Portrait of Wei-Ying Ma

Wei-Ying Ma

Assistant Managing Director
Microsoft Research Asia


Wei-Ying Ma is an Assistant Managing Director at Microsoft Research Asia where he oversees several research groups including Machine Learning, Natural Language Computing, Web Search and Data Mining, Social Computing and Urban Computing. He and his teams have developed many key technologies for search engine and online advertising that have been successfully transferred to Microsoft’s Bing and Ads Center. In recent years, he has led teams in partnership with the Microsoft Application Service Group to develop several famous conversational agents including Xiaoice (in China) and Rinna (in Japan) that inspire and motivate much new research and innovations in both academia and industry. He also led his team to open-source many cutting-edge technologies at GitHub, including the Distributed Machine Learning Toolkit (http://www.dmtk.io/) which makes machine learning tasks involving big data highly scalable, efficient and flexible; Microsoft Graph Engine (https://www.graphengine.io/) which is a distributed, in-memory, real time graph processing engine designed to serve a large knowledge graph for text understanding; and Microsoft Concept Graph (https://concept.research.microsoft.com/) which contains a big graph of 5M concepts and 12M facts/instances mined from billions of web pages and years’ worth of search logs. He also transferred many key technologies to many other Microsoft products including Cortana, Exchange, SharePoint, Delve, Azure, and Microsoft Cognitive Services.

Wei-Ying Ma has published more than 270 papers at international conferences and in journals. He is a Fellow of the IEEE and a Distinguished Scientist of the ACM. He has served on many editorial boards including ACM Transactions on Information System (TOIS), the ACM/Springer Multimedia Systems Journal, and the Journal of Multimedia Tools and Applications. He was a member of International World Wide Web (WWW) Conferences Steering Committee from 2010 to 2016. He has served as program co-chair of WWW 2008, program co-chair of the Pacific Rim Conference on Multimedia (PCM) 2007, general co-chair of the Asia Information Retrieval Symposium (AIRS) 2008, and the general co-chair of ACM Special Interest Group on Information Retrieval (SIGIR) 2011. Under his leadership, his teams from MSRA have been actively publishing research results at conferences such as NIPS, ICML, KDD, ACL, WWW, SIGIR, ACM Multimedia, CIKM, and AAAI.


Graph Engine

Established: May 14, 2015

Graph Engine, previously known as Trinity, is a distributed, in-memory, large graph processing engine. We are very pleased to announce that the Graph Engine 1.0 preview has finally been released to the public. Graph Engine, previously known as Trinity, is…


Established: October 30, 2010

Trinity is a general purpose distributed graph system over a memory cloud. Memory cloud is a globally addressable, in-memory key-value store over a cluster of machines. Through the distributed in-memory storage, Trinity provides fast random data access power over a…

Microsoft Academic

Established: February 22, 2016

Microsoft Academic: Helping researchers stay on top of their game Microsoft Academic (academic.microsoft.com) is an online destination that helps researchers like you connect with the most personally relevant papers, research news, conferences, people, and ideas, powered by artificial intelligence (AI)…
















Summary of Research Works

Wei-Ying Ma developed several technologies during his Ph.D. research at University of California at Santa Barbara, including one of the first content-based image retrieval systems on the Web (called Netra), the widely-used Gabor texture features for image retrieval, and one of the first practical image segmentation solutions for processing a large number and variety of natural scene images (which enables image retrieval systems to provide region-based search capabilities). He is also one of the first researchers to identify the problem of similarity measure in content-based image retrieval, and developed a machine learning approach to learn the similarity measure for image retrieval. In recent years, he has been leading a team at Microsoft Research Asia to develop a system to analyze large-scale multimedia data for automatic annotation.

Starting in 2003, Wei-Ying has expanded his research into general Web search and has applied many innovative ideas from image analysis and segmentation to Web page analysis and information extraction. In particular, he developed the first technique to analyze Web pages using visual cues and use the information to model the Web and extract structured data from Web pages. With these advanced Web-analysis techniques, Wei-Ying has led his team to develop a next-generation search engine that goes beyond traditional page-level relevance ranking. By extracting and integrating information about real-world entities such as people, places and things (e.g. products) from billions of public Web pages, his system creates a paradigm shift on Web search by enabling search queries, relevance ranking, and browsing and navigation of search results at the level of entities and objects. The resulting entity-level search engine – the first on the Web that provides automatic summaries of entities and allow users to navigate and explore their relationships – can be found at http://entitycube.research.microsoft.com (a Chinese-version of the search engine, called Renlifang, is also available at http://renlifang.msra.cn). He and his team also built the Microsoft academic search engine based on entity-level search technologies, which is available at http://academic.research.microsoft.com/. It provides many innovative ways to retrieve rank and explore scientific papers, conferences, journals, and authors based on their importance and relationship.

