HKUST Big Data Institute

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Presentation transcript:

HKUST Big Data Institute Director: Qiang Yang Associate Directors: Lei Chen and Yuan Yao Hong Kong University of Science & Technology

Goal Lead and promote cutting-edge research in Big Data and Artificial Intelligence research, applications and education Inclusive: coverage includes all HKUST academic community as well as industrial and governmental partners

Privacy & Security Data Sharing Policy Data Mining & Visualization Smart Cities Genetic Farming Health Finance & Risk Management Online Shopping Data Mining & Visualization Privacy & Security Data Sharing Policy Big Data Computing & Data Management Data Integration Data Extraction Logistics Data Web Data City Data Financial Data Agricultural Data Sensor Data

Big Data Institute Organization Structure

Existing Centers BDBI Center: Smart City Center WHAT LAB Big Data for Bio Intelligence (Raymond Chu, $1M USD/5 years) Smart City Center Thales-HKUST ITF project (10M -2 years) Digital China-HKUST ITF Project (20M- 2 years) WHAT LAB Wechat (10 M- 5 year) Angel ML System, WeChat

Big Data Bio Intelligence Centre HKUST The Big Data for Bio Intelligence (BDBI) Laboratory, dedicated to designing data analytic solutions for big data in biology and healthcare to advance knowledge and improve people’s living, is officially opened in May 2016.

BDBI Centre The Laboratory aims to become a leading laboratory in the research of big data for biological intelligence and to bridge the knowledge gap between academics and practitioners. Its establishment was made possible by the donation by Mr Raymond Chu, an undistracted industrialist spanning over three decades. He hopes his support could enhance the University’s research efforts with the broad aim to benefit humanity. Research areas of the Laboratory include new big data solutions such as “deep learning solution”, which generates rich features to describe a machine learning problem in order to let computers make decisions, and “transductive transfer learning” – allowing computer models to be easily adapted for use in many different application domains. It will also focus on genetic farming with objectives of making the process more automatic and user-friendly and scaling it to cater to very large data sources.

Thales – HKUST ITF Project Under the backdrop of Innovation and Technology Fund (ITF), HKUST and Thales, a global technology leader in the Aerospace, Transportation and Defense & Security markets, join in the research and development to build a Big Data platform to address critical problems in the public transport. This is a unique project where academia, industry and government work closely together to build an interdisciplinary and cross-domain solution for problems pertinent to Hong Kong and other large cities.

Thales – HKUST ITF Project The platform aims at (1) effectively monitoring and directing the crowd in railway stations so that early warnings can be given on potential dangers (2) ensuring smooth operation of railway transport system by predicting potential major equipment failure The platform fuses together many state-of-the-art big-data research topics, such as data fusion, data analytics, human factors, optimization/visualization, transfer learning, simulation and operations research.

Digital China - Big Data in Smart City A first ever attempt to build a people-aware smart city framework that centers on the residents of a city. The project will integrate data extracted continuously from the people, discover their needs from integrated multi-source data, and finally determine the best resource allocation plans to satisfy their needs. People’s needs from the areas of education, health, travel, safety, finance and entertainment, which all have measurable objectives, will be studied in this project. In order to achieve the goals in the framework, several state of art techniques will be developed including data integration solutions to handle different data sources with different formats, transfer learning-based mechanisms to reveal knowledge, and machine-human collaborative approaches to make wise decision.

Smart City Project (Digital China) Location–based information integration of the city

WECHAT-HKUST AI Technology LAB (WHAT LAB) In November 2015, HKUST joined hands with Tencent to establish WHAT LAB (short for WeChat-HKUST Joint Lab on Artificial Intelligence Technology) at HKUST campus, a laboratory dedicated to foster artificial intelligence and big data research to improve people’s living and advance the frontiers of knowledge, marking a milestone in the collaboration of WeChat and the higher education sector.

WHAT LAB WeChat and HKUST will jointly conduct Artificial Intelligence (AI) Technology related research and explore the far-reaching frontiers of AI. Today AI technology is experiencing a tremendous growth, and much of this advancement depends on talents, problems and data. WeChat and HKUST complement each other in these aspects, and this collaboration on AI research is expected to be long-term and world-leading. Research areas of WHAT LAB include intelligent robotic systems, natural language processing, data mining, speech recognition and understanding. The Lab will bring together top researchers in the development of innovative artificial intelligence application with the database of WeChat.

MSc Program in Big Data Technology Big data is poised to change the way enterprises function and a society operates, and is changing the way science and engineering is conducted. A Master of Science programme in Big Data Technology jointly offered by the Departments of Computer Science and Engineering and Mathematics in HKUST integrates different disciplines together to allow students to know all the important aspects of the big data and how it is used in the real world. This highly competitive and sought after programme offers both full time part time modes of studies in 1 or 2 years respectively. Student intakes in both Fall and Spring every year.

Contact Professor Qiang Yang, qyang@ust.hk Miss Irene Lau, irenelau@cse.ust.hk Yuan Yao, yuany@ust.hk Lei Chen, leichen@ust.hk