深圳计算科学研究院

Research

Volume

Bounded Evaluation

We strive to rebuild a query processing framework for big data with constrained resources and enable enterprises to benefit from big data.

Data-driven Approximation

We reach for a quantum leap from traditional approximate computing and Head strongly towards data-driven approximate algorithms and theories.

Velocity

Parallel Scalability

We are engaged in a novel strategy of balancing computing resources and efficiency, thus cutting overhead costs producing from distributed computing.

Automatic Incremental Calculation

We are working on an effective and universal incremental method, using program language, compilers, and algorithm skills to build incremental program.

Variety

Cross-Modal Fusion Computation

The future development trends lies in the optimization of the query of multi modal data and the value of integration and utilization of such results.

VERACITY / VALUE

Big Data Quality Assurance Model and Method

Data quality management is the process of automatically detecting and fixing data errors through semantic rule discovery to improve data availability.

Explainable AI by Combining Statistical and Logical Methods

Starting from a structure approach to causal reasoning, our research uses machine learning to improve application accuracy, and rules to ensure the interpretability of results.

People

Wenfei Fan

Chief Scientist
Foreign Member of the Chinese Academy of Sciences
Fellow of the Royal Society
Member of the Academia Europaea
Fellow of the ACM
Fellow of the Royal Society of Edinburgh

Publications

GraphScope: A One-Stop Large Graph Processing System

International Conference on Very Large Data Bases (VLDB 2021)

Jingbo Xu, Zhanning Bai, Wenfei Fan, Longbin Lai, Xue Li, Zhao Li, Zhengping Qian, Lei Wang, Yanyan Wang, Wenyuan Yu, Jingren Zhou

GraphScope: A Unified Engine For Big Graph Processing

International Conference on Very Large Data Bases (VLDB 2021)

Wenfei Fan, Tao He, Longbin Lai, Xue Li, Yong Li, Zhao Li, Zhengping Qian, Chao Tian, Lei Wang, Jingbo Xu, Youyang Yao, Qiang Yin, Wenyuan Yu, Jingren Zhou, Diwen Zhu, Rong Zhu

Making Graphs Compact by Lossless Contraction

ACM Conference on Management of Data （SIGMOD 2021）,June 20-25,2021, Xi'an, Shanxi, China

WenFeiFan, YuanHaoLi, MuYangLiu, CanLu

Incrementalizing Graph Algorithms

"ACM Conference on Management of Data （SIGMOD 2021）,June 20-25,2021, Xi'an, Shanxi, China"

WenfeiFan, ChaoTian, RuiqiXu, QiangYin, WenyuanYu, JingrenZhou

Consistent and Flexible Selectivity Estimation for High-Dimensional Data

"ACM Conference on Management of Data （SIGMOD 2021）,June 20-25,2021, Xi'an, Shaanxi, China"

YaoshuWang, ChuanXiao, JianbinQin, RuiMao, OnizukaMakoto, WeiWang, RuiZhang, YoshiharuIshikawa

DISK: A Distributed Framework for Single-Source SimRank with Accuracy Guarantee

International Conference on Very Large Data Bases (VLDB 2021), Aug 16- 20, 2021, Copenhagen, Denmark

YueWang, RuiqiXu, YulinChe, LeiChen, QiongLuo, RuiMao

More

Products & Solutions

YashanDB

YashanDB: An Independent-developed Next Generation Analytic Database

RockDQ

RockDQ: A Data Quality Enhancement System

Fishing Fort

Fishing Fort: A Graph-based Causal Inference System

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