I am a PhD candidate at the NUS Graduate School for Integrative Sciences and Engineering (NGS), National University of Singapore. I am part of the Lab for Media Search (LMS) and my advisor is Prof. Tat-Seng Chua. My primary research interests are in data mining and machine learning using large-scale datasets, with an emphasis on their applications in health informatics and social informatics.

Latest News

  • 06/2017

    One paper on "Wellness Representation of Users in Social Media: Towards Joint Modelling of Heterogeneity and Temporality", was accepted in Transaction of Knowledge and Data Engineering, TKDE, 2017.

  • 10/2016

    One paper on "Leveraging Behavioral Factorization and Prior Knowledge for Community Discovery and Profiling", was accepted by WSDM, 2017.

  • 9/2016

    One paper on "Towards Organizing Health Knowledge on Community-based Health Services", was accepted by EURASIP JBSB.

  • 7/2016

    One paper on "360° user profiling: past, future, and applications", was published by ACM SIGWEB Newsletter.

  • 7/2016

    Our paper on "On the Organization and Retrieval of Health QA Records for Community-based Health Services", recieved the Best Paper Award by IJCAI, BOOM.

  • 6/2016

    One paper on "On the Organization and Retrieval of Health QA Records for Community-based Health Services", was accepted by IJCAI, BOOM Workshop, 2016.

  • 11/2015

    One paper on "From Tweets to Wellness: Wellness Event Detection from Twitter Streams", was accepted by AAAI 2016.

Research Interests

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My area of interest spans Media Search and Retrieval. Within the range, my current research focus is on the area of Knowledge Management and Organization in Social Media, KnowledgeGraph extraction and embedding, and Multimodal information fusion and rerrieval. Specifically, I am interested in structuralizing and organizing User Generated Contents (UGCs) for healthcare and well-being domain.

Research Projects

  • Sensing Wellness from Social Media Traces

    As today’s social platforms have increasingly been transformed into social sensors, a significant focus of my research has been devoted to understanding the wellness of users through their online traces left in social platforms, in both microscopic level of individuals and macroscopic level of user groups and population, by developing computational methods which analyze large scale data. Through such understanding, my goal is to solve real world societal problems, such as people health and lifestyle challenges, and thereby improve the quality of the life of people.

  • Knowledge Organization in Health Domain

    Community-based services leverage the wisdom of crowd through supporting communication, information sharing, and collaboration between individual users. Unsurprisingly, the impact of social media has been extended to the health care domain, as consumers have begun to seek information, share knowledge and experiences online. Therefore it imposes a greater impact on people’s daily information seeking, knowledge construction, and decision making. Although online community-based health services (CBHS) accumulate a huge amount of knowledge and grow at a continuously increasing pace, this knowledge is not effectively accessible due to the unstructured, noisy and opaque nature of data. To enhance the aggregation, navigation, and access into knowledge of the crowd, this research explores techniques to automatically analyze, organize, and retrieve large scale user generated contents (UGCs) on CBHSs.

  • Multi-Modal Information Retrieval and Ranking

    Information reranking is to recover the true order of the inittial search results. Traditional reranking approaches, such as graph-based and pseudo-based, have achieved great success for uni-modal queries. They, however, suffer from some intrinsic limitations. (1) They only capture the pairwise relations instead of high-order relations, which may lead to information loss; (2) They also usually simply concatenate heterogeneous features into one vector that may cause the curse of dimensionality, and neglect the effects of different type of features. In this work, we investigate to find a unified multi-modal framework for multi-modality information retrieval system, where the queries can be mixture of texts, images, videos and audios.

Selected Publications
[Google Scholar] [DBLP]

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Please send e-mail to me to request (p)reprints of papers that do not have a downloadable pdf associated with them.


  • Mohammad Akbari, Tat-Seng Chua, Leveraging Behavioral Factorization and Prior Knowledge for Community Discovery and Profiling , ACM WSDM.
  • 2016



    • Nie, Liqiang, Mohammad Akbari, Tao Li, and Tat-Seng Chua, A joint local-global approach for medical terminology assignment, In Medical Information Retrieval Workshop at SIGIR 2014.
    • Nie, Liqiang, Tao Li, Mohammad Akbari, Jialie Shen, and Tat-Seng Chua, Wenzher: Comprehensive vertical search for healthcare domain, Annual ACM SIGIR Conference.

    Professional Experiences and Services

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    • Teaching Assistant, National University of Singaopore, 2015
      Social Media Computing, CS4242
    • Lecturer, Azad University, 2006-2015
      Neural Network, Artificial Intelligence, Compiler Design, Programming Languages Design and Implementation
    • Invited Lecturer, Iran University of Science and Technology, 2008-2009
      Compiler Design, Artificial Intelligence, Advanced Programming

    Journal and Conference Reviewer

    • IEEE Transaction of Knowledge and Data Engineering (TKDE).
    • ACM Transaction on Knowledge Discovery from Data.
    • Pattern Recognition Letters Journal.
    • World Applied Science Journal
    • ACM Multimedia Conference ACM MM 2015
    • World Wide Web and Population Search at AAAI 2015
    • IEEE International Conference on Healthcare Informatics 2015 (ICHI 2015)
    • IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining ASONAM 2015
    • IEEE AINL-ISMW 2015


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    I I occasionally update my blog here.

    Contact Information

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    Contact info

    The best way of cummmunicating with me is through Twitter. However, there is my contact information.

    • 13 Computing Dr, 117417
    • akbari@u.nus.edu

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