Prospective Students
The laboratory is driven by curiosity. Nothing less is sufficient for the work we do.
We aspire to dream, build, test, tear apart, rebuild, and test again until we arrive at research outcomes that can make a meaningful contribution to real-world problems. Our relationship with established knowledge is one of healthy skepticism. No idea is considered safe here unless it survives experimental scrutiny.
Academic ambition is welcome; academic opportunism is not. We view the laboratory as a destination for thoughtful inquiry into the nature of the world and the principles that govern it. We value careful thinking, intellectual honesty, and genuine curiosity above numerical indicators of success.
Modern academia is evolving rapidly. Increasingly, qualities that are difficult to quantify are reduced to numerical indicators. The widespread use of language models has accelerated this trend. Researchers are encouraged to secure more funding, publish more papers, accumulate more citations, improve their h-index, and generate more patents.
Perhaps this is inevitable. Perhaps it is even necessary. Yet one cannot help but notice that something important is being lost in the process.
All master’s and PhD students meet with the Principal Investigator on a weekly basis. These meetings serve as a forum for discussing research progress, technical challenges, new ideas, and future directions. As students become more experienced and independent, interactions often become more frequent and informal, with research discussions occurring naturally as part of daily laboratory life.
The ultimate goal of graduate education, particularly at the PhD level, is not merely to absorb existing knowledge but to create new knowledge. A successful PhD student should eventually become a leading expert in their specific research area. Neither the advisor nor the literature alone can provide everything required for this journey. At some point, a PhD student should know more about their particular topic than the advisor does. This is not an exception; it is the intended outcome of doctoral training.
The level of guidance naturally depends on the student’s stage of development. Students who are beginning their research journey often require substantial support. Discussions may include detailed mathematical derivations, literature reviews, experimental design, or even implementation-level guidance. As students mature academically, expectations gradually shift from learning existing methods to questioning, extending, and ultimately surpassing them.
Effort and intellectual initiative are valued far more than immediate success. It is perfectly acceptable for an experiment to fail, for a derivation to contain mistakes, or for a proposed method not to produce the desired outcome. Research is inherently uncertain. What is not appreciated is the absence of effort or curiosity.
The laboratory values proactive research behavior. Statements such as “I do not understand this topic” are less helpful than “I investigated several approaches, but I could not resolve this specific issue.” Similarly, simply reporting that an advisor’s suggestion did not work is rarely sufficient. A more productive discussion is one in which the student presents the results, analyzes why the approach failed, and proposes alternative directions worth exploring.
The most enjoyable and intellectually rewarding discussions occur when students bring their own ideas to the table: challenging assumptions, proposing new approaches, questioning existing methods, and contributing perspectives that the advisor had not previously considered. Independence, intellectual honesty, and persistent curiosity are therefore among the most important qualities we seek to cultivate in our students.
Qualifications
Students with undergraduate degrees in Mechatronics Engineering, Computer Science, Mechanical Engineering, or Electrical and Electronics Engineering are welcome to apply.
We do not place excessive emphasis on GPA. However, applicants should be aware that university-level admission procedures may impose minimum academic requirements. Strong foundations in mathematics—including calculus, linear algebra, and probability—as well as proficiency in C++ programming are highly advantageous.
Prospective students are encouraged to familiarize themselves with the laboratory’s research activities and submit a research proposal that reflects their own interests and ideas. Originality and intellectual honesty are valued far more than polished presentation.
The use of language models for language refinement is acceptable. However, applicants should be aware that proposals generated primarily by AI tools are often easy to identify during follow-up discussions and interviews. While such tools can produce technically correct language and fashionable terminology, they cannot substitute for genuine understanding, curiosity, or personal insight. A modest but authentic proposal is far more valuable than an impressive-looking document that does not genuinely reflect the applicant’s own thinking.
At present, we do not have any open positions. Prospective students may submit a general application through the Center for Physical AI and Robotics (PAIR).
