- ๐ญ Iโm currently Ph.D. Candidate working on Bayesian Deep Learning and AI for human behavior prediction.
- ๐ฑ Iโm widely interested in bridging the gap between ML and software engineer, so it is easier to implement an AI-enabled system.
- I like to read papers in: Deep Learning, Data Mining, Adversarial Network (GAN), Unsupervised Learning (VAE), Graph Deep Learning, Bayesian graphical models, NLP, Spatial-temporal series
- โก Fun fact: I have two dogs and I really โค๏ธ my ๐ถs
๐ Languages: Python, Java, C++, JavaScript
๐ AI (expert): Pytorch, Tensorflow, and other scientific computing libraries
๐ High Performance Computing (knowledgable): MapReduce, Spark, Hadoop
๐ Full-stack (for side projects): Node.js, Flask, Spring, Kubernates, Jenkins, MySQL, PostgreSQL, SQLAlchemy, and others
๐ Data Viz: D3.js, Leaflet.js
- 2020-2020, Spatially-valid deep trajectory generation: paper, repo
- 2019-2020, Spaital-temporal graph generation (lead): paper, repo
- 2019-2020, Temporal graph generation (lead): paper, repo
- 2019-2019, Conditional-UNet for wearable AI and multi-label image segmentation (lead): paper, repo
- 2017-2018, Station-to-User Transfer Learning (lead): paper, repo
- 2016-2017, Crowdsourcing urban change (lead): paper
- 2015-2015, Distributed spatial indexing for high-performace computing (assistant): paper