As synthetic biology becomes increasingly computational and driven by powerful algorithmic tools, ensuring the safety and controllability of our global DNA synthesis ecosystem will require effective governance of algorithms and the sensitive data that inform them.

Haoling Zhang is a Ph.D. candidate at King Abdullah University of Science and Technology, working in the laboratory of Prof. Jesper Tegnér. He holds a bachelor’s degree in software engineering and subsequently spent five years at BGI Research working in bioinformatics while also receiving training in computational intelligence from Prof. Tegnér. He also serves as an early-career-researcher reviewer for Springer Nature. His current work focuses on the modelling of biological sequences, with an emphasis on defining and characterizing functional boundaries. He develops noise-resilient machine learning models tailored to high-noise biological environments to enable robust knowledge inference in complex living systems. Haoling has published in high-impact journals such as Nature Computational Science and Nature Communications.