Our Research Areas

We focuses on the following research areas:

1. Clinical structured data analysis
   • Utilizing deep learning algorithms to build clinical decision support models for common clinical prediction tasks based on multimodal clinical structured data
   • Addressing complex clinical application scenarios, including limited data, data missingness, and pattern incompleteness
   • Investigating algorithm implementation-related issues such as uncertainty estimation, interpretability, and reliability
   • Published multiple papers on this topic in international conferences or journals such as KDD, ICDM, SDM, and Big Data Journal
2. Digital pathology image analysis
   • Designing and developing computer vision algorithms and computer-aided diagnosis techniques for integrating digital pathology slides into the pathology workflow
   • Expanding pathologists’ perspectives beyond microscopic slides
   • Utilizing and integrating existing human medical knowledge to discover pathological phenotypes and human genotypes
   • Uncovering medical and life information that transcends human cognition
3. Pathology semantic standardization
   • Constructing large-scale knowledge graphs as the core task
   • Researching information extraction, coreference resolution, sentiment analysis, and intelligent question answering etc.
   • Actively exploring effective methods for acquiring and applying valuable human knowledge
   • Providing strong support for downstream tasks such as information retrieval, question answering, and recommendation systems
4. Deep learning methods on clinical data
   • Image processing methods alone are insufficient for comprehensive pathology analysis and diagnosis
   • Expanding beyond pixel-level analysis to incorporate pathological knowledge and inference-drawing capabilities
   • Building a pathological semantic system for a unified representation of pathological knowledge
   • Enabling computers to perceive and analyze the underlying knowledge behind pathology data
   • Uncovering hidden, immutable laws through computational analysis

We are doing

1. Development of natural language processing and bioinformatics-based text mining AI algorithms
2. Construction of structured biomedical knowledge graphs from unstructured biomedical and clinical data
3. Research in the field of healthcare big data, utilizing large-scale data mining and machine learning algorithms for in-depth analysis
4. Application of artificial intelligence techniques to assist doctors in diagnosis and treatment processes

Our Academic Achievements

Our team has published numerous papers in top conferences and journals, including but not limited to:

                                                                               

Conference					Journal
ACL	AAAI	SIGKDD	NeuralPS	ACM CIKM	IEEE TMI	JMIR	Bioinformatics	MediA	JBHI
MICCAI	IEEE ICDM	SDM	ISBI	IEEE BIBM

Our papers have been cited thousands of times on Google Scholar.

Competition Achievements

When	Competition Name	Prize
2016	SeeDev task of the BioNLP data mining competition	First position
2022	世界人工智能大会	Sail Award(Top award)
2023.7.14	第六届智慧医疗创新大赛陕西赛区	First Prize
2023.7.25	中国发明协会创业奖创新奖	Second Prize
2023.9.22	第六届智慧医疗创新大赛全国总决赛	National Third Prize

Research Projects

• We has undertaken several national and provincial-level research projects and achieved significant research outcomes.
• We have applied for over 50 invention patents and software copyrights.
• The outcomes of our projects have been utilized in major initiatives such as the National Health Commission and the nationwide healthcare informationization survey, as well as in the daily diagnosis and scientific research of multiple healthcare institutions.
• BioModels for biological pathway knowledge graphs and systems have been recognized as the most important resources in the field of systems biology. They have been included as a successful case in the European Infrastructure for Systems Biology (ISBE) initiative by the European Union.

Recruitment

We are dedicated to cultivating talent based on the principle of “people-oriented” development. Our group emphasizes both collective honor and individual creativity, seamlessly combining personal aspirations with team goals.

We cordially invite talented individuals to join our group for academic exchanges and encourage outstanding students to pursue their studies with us.

Research Opportunities:

Graduate Students: We offer exciting research opportunities for graduate students who are passionate about biomedical research. By joining our group, you will have the chance to work on cutting-edge projects and contribute to the advancement of knowledge in the field.

PhD Candidates: As a PhD candidate in our group, you will have the opportunity to engage in interdisciplinary research and collaborate with experts in the field. We provide a supportive and stimulating environment to foster your growth as a researcher.

Postdoctoral Fellows: We welcome postdoctoral fellows who are eager to take their research to the next level. Join our group to conduct innovative research, publish high-impact papers, and develop your independent research profile.

Research Scientists: We are seeking talented and motivated research scientists to join our team. As a research scientist, you will have the opportunity to lead and contribute to research projects, mentor junior researchers, and make significant contributions to the field of biomedical research.

Location: Room 4-6030, Western Science and Technology Innovation Harbor

• Contact Person: Prof. Chen Li; Email: cli@xjtu.edu.cn
• Contact Person: Prof. Tieliang Gong; Email: gongtl@xjtu.edu.cn

Please feel free to reach out to us for any inquiries or further information. We look forward to welcoming exceptional individuals to our research group and creating a vibrant and collaborative scientific community.