Geometry, Statistics, Learning

The primary goal of this deep dive is to build a strong community of academic thought-leaders for Artificial Intelligence in Singapore.

20161111 | ‘Deep Probability Flow,’ Brain Lab, SUTD. |

20161028 | ‘Deeper Learning for Smarter Cities,’ NVIDIA-SUTD Deep Learning Day, SUTD. |

20161027 | ‘From Deep Learning to Minimum Probability Flow,’ ZJU Data Science and Engineering Research Center, Hangzhou. |

20161026 | ‘Smarter Cities through Distributed Artificial Intelligence,’ SUTD-ZJU IDEA Workshop, Hangzhou. |

20160715 | ‘Deep Distributed Intelligence,’ Brain Lab, SUTD. |

20160713 | ‘Distributed Intelligence,’ WNDS Group, SUTD. |

20160713 | NRF Workshop on AI, CREATE, Singapore. |

20160701 | Future of AI, National Library, Singapore. |

20160509 | ‘The Singularity is Near: When Machines Transcend Data,’ Applied Algebra Seminar, Berkeley. |

20160504 | Panellist at ICCCRI 2016, Suntec Convention and Exhibition Centre, Singapore. |

20160316 | ‘Lessons on Statistical Singularities from Deep Learning,’ Yale-NUS Math Seminar. |

20160309 | 6th Singapore Conference on Statistical Sciences, NUS. |

20160304 | ‘Deep Learning,’ NUS Guest Lecture. |

20160226 | ‘Big Data and Data Analytics,’ CSD&M Asia, SUTD. |

20160203 | ‘IoT Analytics,’ SMU Guest Lecture. |

I’m looking for mathematically-minded postdocs and Ph.D. students who are interested in working on distributed machine intelligence and deep reinforcement learning. A strong background in statistical learning and computer science will be preferred. Please read this or email me for more information.