intricacies of health economics and launch strategies, particularly within the hematology and oncology therapeutic domains. In 2017, Wang embarked on an entrepreneurial journey, co-founding the AHEAD project with a focus on developing machine learning algorithms for flow cytometry data analysis. Her commitment to the project’s development was further solidified in 2020 when she stepped up as CEO of AHEAD Medicine. Under Wang’s leadership, her team has achieved significant milestones, including acceptance into the prestigious UC Berkeley SkyDeck accelerator program and establishing key academic and industry partnerships in Asia and the US. AHEAD has proudly become a member of the NIST Flow Cytometry Standards Consortium, contributing to centralized data analysis for interlaboratory study data. In addition, Wang has collaborated with her team and Dr. Paul Wallace to co-author a chapter on AI for the forthcoming 5th edition of the Flow Cytometry Protocols, which is anticipated to be published in the coming months.
What inspired you to apply to the LDP or what are you looking forward to with the LDP?
Dr. Besty Ohlsson-Wilhelm, Dr. Paul Wallace and Dr. Virginia Litwin encouraged and supported me to apply for the LDP. I am excited about the prospect of contributing to the CYTO Innovation and Data Committee within ISAC, drawing on my specialized knowledge in machine learning algorithms and flow cytometry data analysis. My eagerness to collaborate with the community is driven by a shared goal to pioneer new methods for data standardization and to disseminate best practices. I am keen to streamline the data-sharing and querying processes on the flow repository platform, as well as to augment the analytical prowess of the field through the application of machine learning techniques.
Tell us a fun cytometry anecdote:
When I was doing new orientation to my engineers and explaining how cytometry and help identify different immune cells, they are usually overwhelmed by all these different cell types. I usually will recommend them to watch “Cells at Work” a Japanese manga and animation series, which would help them understand the different types of cells or physiological events at different episode.