Name: Dr. Bo Yu
Affiliation: Hunan University of Technology, China
Research interests: scientific engineering computation

The following is an interview with Dr. Bo Yu:

1. Could you provide a brief introduction of yourself to our readers? Could you describe your current research direction and share an update on your progress?
Currently, my research is focused on developing efficient numerical algorithms for large-scale scientific computation in engineering, particularly in numerical solutions to matrix equations. For example, my group is working on structured algorithms for large-scale computations with applications in fluid dynamics and materials science. We have made progress in reducing computational costs while maintaining accuracy through novel structured techniques.

2. Can you share your thoughts and feelings regarding this award?
I am deeply honored to receive this award, as it recognizes the collaborative efforts of my students and colleagues. Scientific computing is a team endeavor, and this achievement reflects the collective impact of our work in developing novel numerical methods for solving real-world problems. It also motivates me to continue pushing boundaries in both theoretical foundation and practical implementation.

3. Could you offer some insights into your approach to reviewing manuscripts? How do you strike a balance between thoroughness and efficiency?
Balancing thoroughness and efficiency is critical. My approach mainly involves the following two stages:

• Assessing the paper’s novelty, technical soundness, and clarity. If the work is outside my expertise or lacks rigor, I typically decline the paper early;
• For promising submissions, my group verifies derivations, numerical experiments, and reproducibility. We focus on whether the methodology is well justified, and if the results are significant. 

4. In your opinion, what are some key qualities that make a review outstanding?
I think an outstanding review should be objective. The report should focus on science, not personal preferences. Also, the review should provide context by comparing the work to the state-of-the-art and highlighting broader implications. Moreover, it should be concise—avoiding vague critiques—and use examples or references to support any claims.

5. Based on your experience, which research topics do you think will be of particular interest to the research community in the coming years?
In my perspective, I foresee growing interest in AI-aided scientific computing, particularly in integrating machine learning with traditional numerical methods.

6. What is your opinion on the open access model of publishing?
Open access (OA) is vital for democratizing knowledge, especially in publicly funded research. However, challenges remain, such as the acceleration of dissemination, high article processing charges (APCs), etc. I fully support community-driven OA models (e.g., arXiv, institutional repositories).