Joao Xavier

Joao Xavier, PhD, is a Professor in the Computational & Systems Biology Program at the Gerstner Sloan Kettering Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center (MSKCC). His research integrates computational modeling and experimental biology to investigate cellular interactions in cancer, focusing on microbiome influences on treatment outcomes, metastasis mechanisms, and metabolic regulation of cell behavior.

His academic background includes a PhD from Universidade Nova de Lisboa. Research interests center on systems biology approaches to cancer-microbiome interactions, with emphasis on microbial ecology in oncology, metastatic biomarker discovery, and metabolic flux dynamics. The lab employs machine learning, mathematical modeling, and wet-lab validation to decode complex biological behaviors.

Recent publications (2022-2025) reveal a dominant focus on clinical microbiome analysis in cancer patients, metastasis prediction via metabolic signatures, and computational tools for microbial community visualization. Key trends include gut microbiota depletion effects on immunity, oral bacterial translocation as clinical markers, and evolutionary dynamics of drug resistance.

Scientific recognition includes:

• Director's New Innovator Award, National Institutes of Health (2011)
• Biofilm Young Investigator Award, Center for Biofilm Engineering (2010)

He mentors graduate students including Qixiu Han and Vishwas Mishra, with notable alumni such as Kerry Boyle and Laura de Vargas Roditi. His NIH-funded research leverages collaborations across MSKCC's computational and clinical divisions, targeting microbiome-based interventions for cancer therapy optimization.

The Joao Xavier Lab comprises senior scientists, computational biologists, and technicians working on interdisciplinary projects. Current team members include Lab Manager Sneh Sharma, Senior Research Scientist Ana Djukovic, and Computational Biologist Isaac Stamper, supported by institutional infrastructure from MSKCC's research divisions.