Lab Philosophy

Mission Statement

Our lab aims to shed light on fundamental principles of human motor control and learning. To this end, we develop theories that are formalized, tested, and refined by combining computational modeling and behavioral experiments. We strive to practice open science and will develop open-source software that supports scientific rigor, regardless of discipline. All of this will be accomplished in a welcoming and collaborative environment that serves as a training ground for a diverse group of creative scientists.

The Big Picture

Scientific research is extremely rewarding, but it does come with a large set of challenges. A helpful strategy to develop early on is to learn to focus on, and appreciate, the process of doing science, perhaps above all else. No matter whether an experiment goes to plan, or a manuscript or grant gets rejected, there is still a great deal of satisfaction to be derived from applying your mind to a tough question and learning something new, or simply seeing an experiment through so that you can design a better one for next time. Of course, this is easier said than done, especially when you need to hit specific benchmarks. And results definitely matter, too! But experience has shown me over and over again that if you’re persistent, rigorous, and thorough, it’s just a matter of time until you do start to see the fruits of your labor, both in terms of interesting results as well as improvements in your scientific skills and knowledge.

One of the most rewarding aspects of scientific research is the collaborative nature of the work. A lab makes meaningful strides when a small collective of individuals works together with the common purpose of making new discoveries and the shared goal of helping to make those around themselves better. Below are some guiding principles to help us all be successful.

Guiding principles

1) Scientific integrity

• Take the extra time to make sure your work is thorough, systematic, and reproducible (see point 3). While it may take more time up front, this advice will save you loads of time (and stress) in the long run when you’re not scrambling to figure out how a piece of code works, how to fix a figure, where a file is stored, etc.

• Think deeply about your projects. Think through the validity of a hypothesis/method/result and, ideally, try to follow-up on your questions by designing a new experiment or model.

2) Learn to lead

• This is specifically in reference to your research projects, education, and career. Ask your questions during one-on-one meetings, lab meetings, seminars, etc. You know better than anyone what you need to make progress.

• Don’t let the fear of making a “mistake” prevent you from trying something, especially something new and potentially helpful to you in the long run. Besides, we all make mistakes, and no matter how silly they may seem in hindsight, we learn from them and do better the next time. As the late, great Miles Davis said: “It’s not the note you play that’s the wrong note—it’s the note you play afterwards that makes it right or wrong.”

• Share, and teach, what you know to others.

3) Be a good scientific citizen

• Practice open science.

• Volunteer to give talks, lead journal club discussions, and be a science advocate.

• Volunteer to be a mentor, especially for programs that aim to provide more research opportunities for underrepresented groups in STEM.

• When providing feedback, focus on problem solving rather than critique.