Over 20 years of experience in technical consulting and solutions for the IT industry. He has served as Enterprise Service Manager of Sybase Software China Ltd.；Senior Technical Consulting Manager of Telecom Industry of Oracle (China) Software Systems Co., Ltd., and Senior Manager of Cloud Computing and Big Data Consulting Team. He is currently Director of Products and Solutions at Fusionskye (Beijing) Technology Co., Ltd., focusing on combining big data with artificial intelligence technology to provide products and solutions for smart operations and business insight.

Topic: Exploration and application of intelligent analysis of log data based on machine learning method

Enterprise digital transformation puts forward higher requirements for IT operation and maintenance, security operations and business data analysis. IT operation data can empower enterprise digital transformation, ensure business continuity, enhance user experience, prevent security risks and real-time business. Insights and other fields bring innovation. This lecture takes log data analysis as an entry point, analyzes the pain points of traditional log collection and structured processing methods, and automatically realizes the normalization of log data through machine learning models, which is unreadable and non-standard. The log data extracts valuable information for active operation and maintenance, real-time alarms, security situational awareness, anomaly detection, forecasting and business intelligence services.

Audience benefits:

Log data is an important data asset of enterprises. It can provide important information and value for enterprises through real-time collection, correlation analysis and mining of log data; log styles are numerous and often change, and log collection and application have been done. People will experience the time-consuming, laborious, inefficient, and small coverage difficulties and complexity of log data processing. The traditional method based on regular expressions limits the effective use of log data. This method can be used to obtain intelligent analysis of log data. And the solution, to ensure the validity of the log data, to fully play and develop the application scenarios of the log data.

Responsible for the construction and operation of Novogene team and IT department. 9 years of professional experience in process design and genomic analysis for second generation sequencing technology (NGS). Published 25 SCI results papers in the field of bioinformatics with a cumulative impact factor of 200 points. In recent years, three patents for bioinformatics analysis and several software copyright applications have been completed.

Topic: Bio-information technology integration in NGS scale application

With the accumulation of NGS data, AI algorithm technology has become more important for the comprehensive mining of data. Through the accumulation of NGS database, AI algorithm can increase the interpretation accuracy and analysis speed of NGS data.

Audience benefits:

1）AI optimizes NGS business processes

2）The role of AI in NGS data mining

3）Practical application of AI in NGS solution

R&D Director of Data Science Team at GBase

Pei Fei had served as senior product development management in ArrayNetworks, VMware, etc. Currently, he is the R&D director of the data science team at GBase, responsible for the construction of the company's AI platform for big data, and includes finance, securities, insurance, Big data analytics solutions in a wide range of fields, including telecommunications, customs, security, and government, with extensive experience in big data and artificial intelligence technologies.

Pei graduated from Tsinghua University with a bachelor's degree and a master's degree in computer science, focusing on database and software. Received a master's degree in computer network from North Carolina State University.

Topic: Big Data and Artificial Intelligence: Requirements, Technology, and Implementation

In the era of big data, people are more concerned about how to extract value from data. The new AI technology from human-computer interaction, data analysis to decision-making automation, completes the process from data to value realization, with varying application in different fields.

The big data analysis of massive data has higher requirements on algorithm processing capability, real-time processing performance, etc., which have a profound impact on the future development trend of big data and AI technology.

In each field, how to apply our dazzling technology to specific business scenarios, to solve practical problems, all of these put forward new requirements and challenges on how to build relevant teams.

Audience Benefits:

1） Understand the digital age, big data and artificial intelligence needs and application areas

2） Understand the trends and cutting-edge technologies of big data and artificial intelligence

3） Understand how big data and artificial intelligence technologies come to the ground, staffing and team building