Big Data Management and Mining Laboratory

At BDLab (Big Data Management and Mining Laboratory), we have organized our research and education around two tracks: a Data Science track, and a Data Management and Mining track. With the Data Science track, we engage with real-world problems that can benefit from data-driven solutions (consisting of all data scientific life-cycle components), given various combinations of the Big Data V5 challenges. Toward this end, we have experienced with a number of data-driven decision-making systems (DDSs) from various application areas, such as health informatics, computational genetics, IoT, intelligent transportation, and scientific computing. The Data Science track complements the Data Management and Mining track by providing practical real-world problems, which we generalize, formalize, and rigorously study as novel data management and mining problems. In particular, we have special interest in the following areas (among others): spatiotemporal data management and mining, graph data management and mining, high-throughput data management and mining using modern hardware, and next generation database engines (or NewSQL).​


Our Team!

Meet the BDLab faculty and students



Learn about BDLab research projects



Learn about BDLab education tracks



Browse BDLab publications


News News (See More)

  • First Place Award at RaCAS 2020

    We are thrilled to announce that the CS senior design team that mentored by Dr. Farnoush Banaei-Kashani (the director of BDLab) and Dr. Min Choi over the last year has received the 1st place award at RaCAS 2020 under the “Technology, Engineering, & Math” category.
    Here are the team members listed in alphabetical order:
    • Koo, Jahoon
    • Lie, Tobby
    • Macfarlane, Kevin
    • Piner, Devin
    • Young, Drake
    More news articles are available here.

  • MobiSys 2020 Paper Acceptance

    Please join us to congratulate Zohreh Raghebi, Even Stene, and Katrina Siegfried, who had two papers accepted for publication in the Mobisys 2020 conference. We wish them many years of great achievements.
    More information about these papers can be found here.

  • DMBIH 2019 Best Paper Award

    Please join us to congratulate Evan Stene, our Ph.D. student, for winning the best paper award at DMBIH (ICDM) 2019.
    Authors: Evan Stene and Farnoush Banaei-Kashani
    Title: SeAlM: A Query Cache Optimization Technique for Next Generation Sequence Alignment
    Workshop: Eighth Workshop on Data Mining in Biomedical Informatics and Healthcare (DMBIH 2019)
    Date: 11/9/2019
    More information about his paper can be found here.

 Tweets! (See More)

Readings Readings

See more PHD Comics© here.

Facebook  Facebook (See More)