What I do: Artificial intelligence (AI) and data science have become a major force to transform science and society. As the MIDAS Executive Director, I lead my institute’s effort to enable the adoption of AI and data science methods across research fields and catalyze research breakthroughs, upskill academic researchers, improve the rigor and reproducibility of research, and ensure the responsible use of data and AI. In addition, I build partnerships with academia, industry, government and community organizations, both for research collaboration and for maximizing the societal impact of data science and AI. Working with colleagues at data science institutes across universities, I seek to improve the institutional capacity of academic research.
I also co-direct our postdoctoral training programs, the Michigan Data Science Fellows program, the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship program, and the Eric and Wendy Schmidt AI in Science African Faculty Fellows program.
Recent fun projects: As the research community (and many others) embraces wave after wave of AI technology advancement, we are at a pivotal time to reconsider many fundamental issues about science and scientists. What is the purpose of science? What should be the roles of AI and human scientists in the scientific discovery process? How should the academic research model keep up with the pace of discovery? I am organizing and participating in conversations around these topics and using the insight from such conversations to guide our work.
The fact that AI is now an important player in scientific research is changing the research ecosystem in significant ways, including the cost and incentives of research, the time from problem postulation to discovery, and the time from discovery to practical solutions. Because of all these, we also need to reimagine how the public and private sectors collaborate in research and discovery. I lead projects in collaboration with cross-sector partners such as Microsoft and Detroit to develop examples of effective collaboration.
Who I am: I am a scientist by training. I received my PhD degree from the California Institute of Technology, where I studied how animal development is shaped by genetic factors and the molecular signaling pathways, with Dr. Paul Sternberg as my mentor. Caltech was a special place for me, where I had endless discussions with my fellow students and professors – often into the wee hours of the morning – about all kinds of exciting (and sometimes “crazy”) science ideas and let our imaginations take flight. I did my postdoc training at Stanford University with Dr. Bill Newsome, using electrophysiology and psychophysics to study the neural mechanism of visual motion perception and cognition. During my training, I became fluent in statistics and coding, and started exploring AI (very new to visual neuroscience at the time). After a short stint as a faculty member at the University of Michigan, I moved to research administration because what I truly enjoy is to see “the big picture” and to advance science in a broad way.
Why I’m passionate about my work: We are at a historic moment because we get to shape how AI transforms lives and society, and I want to make a real contribution. I am enjoying my work everyday because there is so much that we can do and so many challenges that we need to ponder and address, intellectually and practically. As a scientist, I feel the excitement and a sense of duty to help ensure that data and AI are a positive force in our society, not a new way to cause harm.
Fun facts: In addition to science, I love books and classical music. I also write and translate about science and education, and have received multiple awards including China Book Award and China National Library Book Award. I am also a serious piano student. My favorite piece of volunteer work was that I built a math club and taught for 8 years at Martin Luther King Jr. Elementary School (Ann Arbor), where I got to show the kids how much fun math can be and how amazing they can be at math.