Huidong Chen
Machine Learning Enthusiast
About Me
A passionate machine learning enthusiast constantly exploring the cutting-edge advancements in artificial intelligence, deep learning models, and their real-world applications.
Interests
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Generative AI
- Neural Networks
- GNN, LLM, CNN
Education
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PhD in Computer Science, 2012~2018
Tongji University, Shanghai, China
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Visiting PhD student in Computational Biology, 2016~2017
Massachusetts General Hospital & Harvard Medical School, Boston, USA
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Joint-training PhD student in Biostatistics and Computational Biology, 2015~2017
Dana-Farber Cancer Institute & Harvard T.H. Chan School of Public Health, Boston, USA
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BSc in Computer Science, 2008~2012
Tongji University, Shanghai, China
Skills
python
R
Bioinformatics
Machine-Learning
Statistics
Illustrator
Experience
Senior Scientist
Develop or apply new tools, algorithms, and data mining techniques for the integrative analysis of large genomic datasets for use in the development of oral integrin therapies.
Postdoctoral Fellow
- Developed single cell embedding method SIMBA for the co-embeddings of cells and features
- Developed single cell omics trajectory inference tool STREAM.
- Benchmarked the performances of single-cell trajectory inference tools based on topology correctness and pseudotime accuracy
- Developed single cell Virtual Reality tool singlecellVR with Dash by plotly and A-Frame
Postdoctoral Fellow
- Provided the first systematic single cell ATAC-seq computational method benchmarking study.
- Assessed ten scATAC-seq computational pipelines and created a valuable resource for scATAC-seq study with more than 100 well-documented Jupyter notebooks
- Implemented XGBboost to solve regression problem for predicting gene expression level from scATAC-seq analysis
Research Assistant
- Contributed to a scalable unsupervised structure learning method ElPiGraph for approximating complex topologies via principal graph
- Performed and benchmarked various clustering analyses for cell type identification
- Performed and benchmarked various dimensionality reduction methods for single-cell visualization
- Developed statistical hypothesis testing methods for single-cell marker detection
Research Scholar
- Co-developer of a Gini-index-based novel computational method GiniClust to detect rare cells using the density-based clustering method DBSCAN
- Performed single cell RNA-seq trajectory inference analysis to dissect hematopoietic and renal cell heterogeneity in adult zebrafish
- Performed single-cell RNA-seq dataset alignment across experiments for human pluripotent stem cells early differentiation study
Graduate researcher
- Developed a Bayesian-nonparametric-modeling-based novel approach DPNuc for identifying nucleosome positions using the Dirichlet process mixture model
- Applied Markov chain Monte Carlo (MCMC) simulations to estimate the parameters
Teaching Assistant
Led hands-on SQL language sessions and taught students how to access and manipulate databases. Taught weekly sections, held office hours, and assisted with grading homework and exams.
Purchasing Intern
Processed office forms and maintained the database of orders to assist with purchasing tasks.
Software
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Recent Publications
Quickly discover relevant content by filtering publications.
(2021).
Three subtypes of lung cancer fibroblasts define distinct therapeutic paradigms.
Cancer Cell.
(2021).
singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality.
Front. genet.
(2021).
SIMBA: SIngle-cell eMBedding Along with features.
bioRxiv.
(2021).
Current progress and potential opportunities to infer single-cell developmental trajectory and cell fate.
Curr. Opin. Syst. Biol..