Jun Xia
Assistant Professor
Data Science and Analytics Thrust (DSA Thrust)
Information Hub
HKUST(GZ) & HKUST
Email: junxia@hkust-gz.edu.cn
Tel: (020) 88333858
Office: W4-535, HKUST(GZ)
Profile
Jun Xia is an Assistant Professor at the Hong Kong University of Science and Technology (Guangzhou), leading the AI for Multimodality and Science Lab (AIMS Lab) with research focused on Multimodal Large Models and AI for Sciences. He also holds an affiliated appointment at The Hong Kong University of Science and Technology (Clear Water Bay, Hong Kong). He received his Ph.D. from a joint program between Westlake University and Zhejiang University, advised by Chair Prof. Stan Z. Li.
🌟 Hiring: We are actively seeking visiting students, research assistant and self-motivated Ph.D. and M.Phil students. Since July 2022, almost every visiting student who worked with me has published papers at top conferences such as ICML, NeurIPS, and ICLR during their visit. If you are interested, please don't hesitate to contact me via Email.
News 
- (2025.08) Invited to serve as Area Chairs for ICLR 2026 and AI4Science Workshop at NeurIPS 2025.
- (2025.05) Four papers are accepted by IJCAI 2025.
- (2025.04) Invited to serve as an Area Chair for NeurIPS 2025.
- (2025.01) Four papers on AI for Life Science are accepted in ICLR 2025.
- (2024.12) A paper on AIDD is accepted in Bioinformatics.
Selected Awards & Honors
2024: CIE-Tencent Doctoral Research Incentive Project ((首届)中国电子学会—腾讯博士生科研激励计划).
2024: Fundamental Research Project for Young Ph.D. students from NSFC (首批国家自然科学基金青年学生基础研究项目(博士生)).
2024: DAAD AINet Fellowship.
2023: Rising Star in AI (awarded by KAUST AI Initiative headed by Prof. Jürgen Schmidhuber)
2023: Apple AI/ML Scholar Finalist
2023: NeurIPS Scholar Award.
2023: Suwu Scholarship.
2023: Westlake Presidential Awards (The highest honor at Westlake Univ.).
2022: National Scholarship. 2017: National Scholarship.
Professional Service
- Area Chair:
- ICLR 2026
- NeurIPS 2025
- AI4Science@NeurIPS 2025
- Program Committee Member or Reviewer:
- Conferences: ICLR, ICML, NeurIPS, CVPR, KDD, ACL, SDM, ECML, ICASSP, etc.
- Journal Reviewer: Nature Communications, IEEE TPAMI, IEEE TIP, ACM TKDD, IEEE TNNLS, Neural Networks, etc.
AIMS Lab
The AI for Multimodality and Science (AIMS) Lab focuses on cutting-edge research in multimodal AI and its applications in scientific discovery (AI for Science).
Ph.D. Students
M.Phil. Students
Visiting Students and RA
PhD:
- Yunhua Zhong (Ph.D. Student from HKU)
- Taoyong Cui (Ph.D. Student from CUHK)
- Dongxin Lv (Ph.D. Student from Westlake)
- Jie Yang (Ph.D. Student from FDU)
MD:
- Zhijin Dong (MS Student from PKU)
- Yuniang Jiang (MS Student from THU)
- ChuangXin Zhao (MS Student from CAS)
- Pan Liu (MS Student from CSU)
BD:
- Chenming Xu (BE Student from NJU)
- Bo Liu (BE Student from JLU)
- Zhuoli Ouyang (BE Student from SUSTech)
- Ziyi Liu (BE Student from BUPT)
- Yiran Zhu (BE Student from NCEPU)
Alumni
- Yue Liu (MS Student from NUDT → NUS)
- Lecheng Zhang (Undergraduate Student from Westlake → UC Berkery)
- Sizhe Liu (Undergraduate Student from USC)
- Yunhua Zhong (Undergraduate Student from NJU)
- Jiabei Cheng (Ph.D. Student from SJTU)
- Xiaojun Shan (Undergraduate Student from UESTC → UCSD)
- Xiao Zhu (Undergraduate Student from BUPT → HKUST(GZ))
- Chengshuai Zhao (Undergraduate Student from UC Irvine → ASU)
Research Focus
The AIMS Lab focuses on advancing research in Multimodal AI and SpectraAI (AI for Spectral Data Analysis).
Multimodal AI
Core Focus: Pre-training and Post-training techniques for multimodal large models, such as preference optimization and reasoning ablities improvements. Multimodal AI research serve as a foundational support for the advancement of SpectraAI.
SpectraAI (AI for Spectral Data Analysis)
Core Focus: Developing advanced AI models for analyzing spectral data (e.g., Mass Spectrometry, Infrared Spectroscopy, Nuclear Magnetic Resonance). As an application and extension of Multimodal AI in the field of spectral data, SpectraAI places strong emphasis on translating algorithms and models into practical use cases. The ultimate goal is to drive real-world impacts through the deployment of these technical solutions.
Below are our team's Publications
Publications
Listed by categories in reversed chronological order, where ∗ indicates equal contribution and † denotes the corresponding author.
Photos
Openings
We are offering multiple research positions in Multimodal AI and its applications in scientific domains. Positions include PhD, Mphil, Postdoc, RA, and Visiting Scholars.
All admitted postgraduate students receive full scholarships (¥15K/month for PhD, ¥10K/month for MPhil). RAs receive competitive salaries and project bonuses. Students applying for Spring/Fall 2026 can contact us or apply for an RA position first.
中文版
我们提供多个多模态学习及其在科学发现领域应用方向的研究职位，包括博士、硕士、博士后、研究助理和访问学者。
所有录取的研究生均享受全额奖学金（博士每月1.5万元，硕士每月1万元）。研究助理享受有竞争力的薪资和项目奖金。申请2026年春季或秋季入学的学生可以联系我们，或先申请研究助理职位。中文详细信息参见AIMS Lab微信公众号。
Contact Info
To apply, email your CV (education, publications, internships, etc.) and representative papers/projects to junxia@hkust-gz.edu.cn. Use the subject format “Year-Position-Your Name-Your Affiliation” (e.g., “23Fall-PhD-Jay Chou-THU”).
We will evaluate all applications promptly. Due to high email volume, we may not respond to every inquiry. If you pass the resume screening, you will receive an email for an interview. If you do not receive any reply within one month, you will not enter the next round. If you remain strongly interested, you may email us again after one month. Thank you for your patience.
PhD & MPhil Applications
PhD student requirements are listed below. For MPhil students, please contact me and sign up for the Redbird Mphil Class, choosing a academic supervisor after 6 months. For Postdoc/RA/Intern applications, we will schedule online meetings individually.
We prioritize individuals with AI and ML backgrounds but also welcome excellent students in biology and chemistry.
General Requirements:
- Applicants should have a strong interest in AI and ML research, independent thinking, and a desire to produce influential results.
- Strong math and programming skills, Linux experience, and a willingness to learn are essential.
- A spirit of scientific research, openness, and collaboration is crucial.
- Good English writing skills are required, meeting the English admissions requirements of HKUST.
Preferred Qualifications:
Applicants must meet at least one of the following requirements. Priority will be given to those who meet multiple requirements:
- Have relevant research or project experience in AI and ML, with publications in top conferences or journals as the primary author.
- Have internship experience in industry or a research institution, with a deep and systematic understanding of AI/ML applications and outstanding achievements during the internship.
- Have achieved top levels in competitions such as ACM ICPC, MCM/ICM, KDD Cup, or Kaggle.
- Have extensive experience as a full-stack engineer.
News Archive
Complete history of news and announcements.