Yasuo Tabei
Yasuo Tabei (Ph.D.)
Unit Leader


  • Unit leader
    Yasuo Tabei
  • Research scientist
    Takaaki Nishimoto
  • Visiting scientist
    Masashi Tsubaki
  • Visiting scientist
    Hideo Bannai
  • Visiting scientist
    Yoshitaka Yamamoto
  • Visiting scientist
    Masakazu Ishihata
  • Visiting scientist
    Hiroto Saigo


Laboratory's photo

Massive datasets, so called big data, are ubiquitous in research and industry. Data mining researchers/practitioners face the problem of processing and analyzing such huge datasets for knowledge discoveries in various fields. However, coping with big data is a challenge because of its huge computational cost. One important approach for solving this bottleneck in big data era is to (i) build indexes from datasets as a preprocessing by using space-efficient data structures and (ii) process datasets on the indexes. Succinct data structure (SDS) is a space-efficient representation for data structures while supporting fast data operations on the representation. Recently, various types of SDSs have been proposed for compactly representing and indexing strings, trees, graphs, set of integers and so on. We research on basics of SDSs and their applications to artificial intelligence and knowledge discovery for scalable information processing.

Main Research Field
Computer Science
Research Field
Biology & Biochemistry / Pharmacology & Toxicology
Research Subjects
Data compression
Data mining
Artificial intelligence
Laboratory Website URL

Introduction Video

Talk by Dr. Naoya Takeishi, HES-SO, RIKEN-AIP on Learning gray-box deep generative models thumbnails

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