Skip to main content
King Abdullah University of Science and Technology
Computer, Electrical and Mathematical Sciences and Engineering
Computer, Electrical and Mathematical Sciences and Engineering
  • Home
  • Study
    • Prospective Students
    • Current Students
    • Internship Opportunities
  • Research
    • Research Overview
    • Research Areas
    • Research Groups
  • Programs
    • Applied Mathematics and Computational Science
    • Computer Science
    • Electrical and Computer Engineering
    • Statistics
  • People
    • All People
    • Faculty
    • Affiliate Faculty
    • Instructional Faculty
    • Research Scientists
    • Research Staff
    • Postdoctoral Fellows
    • Students
    • Alumni
    • Administrative Staff
  • News
  • Events
  • About
    • Who We Are
    • Leadership Team
  • Apply

Breadcrumb

  1. Home
  2. Profiles
  3. Eman Kabbas

Eman Kabbas

About Eman Kabbas

Eman Kabbas

  • Ph.D. Student, Applied Mathematics and Computational Science

Bayesian and computational Statistics Bayesian Data Aalysis data science Applied and theoretical statistics Data Sciences

Deeply passionate about Bayesian statistics, Eman Kabbas is a Math/Statistics Lecturer in the General Studies Department at Jubail Industrial College (JIC). Currently, Eman is a Ph.D. candidate in Applied Mathematics and Computational Sciences at KAUST, specializing in Bayesian statistics under the supervision of Professor Håvard Rue.

Events

Presented Events

Nov 2 - Nov 8, 2025

  • Proper Random Walk Spline Models

    Eman Kabbas, Ph.D. Student, Applied Mathematics and Computational Science
    Nov 2, 15:00 - 17:00

    B3 L5 R5209

    Bayesian and computational Statistics data science

    This dissertation introduces the Proper Random Walk of order 2 (PRW2), a full-rank Gaussian Markov random field that provides a principled alternative to intrinsic random walk (RW2) priors. By construction, RW2 models exhibit heteroscedastic marginal variances, inflated boundary effects, sensitivity to grid design, and unbounded forecast uncertainty—features that undermine the reliability of inference, particularly in sparse-data settings or beyond the observed domain.

Engage

Related Sites

  • Bayesian Computational Statistics and Modeling (BAYESCOMP)
  • Applied Mathematics and Computational Science (AMCS)
  • Statistics (STAT)

Related Content

  • View related articles
  • View related events

Apply for postgraduate study

Start your application

Are you Eman Kabbas?

Login to edit your profile.

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE)

Connect with us

Footer

  • A-Z Directory
    • All Content
    • Announcements
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice

Disclaimer: The views and opinions expressed in this page are strictly those of the page author.