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Department

The Institute of Data Science of the School of Economics and Information Engineering was established in 2017. It was formerly the Institute of Information Technology Application of the School of Economics and Information Engineering. There are 12 teachers in the institute, including 12 professors and associate professors. The Institute adheres to the school's philosophy of “Science and Technology, Finance and Economics”, and is responsible for the personnel training, computer application and big data research in the field of computer application technology, shouldering the heavy responsibility of serving the society.


In terms of talent cultivation, we will implement the three basic guiding principles of “taking students as the center, persisting in quality education innovation”, “disciplinary cross-cutting, adhering to innovation in scientific research achievements”, “in-depth integration of schools and enterprises, and adhering to practical teaching innovation”. For the development of the IT industry, we will cultivate high-level, practical and compound cross-cutting talents with solid discipline professional foundation, reasonable knowledge structure, excellent professional accomplishment and team spirit, and can adapt to the requirements of industrial development. Cultivate elite and applied high-end technical talents needed in the "big data" era market; cultivate the ability to integrate data, forecasting and analysis, and software development, and obtain insights from various types of data to help Internet companies or large enterprises Software development and data science application talents with extensive practical experience and capabilities.


Research direction:

(a) Digital Image Processing: The digital image processing research team is dedicated to the research of a new generation of image processing technology (high dynamic range image processing) and financial paper recognition technology for the financial industry. The research team has a number of international patents in the field of high dynamic range image processing and has won several international innovation invention awards.


Core courses: advanced algorithm analysis and design, machine learning, deep learning, design patterns, distributed systems, etc.


(b) Big data and data mining technology: research data integration theory and technology, including acquisition, cleaning, modeling and distributed processing and analysis; research data and knowledge fusion of big data in data, features, business, decision-making, etc. Models and methods; research multidimensional data modeling and cross-validation methods; study deep learning models based on neural network systems; study data interaction and hybrid presentation methods; study individual and group multi-time and multi-form content recommendation methods.


Core courses: Linux, data integration management, distributed systems, data warehousing, data mining, software testing, system analysis and design, design patterns, software reliability and security, machine learning, deep learning, and advanced database technologies;


Statistical mathematics: multivariate statistical analysis, time series analysis, stochastic processes, etc.


(3) Blockchain technology and application: At present, the blockchain technology field proposes various consensus mechanisms, cross-chain technologies and smart contract technologies that apply different requirements. On the basis of fully understanding the advantages and disadvantages of various algorithm models, Optimization plan and new transaction model and solution, including: Ethereum experimental platform environment construction; blockchain technology consensus algorithm research; blockchain technology based transaction model research; blockchain technology in financial field application research ; Blockchain and smart contracts are related research in the field of accounting auditing.


Core courses: Linux, distributed systems, software testing, system analysis and design, design patterns, blockchain introduction, network and information security.


Director: Associate Professor Zhiyi Wang