Xin Su | Infectious Diseases | Best Researcher Award

Dr. Xin Su | Infectious Diseases | Best Researcher Award

Attending Physician | Nanjing University | China

Professor Xin Su, M.D., Ph.D., is a distinguished clinical scientist and Chief Physician renowned for his pioneering contributions to respiratory and critical care medicine, with particular expertise in the study and management of severe pulmonary infections. Over a distinguished career spanning nearly three decades, he has demonstrated an exceptional ability to bridge clinical excellence with translational research innovation. His work focuses on the pathogenesis, diagnosis, and treatment of invasive pulmonary aspergillosis (IPA) in non-neutropenic patients, a challenging and underexplored domain of pulmonary medicine. As a leading investigator, Professor Su has spearheaded multicenter studies that have transformed the understanding of pulmonary fungal infections, combining rigorous clinical observation with the use of novel diagnostic technologies, including machine learning and metagenomic sequencing. His publications in high-impact journals such as The Lancet Infectious Diseases, Microbiology Spectrum, Frontiers in Cellular and Infection Microbiology, and Clinical Microbiology and Infection reflect a deep commitment to advancing evidence-based practices and diagnostic accuracy in the field. Through his groundbreaking studies, Professor Su has introduced innovative diagnostic models that integrate big data analytics with clinical biomarkers, offering more precise and timely identification of IPA and related fungal diseases. Beyond diagnostics, his investigations into host immune responses, interferon signaling, and biomarker development have opened new avenues for prognostic assessment and personalized treatment strategies. His leadership roles as a Chief Physician, Professor, and Doctoral Supervisor at Nanjing University-affiliated hospitals underscore his dual impact as both a clinician and academic mentor. Colleagues and collaborators recognize his unique ability to unite global expertise, as evidenced by his participation in international research consortia addressing fungal infections and severe pneumonia outcomes. His scholarly rigor, coupled with his mentorship of young clinicians and researchers, has significantly enriched the field of respiratory and infectious disease research. While Professor Su’s scientific achievements are substantial, he continues to identify strategic growth areas that align with the evolving challenges of respiratory medicine. Expanding the clinical utility of machine learning-based diagnostic platforms, validating novel biomarkers in diverse patient populations, and enhancing global collaborative networks remain key objectives. Moreover, strengthening translational pathways that connect molecular diagnostics to frontline patient care is an ongoing priority, ensuring that innovations in the laboratory translate into improved clinical outcomes. Looking ahead, Professor Su’s future research aims to deepen the mechanistic understanding of host-pathogen interactions in fungal and viral co-infections, refine AI-driven diagnostic algorithms for pulmonary infections, and integrate multi-omics data into clinical decision-making frameworks. His vision is to establish an internationally recognized precision-medicine model for diagnosing and managing severe respiratory infections, ultimately contributing to reduced mortality, optimized therapeutic strategies, and global health resilience in the era of emerging respiratory pathogens. He has 2677 citations from 128 documents with an h-index of 28.

Profiles: Scopus | ORCID

Publications

1. Diagnostic and prognostic roles of interferon-λ1 and interferon-λ3 in bronchoalveolar lavage fluid and plasma in non-neutropenic patients with invasive pulmonary aspergillosis. (2025). Microbiology Spectrum.

2. Rapid and accurate diagnosis of severe pneumonia: Similarities and differences between severe community-acquired pneumonia and hospital-acquired pneumonia/ventilator-associated pneumonia. (2025). Chinese Journal of Tuberculosis and Respiratory Diseases.

3. Development and validation of a machine learning-based diagnostic model for identifying nonneutropenic invasive pulmonary aspergillosis in suspected patients: A multicenter cohort study. (2025). Microbiology Spectrum.

4. Expert consensus on cancer treatment-related lung injury. (2025). Journal of Thoracic Disease.

5. Pentraxin-3 as a novel prognostic biomarker in non-neutropenic invasive pulmonary aspergillosis patients. (2025). Microbiology Spectrum.