Qi Long

Qi Long
  • Professor of Biostatistics in Biostatistics and Epidemiology
  • Professor of Computer and Information Science
  • Professor of Statistics and Data Science

Contact Information

  • office Address:

    201 Blockley Hall
    423 Guardian Drive
    Philadelphia, PA 19104

Teaching

Current Courses

  • BSTA7820 - Stat Meth/incomplet Data

    Selected topics from public health and biomedical research where "Big data" are being collected and methods are being developed and applied, together with some core statistical methods in high dimensional data analysis. Topics include dimension reduction, detection of novel association in large datasets, regularization and high dimensional regression, ensemble learning and prediction, kernel methods, deep learning and network analysis. R programs will be used throughout the course, other standalone programs will also be used. Prerequisite: If course requirement not met, permission of instructor required.

    BSTA7820001

  • CIS8990 - Doctoral Independent Study

    For doctoral students studying a specific advanced subject area in computer and information science. The Independent Study may involve coursework, presentations, and formally gradable work comparable to that in a CIS 5000 or 6000 level course. The Independent Study may also be used by doctoral students to explore research options with faculty, prior to determining a thesis topic. Students should discuss with the faculty supervisor the scope of the Independent Study, expectations, work involved, etc. The Independent Study should not be used for ongoing research towards a thesis, for which the CIS 9990 designation should be used.

    CIS8990080

Past Courses

  • AMCS5999 - Independent Study

    Independent Study allows students to pursue academic interests not available in regularly offered courses. Students must consult with their academic advisor to formulate a project directly related to the student’s research interests. All independent study courses are subject to the approval of the AMCS Graduate Group Chair.

  • AMCS9999 - Ind Study & Research

    Study under the direction of a faculty member.

  • BSTA6990 - Lab Rotation

    Student lab rotation.

  • BSTA7820 - Stat Meth/Incomplet Data

    Selected topics from public health and biomedical research where "Big data" are being collected and methods are being developed and applied, together with some core statistical methods in high dimensional data analysis. Topics include dimension reduction, detection of novel association in large datasets, regularization and high dimensional regression, ensemble learning and prediction, kernel methods, deep learning and network analysis. R programs will be used throughout the course, other standalone programs will also be used. Prerequisite: If course requirement not met, permission of instructor required.

  • BSTA8990 - Pre-Dissertation Lab Rot

  • BSTA9950 - Dissertation

    Ph.D. students enroll in this course after passing their candidacy exam. They work on their dissertation full-time under the guidance of their dissertation supervisor and other members of their dissertation committee.

  • CIS8990 - PhD Independent Study

    For doctoral students studying a specific advanced subject area in computer and information science. The Independent Study may involve coursework, presentations, and formally gradable work comparable to that in a CIS 5000 or 6000 level course. The Independent Study may also be used by doctoral students to explore research options with faculty, prior to determining a thesis topic. Students should discuss with the faculty supervisor the scope of the Independent Study, expectations, work involved, etc. The Independent Study should not be used for ongoing research towards a thesis, for which the CIS 9990 designation should be used.

  • GCB6990 - Lab Rotation

    Lab rotation

  • GCB8990 - Pre-Dissertation Research

    Pre-dissertation lab research

  • GCB9950 - Dissertation

    Ph.D. students enroll in this course after passing their candidacy exam. They work on their dissertation full-time under the guidance of their dissertation supervisor and other members of their dissertation committee.

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