Computing Science Vision:
  I believe that computing science will become a fundamental field used extensively across various domains. Currently, computing science plays a crucial role in conducting simulations for tasks such as semiconductor chip design, battery material development, and protein analysis for drug development. This trend is expected to accelerate as researchers enhance hardware computing capabilities and develop better algorithms. In particular, there is increasing discussion about the application of artificial intelligence in various industries, and I anticipate a continued trend of applying computing science beyond just artificial intelligence in diverse fields.

Thoughts on the Organic Connection between Education, Research, and industry:
  In the field of computer science, the connection with industry is a crucial criterion in shaping the direction of research and education. This is because the outcomes of education and research usually have real-world impacts when applied in industry. In research, there is often a focus on developing new technologies applicable to industry problems, such as using artificial neural networks for protein structure prediction in drug development. In education, it is essential for students to acquire skills that are beneficial when they enter specific industries after graduation. However, I also believe that education and research should not solely prioritize industry connections. They should play a role in envisioning and planning for the future, especially in more fundamental content areas that may not immediately lead to industry applications.

Current Technological/Philosophical issues in the Computing Field:
  One prominent issue is the practical application and extension of recently developed artificial intelligence technologies. While AI has demonstrated excellent performance in language models and image generation, fully establishing how to connect this capability to real-world applications is still a work in progress. Additionally, integrating AI into other scientific fields is challenging due to the need for knowledge in both science and AI. Another significant issue under discussion is how to regulate AI, especially in critical decision-making scenarios. Determining responsibility in decision-making when AI is involved is unclear, and intentional biases in AI training processes pose challenges. This issue extends beyond AI and involves reaching a consensus on how computing algorithms participate in human-led decision-making processes.

Approach and Strategies for Teaching Fundamental AI Courses:
  The introductory AI course reflects the trend of AI becoming essential in various fields. Instead of focusing on developing AI within computer science, the course aims to provide knowledge that is useful when applying AI in different disciplines. I want to create a course where students can comfortably learn, while those interested can delve into more in-depth content. Initially, preparing a course for first-year students was daunting, especially because most AI courses assume students have a basic understanding of linear algebra, programming, and other fundamental computing concepts. However, our AI foundational course attracts students without these prerequisites. Therefore, my emphasis during teaching is on conveying intuitive insights into AI techniques, allowing students without a background in mathematics or computing science to grasp the concepts.

Challenges for an Experimental AI Basics Courses:
  The AI basics course is designed experimentally and does not have a designated textbook, making it challenging for students to navigate homework, exam preparation, and additional study. To address this, I aim to operate the course as transparently as possible and provide a wealth of resources for students who want to study further. By doing so, I hope to assist students in making informed decisions about their direction and enable those who wish to delve deeper into the subject.

Advice for Students:
  I advise students to prioritize their health, engage in diverse experiences during their academic years, and actively pursue hobbies and dreams they genuinely enjoy. Many undergraduate students tend to invest more time in efforts to achieve good grades rather than considering their future paths. From my own experience, the decisions I made regarding which department to enter, which research lab to join, or which company to work for had significant impacts on my life. To make decisions without regrets, I encourage students to utilize internships and similar programs, engage in conversations with various people, and dedicate time to contemplate their career paths.