Luella Fu


I am Luella Fu, an assistant professor in the Mathematics Department, at San Francisco State University. I have only been here a short while but I have already benefited immensely from supportive colleagues and diligent students. I am excited to be here.

My methodological focuses are in nonparametric empirical Bayes methods and multiple testing. Like much of statistics, these methodologies grew from difficulties in real data. Specifically, genome sequencing technology allowed scientists to contrast thousands of genes ("large-scale" data) between sick and healthy patients for a wide variety of illnesses, but the scientistis needed a way to accurately detect which genes were related to illness and which were not ("multiple testing"). My enthusiasm for this field comes from its potential to expand into the technological realm, where multiple testing frameworks can provide mathematically-grounded algorithms for fraud detection and quality control. There is still a lot of work to be done here both algorithmically and theoretically because the scale of online data is such that the error rates need to be much lower than what is traditionally acceptible. There is also a lot of opportunity in online data because there is so much information that can be used to create models that require fewer statistical assumptions but that still have mathematical properties ("nonparametric empirical Bayes methods").This is an amazing field with so many applications to large-scale data and so much still to develop in terms of theoretically-backed statistical techniques.I am also interested in how statistics are used in other applications, and have worked on medical and social network problems. Click for my CV.

Teaching is also a primary interest of mine. I especially enjoy teaching with statistical programming and class exercises because these components make class more interactive and oriented towards problem-solving. I would like to model a class on An Introduction to Statistical Learning with Applications in R, because the material's practical focus may make it a good candidate for flipping a classroom. In class, students could implement algorithms in R, have more resources to troubleshoot their difficulties, and exchange thoughts. At home, they could watch lecture segments at their own pace. Having attended teaching workshops given by SFSU's Center for Equity and Excellence in Teaching & Learning and at USC's Center for Excellence in Teaching, I realize that good teaching is built upon many, many possible practices. I am still experimenting with a few and hope to build up to classroom flipping.

My graduate school experience was illuminated by faculty, collaborators, and peers. My co-advisors were Dr. Wenguang Sun and Dr. Gareth James. Their quality of thought, creativity, and work flow inspire me all the time.

Other collaborators with whom I have worked closely have included Dr. Pallavi Basu on multiple testing; my sister Dr. Sue Fu on a study of surgical costs; and Dr. Thomas Valente, Megan Jacobs, Jody Brookover, Dr. Nate Cobb, and Dr. Amanda Graham on social network and health research. When conducting research on model selection, I was also advised by Dr. Yingying Fan and Dr. Jinchi Lv.

My community made a hugely positive impact on my life and research. Dr. Courtney Paulson and Dr. Pallavi Basu were a joy with whom to share part of the PhD experience, while Dr. Xinghao Qiao fearlessly led the way for us all! PhD students Weinan Wang, Trambak Banerjee, and Josh Derenski were great company and made me very proud of our PhD program. I was also fortunate that my time overlapped with PhD students Brad Rava, Simone Shao, and Patrick Vossler, who greatly added to my community. I am deeply grateful to everyone mentioned and also to the former PhD chair Dr. Greys Sosic, worked very patiently and with great sensitivity with us students. Also, decades of thanks go to my best friend Dushan Perera, who took my website design from the '90s into the 21st century.