Bio

Hello, my name is Haibin YU, a research fellow at the School of Computing Department , National University of Singapore . It is my great honor to be co-supervised by Prof. Kian Hsiang Low and Prof. Patrick Jaillet . I obtained my bachelor degree in Mechanical Engineering and Automation Department, Beihang University (BUAA). My research interests include Bayesian non-parametric methods: Gaussian Process, Bayesian Optimization, Generative Models and Bayesian Deep Learning. My CV can be found [here]

Education

National University of Singapore, School of Computing

Aug, 2014 --- Feb, 2020

PhD Student

Beihang University, Mechanical Engineering

Sept, 2010 --- Jul, 2014

Bachelor of Engineering

Publications

Stochastic Variational Inference for Bayesian Sparse Gaussian Process Regression

Haibin Yu, Trong Nghia Hoang, Kian Hsiang Low and Patrick Jaillet
In Proceedings of the Internatioanl Joint Conference of Neural Networks (IJCNN-19)
[Paper] [CODE]

Bayesian Optimization Meets Bayesian Optimal Stopping

Zhongxiang Dai, Haibin Yu, Kian Hsiang Low and Patrick Jaillet
In Proceedings of the 36th Internatioanl Conference of Machine Learning (ICML-19)
[Paper] [Supp] [CODE]

Implicit Posterior Variational Inference for Deep Gaussian Process

Haibin Yu*, Yizhou Chen*, Kian Hsiang Low and Patrick Jaillet
In Proceedings of the 33rd Conference on Neural Information Processing Systems (NeurIPS-19),
[PDF] [CODE]
Spotlight presentation, top 3%

Selected Competitions

JDD Global Digitalization Chanllege

Global Champion, 500000 RMB (80000 USD) prize

The task is to use the history changes of mobile device users in several cities and districts transfer between users, rate of mobile equipment users and others analog data in different districts and cities, set up reasonable forecast model, make dynamic population change forecast in various districts and counties of the city in the subsequent 15 days.
[News (in Chinese)] [News (in English)]

Thesis

Finally, I submit my thesis. Hope all the best to the defence!

New Advances in Bayesian Inference for Gaussian Process and Deep Gaussian Process models
[thesis] (to be updated)

Selected Honors and Awards

Outstanding Graduate of Beihang University,    2014   
- Beihang University, China

Scholarship of Singapore and MIT Alliance Research Technology,    2014-2018   
- Ministry of Education, Singapore

Research Achievement Award,    2019   
- National University of Singapore, Singapore

Academic Talks

Why Probabilistic Machine Learning Comes to Rescue,    2019.10   
- Wilmar@NUS Lab, Singapore

Implicit Posterior Variational Inference for Deep Gaussian Processes,    2019.11   
- AI Seminar, Singapore

Professional Activities

Invited reviewer for IEEE Transactions on Cybernatics.

Invited reviewer for Annual Conference on Neural Information Processing Systems (NeurIPS 2020).

External reviewer for International Joint Conference on Artificial Intelligence (IJCAI 2020).

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