Liming Zhang: AI + Big Data

• 🔭 I’m currently Ph.D. Candidate working on Bayesian Deep Learning and AI for human behavior prediction.
• 🌱 I’m 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
• ⚡ Fun fact: I have two dogs and I really ❤️ my 🐶s

My Stack

🍇 Languages: Python, Java, C++, JavaScript
🍎 AI (expert): Pytorch, Tensorflow, and other scientific computing libraries
🍐 High Performance Computing (knowledgable): MapReduce, Spark, Hadoop
🍐 Full-stack (for side projects): Node.js, Flask, Spring, Kubernates, Jenkins, MySQL, PostgreSQL, SQLAlchemy, and others
🍑 Data Viz: D3.js, Leaflet.js

AI Papers and Codes:

Google scholar link

• 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

Demos

• 2018: SolarMart (entrepreneurship team), find solar benefit of your hourse with real products. Link / Youtube
• 2017: Coffee Gravity (solo work), an interactive data viz app. Link
• 2017: 1st prize in Transportation Hackathon. Youtube