AI & Biological Sciences

Validate beyond the distribution; question the benchmark first.

Our work explores the two-way relationship between AI and the biological sciences, including machine learning applications in genomics, neuroscience, and biomedical data, as well as computational ideas inspired by biological systems. We emphasize scientific questions, appropriate computational methods, and evidence-based evaluation.

AI for Biological Research

Machine learning methods for genomic data modeling, computational analysis, and biological research questions.

Biology-Inspired Artificial Intelligence

Exploring computational ideas inspired by biological neural structures, information processing, and learning mechanisms.

Facts and outputs

Publications

Computational genomics

Westlake UniversityIn progress

People and collaboration

Haowei (Jack) Hua

Co-Founder & Research Lead

Focuses on interdisciplinary research, scientific inquiry, and innovation-driven project development while contributing to technical architecture discussions, system design, and engineering decisions. He works collaboratively to connect scientific ideas with practical development.

Neuroscience, Princeton University

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