Wei-Ying and his team also initiated an effort in Microsoft to develop a web-scale data mining infrastructure for search. Different from traditional Internet services, search involves myriad offline computations to analyze the data at a very large scale, and an infrastructure for “scale” experiments is often required to evaluate the effectiveness of newly invented algorithms in a semi-real environment. Such an infrastructure is also critical for supporting massive web mining, knowledge discovery, and asynchronous metadata exchange in a search engine pipeline so that the cycle of idea formulation, experimentation, and deployment can be iterated quickly.

Wei-Ying is an inventor or co-inventor of over 80 patents in the area of web search and multimedia information retrieval.

The following are some of the systems Wei-Ying and his team have developed at Microsoft Research which have been released to the public.

EntityCube (http://entitycube.research.microsoft.com)

EntityCube is a research prototype for exploring object-level search technologies, which automatically summarizes the Web for entities with a modest web presence. Key technologies include web-scale entity extraction, name disambiguation, entity ranking, and relationship extraction and exploration.

Renlifang (http://renlifang.msra.cn/)

Renlifang is the Chinese version of EntityCube (and the name EntityCube is the English translation of Renlifang) which currently has millions of daily page-views during peak times. It has received wide press coverage and publicity in China.

Microsoft Academic Search Engine (http://academic.research.microsoft.com/)

Using similar technologies, Wei-Ying and his team created this academic search service to facilitate the exchange of ideas and communications between academic communities. A user can retrieve relevant information on academic papers, scientists, conferences, and journals and thus generate more accurate, relevant, and efficient results in comparison to document-level ranking. Features of this search service include the ability to find top scientists, conferences, and journals in a specific field, locate top research papers, and identify rising stars or hot topics in a specific field.

Microsoft TravelGuide (http://travel.msra.cn/)

TravelGuide is a vertical search engine for the travel domain that utilizes deep web crawling and forum site structure analysis technologies developed by Wei-Ying and his team. This engine aggregates travel related information from across the web and presents relevant knowledge to the user, helping them understand more about travel destinations, such as popular places, themes, short trips, etc.

Selected Publications

Keynote Speeches

Wei-Ying Ma has been invited to give keynote speeches at the following academic conferences and industrial forums on web search, multimedia computing, and cloud computing.

  • Empowering People with Knowledge: the Next Frontier for Web Search
    The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Hyderabad, India, 2010.
  • Rethinking Multimedia Search in the new “Cloud + Clients” Era
    The Workshop on Large-scale Multimedia Mining and Retrieval at ACM Multimedia Conference 2009
  • Cloud Computing and the Future of Internet Services
    The 10th International Mobile Data Management (MDM) Conference 2009
  • Building Web-scale Data Mining Infrastructure for Search
    The 10th Asia-Pacific Web Conference, APWeb 2008
  • The Challenges and Opportunities of Mining Billions of Web Images for Search and Online Applications
    The Multimedia Retrieval Workshop at SIGIR 2007
  • The Challenges and Opportunities of Mining Billions of Web Images for Search and Advertising
    The 9th International Conference on Visual Information Systems, VISUAL2007
  • Building Infrastructure to Support Web-scale Data Mining for Search
    DBWeb in Kyoto, Japan, 2006
  • Object-level Vertical Search
    Workshop on Web Information Retrieval and Integration at ICDE 2006
  • From Relevance to Intelligence: Toward Next Generation Web Search
    Multimedia Information Retrieval (MIR) Workshop at ACM Multimedia Conference 2005
  • Adaptive Content Delivery on Mobile Internet across Multiple Form Factors
    International Multimedia Modeling (MMM) Conference 2004
  • Towards Next Generation Web Search
    International Conference on Web Information Systems (WISE) 2004