Summary
Sixing Huang is a bioinformatician and evangelist with a decade of experience bridging biology, high-performance data pipelines, and modern software practices. Trained in China and Germany (Ph.D. in Bioinformatics, magna cum laude), he spent seven years at the Leibniz Institute DSMZ building scalable diversity-analysis pipelines and has since worked across industry roles applying metagenomics, NLP and knowledge graphs. A triple-certified Neo4j specialist who experiments with GPT and participates in Kaggle and Project Euler, he pairs domain biology knowledge with hands-on skills in C++, Python, Scala, Go, Kubernetes, Terraform and AWS ML. He self-taught cloud and big-data tools despite limited daily reliance on microservices, demonstrating a proactive drive to modernize research software. Based in Tokyo, he teaches, writes, and advocates for reproducible, test-driven development in bioinformatics while exploring graph+LLM solutions to biological problems. His background combines rigorous academic training with practical engineering curiosity and a commitment to using technology for global challenges like pandemics and climate change.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Bioinformatik, magna cum laude, Doctor of Philosophy (Ph.D.), Bioinformatik, magna cum laude at Max Planck Institute for Marine Microbiology
Diplom degree, Biologie, 1, Diplom degree, Biologie, 1 at Universität Bremen / University of Bremen
Chinese, English, German, Japanese