BDE 2020


2020 2nd International Conference on Big Data Engineering (BDE 2020) was sucessfully held during May 29-31, 2020 Online.

1. Conference Proceedings

BDE 2020 conference proceedings (ISBN: 978-1-4503-7722-5) is archived in the ACM Digital Library.

The BDE 2020 papers have been indexed by Ei Compendex, Scopus!

2. Photos of BDE2020

Group Photo

Keynote Speakers

Title: Cloud, AIoT and Edge Computing in 5G Mobile Core Environment

Prof. Kai Hwang, Chinese University of Hong Kong, China

Title: Multiresolution Learning: A 20-Year Perspective

Prof. Yao Liang, Purdue University School of Science & Indiana University Purdue University, USA

Title: Big Data and Human-AI System Interaction

Prof. Changxu Wu, University of Arizona, USA

Invited Speakers

Title: Disruptive AI Technologies for Molecular Biology and Medicine: DNA Motifs, CRISPR-Cas9 Off-Targets,

and Cancer Screening from Blood

Dr Ka-Chun Wong, City University of Hong Kong, Hong Kong

Title: Big Data: Algorithms and Ecosystems

Dr Wei Li, Central Queensland University (CQU), Australia

Title: Dynamic Incremental Semi-Supervised Fuzzy Clustering for Data Stream Classification

Dr Gabriella Casalino, University of Bari Aldo Moro, Italy

 

3. Best Presentations

Session 1 –Rubbing Image Retrieval Using Deep Convolutional Neural Network (BE0030) presented by Ziyang Wang from East China Normal University, China

Session 2 –A Framework for Arabic Tweets Multi-label Classification Using Word Embedding and Neural Networks Algorithms (BE0025) presented by Abdullah M. Bdeir from Abu Dhabi University, UAE

Session 3 –Predicting Chinese Bond Market Turbulences: Attention-BiLSTM Based Early Warning System (BE0020) presented by Peiwan Wang from Xi’an Jiaotong-Liverpool University, China

 

Submission Method


Electronic Submission System (PDF format)

Format:

1. Full paper (Click)
2. Abstract (Click)

Contact Method


Ms. Daisy Zheng

BDE 2024 conference secretary

E-mail: bde.conference@gmail.com

Tel: +86-021-59561560

 

Co-Sponsored by



 


Technically Supported By