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Resume (English only)
Academic Achievements
- Published a paper on understanding CRISPR/Cas9 off-target enzymatic reactions in Nature Computational Science.
- Proposed an automated framework for efficiently designing deep convolutional neural networks in genomics in Nature Machine Intelligence.
- Published a study on deep-learning augmented RNA-seq analysis of transcript splicing in Nature Methods.
Research Experience
Leads the lab at the Division of Artificial Intelligence in Medicine, Cedars-Sinai, focusing on using statistical learning and deep learning to communicate across research areas in computational biology.
Background
Research interests include AutoDL-powered interpretation of genetic variations and post-transcriptional and transcriptional regulatory networks.
Miscellany
Received the 2023 Winnick Award; three papers accepted at NeurIPS23 workshops; EM-GNN paper accepted at Bioinformatics.