[Introduction]
Lantian Yao received his Ph.D. in Computer Science from The Chinese University of Hong Kong in 2025. He is currently an Assistant Professor and Master’s Supervisor at the School of Informatics, Xiamen University. His research lies at the intersection of artificial intelligence, life sciences, and medicine, focusing on developing advanced machine learning algorithms to address critical biomedical challenges.
Over the past three years, he has published more than 30 high-quality SCI papers in leading journals of the field, including 6 papers in Nucleic Acids Research (Impact Factor: 16.7) and 5 papers in Briefings in Bioinformatics, with a total citation count exceeding 1,500. His main research directions include:
>AI-driven intelligent drug design
>Multi-omics data analysis of large-scale biological sequences
>Functional prediction and mechanistic study of natural antimicrobial peptides
His long-term goal is to integrate information technology (IT) and biotechnology (BT) into innovative drug discovery frameworks, thereby strengthening healthcare systems and improving human health.
[Personal Website] [Google Scholar] [ORCID: 0000-0003-4554-6827]
A complete publication list can be found on my Google Scholar：https://scholar.google.com/citations?user=LQhebNAAAAAJ or my website：https://lantianyao.github.io/
[Research Interests]
>Artificial Intelligence
>Bioinformatics and Computational Biology
>Medical Big Data Analytics
>Data Mining
>Precision Medicine
[Recruitment]
I am actively recruiting undergraduate interns, master’s students, and visiting students (both from within and outside Xiamen University, remote collaboration is possible) who are interested in Artificial Intelligence or AI for Science. A biomedical background is not required.
If interested, please send your CV to lantianyao@xmu.edu.cn (emails with a proper subject line will always receive a reply).
I provide:
>High-quality one-on-one research supervision
>Computing resources for research projects
>Opportunities to participate in international/domestic conferences and publish academic papers
>Financial support (stipends)
>Guidance for future career development and graduate school applications
I maintain strong collaborations with world-leading universities (including CUHK). Most of the students I have supervised have published academic papers and proceeded to pursue advanced studies at top institutions such as Harvard University, The University of Hong Kong, CUHK, and Westlake University.
[Recruitment Notes]
1. Our group primarily focuses on algorithm design and development, so students are not required to have a biomedical background. Solid programming skills and strong mathematical foundations are sufficient to engage in our research.
2. We also welcome students from non-computer science backgrounds to join us as undergraduate interns or research visitors (on-site or remote). I have successfully supervised several non-CS students in the past, and with diligence, they were able to achieve solid research outcomes in a relatively short time.
3. I encourage my master’s students to set ambitious goals, such as publishing high-quality academic papers and pursuing doctoral studies at top institutions worldwide. More importantly, I hope they will grow into independent researchers and future academic leaders in their respective fields. To support this, I will make full use of my resources to provide comprehensive guidance and foster rapid growth.
4. The master’s period is extremely valuable. I expect students to begin research training as soon as possible after completing the mutual selection process.
>For students with guaranteed graduate admission (保研), research projects should ideally start after admission is finalized (around October).
>For students admitted through entrance exams (考研), research should commence promptly after the re-exam (around March).
This includes attending group meetings, giving literature presentations, and starting research projects. The earlier you adapt to research life, the smoother the graduate journey will be. Research interns and visiting students may start at any time.
5. I view the mentor-student relationship as an equal partnership. I hope my students will not only be my academic collaborators but also trustworthy friends. Therefore, I welcome open communication-whether about research, career plans, or personal concerns-and will do my best to provide support.
6. As our group admits a very limited number of students each year, I kindly ask that once you complete the mutual selection process with me, you refrain from contacting other supervisors. Integrity is the foundation of both research and personal conduct, and I hope our collaboration will be built on mutual trust and respect.