Ann Huang

Technical lead for analysis of high-throughput perturbation screens for AI-driven drug discovery

Functional genomics in the Illumina Artificial Intelligence Lab

• Profiled glioblastoma invasion by analyzing human histology samples, patient-derived xenograft mouse histology samples, and scRNA-seq data from patient-derived glioblastoma samples (Neuro Oncol, 2022) • Analyzed scRNA-seq data to identify genetic regulators of glioblastoma stem cells, and then used CRISPR/Cas9 to determine their potential for improved glioblastoma therapies (Nat Communs, 2022) • Advisor: Jiangbing Zhou, Department of Neurosurgery

• Constructed a COVID-19 cell atlas using scRNA-seq and snRNA-seq data from COVID-19 autopsies to determine SARS-CoV-2 pathophysiology (eLife, 2023) • Benchmarked multiome (GEX/ATAC) datasets by providing cell type annotations that served as the ground truth labels for matching cells between different modalities (NeurIPS Datasets and Benchmarks Track, 2021)

• Developed a peptide-based multi-ligand protein capture agent to replace antibodies in current malaria rapid diagnostic tests • Demonstrated that this capture agent has five-fold stronger affinity to the target protein compared to existing methods without loss of specificity • Advisor: James R. Heath, Department of Chemistry

Thesis: Development and Delivery of Genome-Editing Therapies for Improved Glioblastoma Treatment