Introduction

Foreword

Goal

• Taking data science and information computing knowledge as the main axis, combining mathematics and statistics, information science and high-performance computing to solve practical problems in the industry.
• Reorganize the teaching and research direction of teachers in the department to enhance high-quality research and teaching.
• Cultivate forward-looking data science knowledge, data engineering system design and cross-domain integration capabilities to meet the industry's needs for talents with advanced R&D and value-added capabilities.

Brief introduction

• Data science and scientific computing are interdisciplinary studies, which basically involve several major subfields. The foundations include: information science, numerical methods and optimization, probability and statistics, etc., supplemented by various applications and related domain knowledge, such as medical fluids, image processing, natural language processing, time series analysis, program trading, medical imaging, etc. The department will re-integrate the planning of courses and teachers' research directions in response to the needs of practice and the industry.
• The concept of our institute is to combine scientific computing modeling, information, mathematics, statistics and other teachers, and structure the integration of these four professional fields to cultivate data analysis talents to meet the needs of national development and industrial upgrading. In this interdisciplinary emerging field - data science and information computing, we hope to cultivate talents with core competencies in both information and statistics disciplines, so that they can conduct cross-field data research in various industries. Especially for the complex and huge amount of various types of data generated by different industries at present, conduct in-depth knowledge exploration and establish prediction mechanisms and models, introduce data science and computing at all levels, and enhance the development of future emerging technology industries.
• Integrate teachers with professional background in mathematical analysis and statistics to strengthen students' professional background in data science analysis and information computing, and based on this, integrate into various professional fields of data analysis and computing.