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iohmm's Introduction

Liming Zhang: AI + Big Data

  • ๐Ÿ”ญ Iโ€™m currently Ph.D. Candidate working on Bayesian Deep Learning and AI for human behavior prediction.
  • ๐ŸŒฑ Iโ€™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
  • โšก Fun fact: I have two dogs and I really โค๏ธ my ๐Ÿถs

My Stack

๐Ÿ‡ Languages: Python, Java, C++, JavaScript
๐ŸŽ AI (expert): Pytorch, Tensorflow, and other scientific computing libraries
๐Ÿ High Performance Computing (knowledgable): MapReduce, Spark, Hadoop
๐Ÿ Full-stack (for side projects): Node.js, Flask, Spring, Kubernates, Jenkins, MySQL, PostgreSQL, SQLAlchemy, and others
๐Ÿ‘ 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

iohmm's People

Contributors

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