个人简历

崇志宏
人工智能和去中心化互联（AI & BlockChain）
Associate Professor
I am now an associate professor in the School of Computer Science & Engineering,Southeast University,Nanjing, China, 211189.

1. B.E. of Computing Technology 30/Jan/1991 Nanjing University of Information Science and Technology

2. M.S. of Economics 30/Jan/2000 Research Institute of Fiscal Science, the Ministry of Finance of China

3. Ph.D.of Computer Science 30/Jan/2006
Fudan University

/*POTENTIAL MASTER STUDENTS WHO ARE INTERESTED IN MY RESEARCH ARE WELCOME TO TALK TO ME!
Selected Research Grant
12. Decentralized Application Developement via Blockchain Platform, supported byHande FinMaker， 1/2017~12/2017. Principal Investigator（负责人）.
11. Unveiling the Mind of Big E-Business Platform's Customers via Deep Learning, supported by Focus Technology Co., Ltd, 5/2016~6/2017. Principal Investigator.
10. Storage of Large Scale Knowledge Graph using Big Data Technology, supported by the 28th Research Institute of China Electronics Technology Group Corporation, 9/2016~9/2017, Principal Investigator.
9. Deep Learning for Image Retrieval on E-Business Platform, supported by Focus Technology Co., Ltd, 1/2016~6/2016. Principal Investigator.
8. Mining regular patterns from trajectory data in the presence of knowledge, supported by Focus Technology Co., Ltd, 9/2015~4/2016. Principal Investigator.
7. Real time visualization of Twitter's Storm system status, supported by University of Illinois Research Center in Singapore, 7/2015~9/2015, Visiting Postdoctoral Researcher.
6. Visualization of Customers' Behaviors in the World Wide Web from the View of Business, Supported by Huawei Technologies Co., Ltd, 1/2015~9/2015. Principle Investigator.
5. Big Semantic Data Processing and Visualization for Public Security Intelligence Agency, Supported by One of the Leading China Companies (Anonymous for Confidential Issue) in This Field, 12/2014~12/2015. Principal Investigator.
4. Information Extraction from Specific Web Pages via Machine Learning & Natural Language Processing in the Presence of RDFS Knowledge, Supported by Focus Technology Co., Ltd, 7/2014~7/2015. Principal Investigator.
3. Analysis and visualization of Browsing Behavior on Made-in-China Website via Big Data Platform, Supported by Focus Technology Co., Ltd, 7/2014~7/2015. Principal Investigator.
2. Big Data Processing of Readings of Electric Meters in Jiangsu Smart Power Grids, Supported by Jiangsu Frontier Electric Technology Co., Ltd, 12/2013~6/2014. Principal Investigator.
1. Distributed Refined Synopsis of Data Streams, Supported by National Natural Science Foundation of China (Grant No. 60973023,1/2010~12/2012). Principal Investigator.

Slides
12. 2017年暑期人工智能和大数据技术讨论班
第0讲：符号和联结的讨论以及本次讨论的目的和内容
第1讲：神经网络计算模型和BP算法
11. 非结构化数据存储、区块链数据库-中兴通讯科技公司（南京）交流
10. 南京农业大学的深度学习交流
1. 深度学习的基本原理（企业交流）
2. 知识和深度学习的正则化（东南大学苏州研究院研究生讲座 ）
3. 区块链数据库：企业交流
4. 数据流处理（VLDB 2004 talk）
5. 基于视图的知识图谱存储（CIKM 2012 talk）
6. Datalog、逻辑语义、语义网络（
7. 基于标签的知识图谱的传递关系查询
8. 2013年海峡两岸交流： 基于全序标签的可达性查询
9. 大数据驱动的产品研发（美的新产品研发部门交流）
Reading List (Engineering Artificial Intelligence Software )
A. Deep Learning & Game Theory
1. Hybrid computing using a neural network with dynamic external memory
2. DEEP LEARNING WITH DYNAMIC COMPUTATION GRAPHS
3. Multi-agent Reinforcement Learning in Sequential Social Dilemmas
B. Big Data and Programming Model
1. MapReduce: Simplified Data Processing on Large Clusters
2. Fast Greedy Algorithms in MapReduce and Streaming
C. Logic Reasoning & Knowledge Graph
1. Reasoning and Query Answering in Description Logics
2. Ruled-based Reasoning Systems
D. Blockchain & Decentralized Application
1. Ethereum Homestead Documentation
2. Corda: A distributed ledger

研究领域

BlockChained AI-Logic（Knowledge Graph and Deep Learning for Data Science and Engineering
I am interested in the applicaton of Artificial Intelligence in data science and engineering, including logic and deep learning methods in the context of big data from the World Wide Web, which is referred to as Data and Intelligence (D & Intel). The following directions cover the main part of my application-oriented research venture.
1. Engineering AI Software: Programming Model for Deep Learning and Reasoning on Large Scale Platforms(Engineering Artificial Intelligence Software )
2. Model and Algorithm: Knowledge-Enhanced Deep Learning Models and Large Scale Training Algorithms

3. Application:Large Scale KnowledgeGraph, Unbiquitous AI, Natural Language Processing, Image Understanding, Social Behavior Analysis......
4. Blockchain System: Decentralized AI Applications via Blockchain, Programming Model for Decentralised Applications""

近期论文

9. Zhenjie Zhang, Hu Shu, Zhihong Chong, Hua Lu, Yin Yang. C-Cube: Elastic Continuous Clustering in the Cloud. IEEE ICDE 2013.
8.Zhihong Chong, He Chen, Zhenjie Zhang, Hu Shu, Guilin Qi, Aoying Zhou. RDF Pattern Matching using Sortable Views. ACM CIKM 2012. Slides.
7. Weiwei Ni, Zhihong Chong, Hu Shu, Jiajia Bao, Aoying Zhou. Evaluation of RDF Queries via Equivalence.Frontiers of Computer Science. 2012.
6.Zhihong Chong, Guilin Qi, Hu Shu, Jiajia Bao, Weiwei Ni, Aoying Zhou. Open User Schema Guided Evaluation of Streaming RDF Queries. ACM CIKM 2010.
5. Weiwei Ni, Jinwang Zheng, Zhihong Chong. HilAnchor: Location Privacy Protection in the Presence of Users' Preference. Journal of Computer Science and Technolog (JCST)27(2). 2012.
4.Zhihong Chong, Jeffrey Xu Yu, Zhengjie Zhang, Xuemin Lin, Wei Wang, Aoying Zhou. Efficient Computation of k-Medians over Data Streams Under Memory Constraints. Journal of Computer Science and Technolog (JCST) 21(2). 2006
3. Jeffrey Xu Yu, Zhihong Chong, Hongjun Lu, Zhenjie Zhang, Aoying Zhou. A False Negative Approach to Mining Frequent Itemsets from High Speed Transactional Data Streams.Information Sciences 176(14). 2006 .
2.Zhihong Chong, Jeffery Xu Yu, Hongjun Lu, Zhenjie Zhang, Aoying Zhou. False-Negative Freuqent Items Mining from Data Streams with Bursting. DASFAA 2005.
1. Jeffrey Xu Yu, Zhihong Chong, Hongjun Lu, Aoying Zhou. False Positive or False Negative: Mining Frequent Itemsets from High Speed Transactional Data Streams.VLDB 2004.