About CompetiLab

Who we are

CompetiLab is an interdisciplinary learning studio based in Taipei. We work with secondary school students, and with motivated younger students where it makes sense, on three kinds of work: independent academic research and writing, synthetic biology in the shape of the iGEM competition, and biodesign in the shape of the Biodesign Challenge.

We are a small, independent organization. We are not part of any competition, university or examination body, and we say so plainly wherever it might otherwise be assumed.

Our mission

Young people should not merely learn established knowledge. They should learn to ask original questions, investigate problems, collaborate across disciplines, and communicate ideas that matter. Our mission is to build an environment where that kind of learning is normal, rigorous and honest.

Why independent research matters

School teaches answers. Research teaches what to do when there is no answer yet. A student who has carried a question from vague interest to a defensible finding has learned to tolerate uncertainty, to read critically, to keep records, to accept critique, and to write for a reader who does not already agree. Those habits outlast any particular subject.

Independent research also gives students something that is theirs. The work is not an assignment; it is a contribution, however small, to a conversation larger than the classroom.

How we approach interdisciplinary learning

Our three programs are three ways of working that reinforce one another. Academic writing is thinking made visible. Synthetic biology is experimenting with a living system under constraints. Biodesign is creating, with the responsibility that comes from working with life. Students usually enter through one and find themselves borrowing from the others: the iGEM team that writes a better paper, the researcher who prototypes, the designer who learns to cite.

Educational principles

1. 01

   Questions before answers

   Every project starts with a question that could come out either way.
2. 02

   Students do the work, with the pieces ready

   Mentors guide, question and critique. We provide designed modules for the mechanical parts of research, environments, data pipelines, protocols and templates, so building a project is like building with Lego: the bricks are prepared, and what a student makes with them is their own.
3. 03

   Honesty about uncertainty

   We teach students to say what they do not know, in their papers, their models and their proposals.
4. 04

   Real audiences

   Work is made to be read, used or argued with by people outside the program.
5. 05

   No promises we cannot keep

   We do not guarantee publication, prizes, competition results or admissions. We guarantee a rigorous process and candid feedback.

Research ethics and academic integrity

Students in our programs follow the same standards as working researchers: accurate citation, transparent methods, no fabrication or falsification, and clear disclosure of any assistance, including from software tools. Projects involving people follow informed-consent practice appropriate to their scale. Projects involving organisms follow institutional biosafety rules in supervised facilities; CompetiLab does not operate a laboratory. We decline work that cannot be done honestly.

Team and mentors

Our mentors have research backgrounds in molecular biology, modeling and data science, bioinformatics, clinical and public-health research, strategy and design. Among them are scholars who have published at leading machine learning conferences such as ICML and NeurIPS. Whatever a student's question, we are confident of matching them with a mentor who fits it. We publish individual mentor profiles only once their credentials have been verified, and this page will be updated as that happens. In the meantime, we are glad to describe the mentor team in conversation.

Our approach to student development

We would rather a student finish one project well than three badly. We match pace to the student, say honestly when we think waiting a year would serve them better, and measure success by what a student can now do alone that they could not do before: find a question, read a field, design a method, make a thing, and explain it.