UCLA Computer Science Department

Thuy Vu
Thụy Vũ
Scalable Analytics Institute (ScAi)
Computer Science Department, UCLA
first.last@Smiley face.edu

Thuy completed his Ph.D. program in the Computer Science Department at University of California, Los Angeles (UCLA) in Winter 2017. He was under the supervision of Professor D. Stott Parker. He still meets with Professor Parker to discuss about things, from education to data science and also sustainability.

Prior to attending UCLA, he was an R&D engineer at the Institute for Infocomm Research, Singapore from 2006 to 2011. At the Institute, he worked on two projects in multingual information extraction and machine translation. He was named the Achiever of the Year FY-2009 for his R&D contribution in Human Language Technology. He received the B.S. in Computer Science from University of Science, Vietnam.


Thuy's general interest is to connect theories and advances in different computational problems. He is particularly interested in processing and mining structured and textual data, especially on:

  • data explanatory and mining
  • natural language processing, focusing toward theories in computational linguistics
  • machine learning, especially in learning feature representations for structured and textual data
  • large-scale data processing and analytics
  • Meanwhile, Thuy is investigating applications of automatic feature learning for compositionality related problems in natural language and structured data.

    Thuy also enjoys reading topics in other areas. He took varied graduate courses in theoretical computer science, bio-informatics, statistics, linguistics, and managements. In the past year, he had an opportunity with studies on environment and sustainability -- one of his interests. This Summer, he served the IPAM's RIPS 2016 as an academic mentor supporting a team of four students working on an industrial project helping GumGum in their bid stream delivering.


    Thuy has spent a non-trivial amount of time assisting courses in his Department, from lower division to upper division and also graduate level. The list includes:
    1. CS31 & CS32 Introduction to Computer Science 1, 2 (programming and data structures in C/C++)
    2. CS33 Introduction to Computer Organization (architecture; assembly language; and operating systems fundamentals)
    3. CS35L Software Construction Laboratory (fundamentals of open-source tools and environments)
    4. CS131 Programming Languages (principles of programming languages and language paradigms)
    5. CS132 Compiler Construction (compiler structure; lexical and syntactic analysis; semantic analysis and code generation; and theory of parsing)
    6. CS181 Languages and Automata Theory (abstract computational devices: automata, regular expression, grammar, Turing machines)
    7. CS249 Data Science Principles (concepts and methods for scalable data analysis of data)


    1. Mining Community Structure with Node Embeddings,
      with D. Stott Parker. Book Chapter in From Social Data Mining and Analysis to Prediction and Community Detection, 2017.

    2. Extracting Urban Microclimates from Electricity Bills,
      with D. Stott Parker. AAAI 2017, San Francisco. [pdf]

    3. K-Embeddings: Learning Conceptual Embeddings for Words using Context,
      with D. Stott Parker. NAACL 2016, San Diego. [pdf, bib]

    4. Node Embeddings in Social Network Analysis,
      with D. Stott Parker. ASONAM 2015, Paris. [pdf, bib]

    5. Interest Mining from User Tweets,
      with Victor Perez. CIKM 2013 Poster, San Francisco. [pdf, bib]

    6. System and Method for Aligning and Indexing Multilingual Documents,
      with Ai Ti Aw, Min Zhang, Lian Hau Lee, Fon Lin Lai. US 20110295857 A1. [link]

    7. MARS: Multilingual Access and Retrieval System with Enhanced Query Translation and Document Retrieval,
      with Lianhau Lee, Aiti Aw, Mahani Sharifah Aljunied, Min Zhang, Haizhou Li. ACL-IJCNLP 2009 Software Demonstrations, Singapore. [pdf, bib]

    8. Feature-Based Method for Document Alignment in Comparable News Corpora,
      with Aiti Aw and Min Zhang. EACL 2009, Athens. [pdf, bib]

    9. Term Extraction Through Unithood and Termhood Unification,
      with Aiti Aw and Min Zhang. IJCNLP 2008, Hyderabad. [pdf, bib]

    10. A Maximum Entropy Approach for Vietnamese Word Segmentation,
      with Dien Dinh. RIVF 2006, Vietnam. [pdf, bib]