Workshop on Data Science and Deep Learning (DSDL2018)

Sponsored by Department of Statistics and Actuarial Science under the Kin Lam Development Fund for Data Analytics


April 7, 2018 (Saturday)

9:30 am - 5:05 pm (Registration 9:00 am - 9:30 am,
Lunch time 12:10 pm - 2:00 pm)

Venue: Theatre P4, Chong Yuet Ming Physics Building, HKU

 

 
About the Workshop

Data science and deep learning become extremely active research areas in statistics and computer science. They bring both big opportunities and unprecedented challenges to traditional research exercises. With the generous support of Professor Kin Lam’s fund, we plan to organize the workshop on data science and deep learning at the University of Hong Kong. The main topics of this workshop include big data analytics, high dimensional statistics, deep neural networks, large-scale optimization and GPU computing, with applications across different science and engineering fields. This workshop serves as an avenue for idea exchanging and networking for collaborations in the big data and deep learning areas, which bridges statistics and computer science to tackle the new challenges.

 

Photo

Please click here for the photo album.

 

Programme

Programme and Abstracts (Updated on April 6, 2018)  

Morning session
9:00 – 9:30 Registration
9:30 – 9:35 Opening Address
9:35 – 10:05 Big Data, a Golden Opportunity for Mathematics

Zhihong Xia
Department of Mathematics, Southern University of Science and Technology, China

10:05 – 10:35 Role of Statistical Metric in Big Industrial Data and Artificial Intelligence

Chunlin Ji
Vice President, Kuang-Chi Institute of Advanced Technology, Shenzhen, China

10:35 – 11:10 Photo Taking and Coffee Break
11:10 – 11:40 Tensor Models for Data Analysis

Michael Ng
Department of Mathematics, Hong Kong Baptist University, Hong Kong

11:40 – 12:10 Deep Learning for Image Recognition

Yizhou Yu
Department of Computer Science, HKU

12:10 – 14:00 Lunch
Afternoon session
14:00 – 14:30 Ensemble Approaches in Machine Learning

Xin Yao
Department of Computer Science, Southern University of Science and Technology, China

14:30 – 15:00 Learning Deep Representation for Image Recognition

Di Lin
Department of Computer Science, Shenzhen University, China

15:00 – 15:30 Forecasting High-Dimensional Covariance Matrices Using Deep Learning

Philip L.H. Yu
Department of Statistics and Actuarial Science, HKU

15:30 – 16:00 Coffee Break
16:00 – 16:30 Profiling Users from Online Social Behaviors, with Applications in Tencent Social Ads

Rick Jin
Director of Ads Quality R&D Center, Social & Performance Ads Department, Tencent, Shenzhen, China

16:30 – 17:00 AI-powered Medical Imaging Analytics via Deep Learning

Aijun Zhang
Department of Statistics and Actuarial Science, HKU

17:00 – 17:05 Closing Remarks
18:00 Workshop dinner

 

Registration

Registration fee is free of charge. Please register here.

 

Invited Speakers (in alphabetical order):

Chunlin JiKuang-Chi Institute of Advanced Technology, Shenzhen, China
Rick JinSocial & Performance Ads Department, Tencent, Shenzhen, China
Di LinDepartment of Computer Science, Shenzhen University, China
Michael NgDepartment of Mathematics, Hong Kong Baptist University, Hong Kong
Zhihong XiaDepartment of Mathematics, Southern University of Science and Technology, Shenzhen, China
Xin YaoDepartment of Computer Science, Southern University of Science and Technology, Shenzhen, China
Philip L.H. YuDepartment of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong
Yizhou YuDepartment of Computer Science, The University of Hong Kong, Hong Kong
Aijun ZhangDepartment of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong

 

Map & Transportation

 

Organizing Committee

Fei JiangThe University of Hong Kong, Hong Kong
Guosheng YinThe University of Hong Kong, Hong Kong
Philip L.H. YuThe University of Hong Kong, Hong Kong
Aijun ZhangThe University of Hong Kong, Hong Kong

 

Acknowledgement

The Organising Committee would like to extend deep gratitude to Professor Kin Lam for pledging to establish the Kin Lam Development Fund for Data Analytics. The Fund is to support staff development, simulate research and collaborative initiatives in the area of data analysis. Professor Lam is currently an Honorary Professor and also a long-time patron of the Department of Statistics and Actuarial Science, The University of Hong Kong.

 

For Enquiry

Please feel free to email enquiries to saas@hku.hk.