Pseudotime analysis and integration for time-series single-cell sequencing and imaging data
Gang presented at UW 4D-Genome Meeting.
Contributed Talks/Posters
Integration of imaging and sequencing data in the context of visual cell sorting
Gang presented at 2023 UW CMB Annual Meeting.
Integration of imaging and sequencing data in the context of visual cell sorting
Gang was invited to give a talk at the 8th Young Statistician Forum at Shanghai University of Finance and Economics.
Integration of imaging and sequencing data in the context of visual cell sorting
Gang presented at 2022 4DN annual meeting.
Integration of imaging and sequencing data in the context of visual cell sorting
Gang presented at 2022 WA GS retreat.
Integration of imaging and sequencing data in the context of visual cell sorting
Gang was invited to give a talk, “Integration of imaging and sequencing data in the context of visual cell sorting”, at The 5th International Conference on Econometrics and Statistics(EcoStat 2022).
Integration of imaging and sequencing data in the context of visual cell sorting
Gang was invited to give a talk, “Integration of imaging and sequencing data in the context of visual cell sorting”, at 2022 HSPH Program in Quantitative Genomics Seminar.
Integration of imaging and sequencing data in the context of visual cell sorting
Gang presented at 2022 UW GS postdoctoral seminar.
Integration of imaging and sequencing data in the context of visual cell sorting
Gang presented at 2021 4DN Annual Meeting .
Integration of imaging and sequencing data in the context of visual cell sorting
Gang presented at UW 4D-Genome Meeting.
Coupling Machine Learning with Fiducial Inference and Genetics
Gang successfully passed the public oral defense.
DeepGWAS to Enhance GWAS Signals for Neuropsychiatric Disorders via Deep Neural Network
Presented at 2020 American Society of Human Genetics Annual Meeting. Our abstract has been selected as reviewer’s choice (~10%). This is a joint work with Prof. Yun Li et. al.
SMNN: Batch Effect Correction for Single-Cell RNA-seq Data via Supervised Mutual Nearest Neighbor Detection
Presented at 2020 JSM. This is a joint work with Prof. Yun Li et. al.
SMNN: Batch Effect Correction for Single-Cell RNA-seq Data via Supervised Mutual Nearest Neighbor Detection
Presented at 2020 Eastern North American Region Spring Meeting. This is a joint work with Prof. Yun Li et. al.
Ensemble Imputation for DNA Methylation Levels Across Platforms
2020 Conference on Statistical Practice. This is a joint work with Prof. Yun Li et. al.
Ensemble Imputation for DNA Methylation Levels Across Platforms
Contributed Poster, George R. Brown Convention Center, Houston, TX
Presented at 2019 American Society of Human Genetics Annual Meeting. This is a joint work with Prof. Yun Li et. al.
(Invited Talk) Ensemble Imputation for DNA Methylation Levels Across Platforms
Invited Talk, Nankai Univerisity, Tianjin, China
Presented at The 2019 ICSA China Conference. This is a joint work with Prof. Yun Li et. al.
Deep Fiducial Inference and Approximate Fiducial Computation
Contributed E-Poster, Hyatt Regency Bellevue, 900 Bellevue Way, Bellevue, WA
Received Student and Early-Career Travel Award!
(Contributed Talk) Deep Fiducial Inference and Approximate Fiducial Computation
Contributed Talk, Sitterson Hall, Room 014, University of North Carolina, Chapel Hill, NC
Presented at 2019 MUMS Transition Workshop and SPUQ. See my slides on SAMSI website. This is a joint work with Prof. Jan Hannig.
Deep Fiducial Inference and Approximate Fiducial Computation
Contributed Poster, Penn Pavilion, Duke University, Durham, NC
Presented at Sixth Bayesian, Fiducial, and Frequentist (BFF6) Conference on Model Uncertainty. This is a joint work with Prof. Jan Hannig.
Across-Platforms Imputation for DNA Methylation Levels
Contributed Poster, San Diego Convention Center, 111 West Harbor Drive, San Diego, CA
Presented at 2018 American Society of Human Genetics Annual Meeting. See more info here. This is a joint work with Prof. Yun Li et. al.