image credit Loren Long; Children's book Good Day, Good Night written by Margaret Wise Brown.

Thanks for your interest!

Recruitments for this year have closed, but feel free to reach out if you're interested in working in the lab in the future!

Graduate students: New applications will be considered in Dec 2024.

Here are some general resources for applying to graduate school.
Here is general information on applying graduate school in UCSD Psychology;
Don't miss the option to submit a fee waiver if you qualify.

This Twitter thread also rounds up lots of useful resources for prospective applicants.

The lab will likely be admitting a student(s) through UCSD's graduate program in the 2024-2025 admissions cycle to start in Fall 2025. I am open to co-mentorship with other faculty. I am not taking meetings with potential graduate students, though I look forward to seeing your materials! Your research statement should describe (1) your current research interests and why they are a good fit for the Visual Learning Lab, and (2) what skills/interests have you acquired during your previous research experiences. It's unlikely that you'll have expertise in developmental psychology, machine learning, AND vision science—that's ok! Let me know what parts of your experience and future interests overlap, and try to be specific. For example, you might be mostly interested in running large-scale behavioral experiments with kids (to address what questions)?, or mostly interested in building computational models (what kind?). You can see the Research page on this site for some broad overview on what I think we'll work on together. There are also more details on what you can expect the lab to be like under the headings below ("what it's like" and "what we're looking for").

What's it like to work with you?

I truly enjoy working with mentees, and it's one of the reasons I've chosen to stay in academia. I am committed to creating a lab environment in which mentees from all backgrounds can thrive and feel empowered to contribute. Inclusivity and respect for others —no matter their level of expertise!—are key values in our lab. Our lab will be constructed with the goal of providing an intellectual environment that respects and celebrates the full spectrum of human diversity in race, ethnicity, gender identity, age, socioeconomic status, national origin, sexual orientation, disability, and religion.

You can also expect me to support you in whatever shape your career may take: I have had incredible mentors who have supported me throughout setbacks and helped me find my path in science, yet I realize that academia is only one path of many. Practically speaking, this might look like helping you prepare for interviews or internships outside of academia or promoting your academic work to potential postdoc advisors at other institutions. Regardless, I will work with you to develop an Individual Development Plan and solicit regular feedback from you and others in the lab about how things are going—I won't be a perfect mentor, and we'll all still be learning.

The Visual Learning Lab will also be built with foundations in the Open Science movement—for example, our data will be "born open", and our focus will be creating reusable resources and skills and enabling better science rather than advancing specific theoretical agendas. Towards that end, you can also expect there to be regular co-working sessions, "code parties", and hackathons where we learn and create together.

Interviewees will have the option to meet with past advisees if they would like in order to get honest feedback about what it’s like to work with me. Check back here for a mentorship statement and lab manual.

What is the lab looking for?

Our lab is seeking individuals with broad interests in any of the topics mentioned so far and a commitment to creating an inclusive, welcoming, and supportive lab culture. In addition, we see the following skill sets as foundational:

Data management & statistical thinking: Research projects will involve collecting, wrangling, managing, and analyzing high-dimensional and messy datasets. Practically, you should be familiar with some combination of the major programming languages used for scientific computing, e.g., Python and R, which are the main programming languages used in the lab. Ideally, you will have used these skills in another context, and/or have taken courses in statistics, data science, and/or machine learning.
Communication & organization skills: It is essential for scientists to be able to communicate with each other and with others about their ideas, process, mistakes (yes, we all make mistakes!), and findings. This relies on good oral and written communication skills and a high-level of attention to detail—particularly when it comes to project management! Our lab will use a standard set of tools (e.g., GitHub, OSF repositories) in order to facilitate project management. But a good working relationship (and lab culture) is built upon a foundation of open communication between all parties.
A readiness to learn and to try new things. We are looking for individuals who are ready to learn new skills —who are comfortable being uncomfortable and learning new skills as they go. Research often involves being uncomfortable with something that's new or challenging in some way, and our interdisciplinary work also integrates many different technical skills. This means that almost every lab members will be learning something new (including me!). You should still apply even if you don't have the specific technical toolkit we've used in prior projects—what's most important is that you know how to dive into something new.
Curiosity & generosity. Science works best when we collaborate together as a team and help each other. A team spirit and willingness to help lab members with their projects, problems, and ideas is essential to a healthy and productive lab culture. We are looking for individuals who are curious about what they can learn from other's work and experiences, and who are generous with their time and intellect.