One of my goals as an advisor for postdocs, PhD students, and undergraduate researchers in the lab is to train the next generation of researchers. Here I describe my expectations for a healthy advisor-advisee relationship.
Student Development: The goal of the PhD is for students to develop their own research directions and the skill set necessary for independent work. Towards that goal, students are encouraged to explore a wide array of areas, to develop computational maturity through coursework or engagement with the scientific literature, and to refine their “research taste.” I am committed to providing professional development support for students towards post-PhD jobs in academia, industry, startups, public policy, or something else altogether.
Research Philosophy: We’re an interdisciplinary group that seeks to develop machine learning and other computational methods to transform healthcare into a more patient-centered and equitable system. These goals will require machine learning expertise, clinical domain knowledge, and ethical thinking. We place a heavy emphasis on rapid prototyping, collaborative brainstorming, and clear communication. Students will engage directly with collaborators in medicine, public health, and other fields to ensure real-world relevance. We define impactful research as work that challenges how the field thinks about equity, health, or machine learning, and we are less interested in outperforming benchmarks or technical novelty for its own sake.
Meetings: Meeting with students is one of my favorite things about my job, and I actively look forward to my time talking through papers or getting into the weeds about an idea. I meet with each student on average once a week. When a student is new to the lab or to a research direction, I prioritize more frequent meetings with the student and reduce the frequency as they become more independent. These meetings can involve high-level project brainstorming, low-level technical discussions, and general life and career planning. We hold group meetings once a week where we read through a paper in-depth or host an outside speaker.
Group Structure: The group is currently three PhD students (one of whom is co-advised) along with several undergraduates. Individual interests range from NLP to climate change to treatment protocol planning. Students are strongly encouraged but not required to work in person from either our UC Berkeley or UCSF Mission Bay campus to promote cross-pollination and peer mentoring. I am generally available online for quick questions (excluding unplugged vacations), but I do not expect students to be similarly available.
Diversity and Inclusion: We celebrate the innovation and skill-sharing that a heterogeneous lab group can create. Students are encouraged to bring their full selves to work, and we celebrate the differences in student interests, backgrounds, and perspectives. I strive to create an environment where students can share suggestions or concerns, take the rest they need, and persevere through the challenges of research.