AI at the frontier of biology and medicine.
We track the areas where AI is already changing biological and medical research. Below are the broad themes; individual projects and papers are being ported here gradually — for now, the full portfolio lives on our creator's research page.
Medical Diagnosis
Imaging, pathology, ECG, EEG, risk prediction, triage, and clinical decision support systems accountable to physicians and patients.
Drug Design
Protein structure, molecular generation, target discovery, virtual screening, and toxicity prediction — from computational promise to validated therapy.
Genomics & Genetics
Variant interpretation, gene regulation, single-cell analysis, and models that connect sequence, expression, phenotype, and disease.
Personalized Medicine
Patient-specific treatment response, multi-omics profiles, digital biomarkers, and AI systems that adapt care to individual biology.
Neuroscience
Epilepsy, dementia, neural decoding, connectomics, psychiatric disease, and the search for mechanistic understanding.
Infectious Disease
Viral and bacterial evolution, outbreak forecasting, antimicrobial resistance, and vaccine design.
Notable projects
Medical imaging models
Deep learning approaches for diagnostic imaging and clinical decision support.
Optimization for biological modeling
Provably fast solvers applied to large-scale biological and genomic data.
AI for scientific discovery
Methods connecting machine learning with hypothesis generation in the life sciences.
For full papers, projects, and publications
The complete research portfolio — publications, ongoing projects, and academic background — is maintained on our creator's personal page, and will be gradually ported into AI Biologist under these broad themes.