Frank Xiaoguang Fang
Scientist Data Analyst Life Sciences @Trailhead Biosystems
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WORK HISTORY
Scientist Data Analyst Life Sciences @Trailhead Biosystems
Beachwood, OH, US
Developed iPSC differentiated products.• Led high-dimensional experimental design and data analysis to optimize iPSC differentiation workflows.• Developed statistical and machine learning models (regression, neural networks) to predict differentiation outcomes and guide process optimization.• Generated data visualizations (heatmaps, volcano plots, dashboards) to support R&D and decision-making.• Developed and refined SOPs and experimental protocols for scalable cell production.• Supported preclinical relevant studies.• Trained QC and technical staff; collaborated with cross-functional teams.
EDUCATION
Xiamen University
Doctor of Philosophy (PhD), Biology; Data Analysis
Georgia Institute of Technology
Master's degree, Master of Science in Analytics, Computational Data Analytics Track
ABOUT FRANK XIAOGUANG FANG
I am a life sciences professional and data analyst with over 10 years of experience spanning biotechnology, translational research, and advanced data analytics. My work sits at the intersection of experimental biology and data-driven decision making, with a focus on stem cells, gene therapy, in vivo models, and high-dimensional biological data.I have extensive hands-on experience in iPSC culture and differentiation, viral vectors (AAV and lentivirus), molecular cloning, flow cytometry, and animal models, combined with strong skills in statistical analysis, machine learning, and data visualization using Python, R, SQL, and BI tools.In industry and academic settings, I have supported preclinical development, process optimization, toxicology-related analysis, and translational research, while also building predictive models, dashboards, and analytical pipelines to extract insights from complex biological datasets.I enjoy working in collaborative, cross-functional environments and am particularly interested in roles that combine biology, data science, and real-world impact—including biotech, CROs, gene and cell therapy, biomanufacturing analytics, and healthcare data science.Core interests:• Translational & preclinical research• Cell & gene therapy• Data science in life sciences• In vivo studies, PK/PD & toxicology analytics• Machine learning & high-dimensional biological data
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