Xinghao Zhang
Developmental & Computational Biology | AI/ML | Complex System
- Role
- Principal Scientist, Systems and Computational Biology at Takeda
- Location
- Cambridge, MA, US
- LinkedIn followers
- 500 followers
About Xinghao Zhang
Innovative and impact-driven Scientist specializing in computational & developmental biology, with years of experience in multi-omics integration, single-cell and spatial transcriptomics, and graph based machine learning. Proven leader in target discovery, disease modeling, and translational research across pharma, biotech, and academic settings. Adept at building scalable AI/ML pipelines, mentoring cross-functional teams, and driving strategic collaborations to accelerate therapeutic innovation. Passionate about bridging experimental biology and computational insights to uncover novel mechanisms in complex diseases.
Experience
Principal Scientist, Systems and Computational Biology
Aug 2023 — Present · Cambridge, MA, US
Directed computational strategy for target discovery and disease understanding in chronic and autoimmune inflammatory/fibrotic disease, driving innovation in therapeutic areas through integration of high-dimension multi-modal data diverse biological systems.• Spearheaded AI/ML-driven target discovery and MoA elucidation initiatives across gastrointestinal and inflammatory diseases, integrating multi-omics data (single-cell/perturb/spatial transcriptomics, epigenetics, proteomics, genetics) to enable patient stratification and translational insights.• Designed and deployed graph neural network methods leveraging gene regulatory networks, protein-protein interactions, and disease pathways to prioritize therapeutic targets and simulate in silico perturbations using contrastive learning and optimal transport.• Developed proprietary knowledge graphs, applied graph learning and foundation models to uncover cross-disease and tissue-specific mechanisms, accelerating biomarker discovery and target expansion.• Led a strategic initiative to evaluate therapeutic targets using large language models (LLM) and hierarchical multi-agent systems, enabling autonomous data analysis across biology, druggability, translation, market, safety, and clinical risk dimensions.
Education
Quantic School of Business and Technology
Master of Business Administration - MBA, Business Administration and Management, General
2023 — 2024
San Diego State University
Master of Science (M.S.), Molecular Biology
2012 — 2014
University of Cincinnati College of Medicine
Doctor of Philosophy (PhD) candidate, Molecular and Developmental Biology
2014 — 2019
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