Home \ Faculty Details \ Ibtisam Daqqa
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  • Phone:

    +966-13-849-8881

  • Email:

    idaqqa@pmu.edu.sa

  • Office No:

    F-09

  • Ibtisam Daqqa

  • Job Title :

    Assistant professor

  • College :

    College of Sciences and Human Studies


  • Department :

    Mathematics & Natural Sciences


 

Ibtisam Daqqa  is an assistant professor in Mathematics and Natural Sciences Department at Prince Mohammed Bin Fahd University. She specializes in Applied Mathematics. Daqqa’s work focuses on blending theoretical applied mathematics with practical applications in physics, medicine, materials science, and educational methodology.In teaching, Dr. Daqqa emphasizes inquiry-based learning and aims to help students develop critical thinking and collaboration skills.

 

  • Ph.D. 2008  University of South Florida, Tampa, Florida.
  • M.Sc. 1998  University of Jordan, Amman, Jordan.
  • B.Sc. 1995  Applied Science University, Amman, Jordan.

Geometrical representation and Hirota direct approach for multiple soliton solutions of nonlinear M-coupled fractional equations

AA Hassaballa, M Yavuz, EAB Abdel-Salam… - Mathematical and Computer Modelling of Dynamical …, 2025

 

Dynamics of Kink and Multi-Kink Solitons in the Stochastic (2+ 1)-Dimensional Burgers Equation with Multiplicative White Noise

I Daqqa - Appl. Math, 2025

 

Stochastic Effects on Soliton Dynamics in the KdV Equation with Multiplicative White Noise

HM Adel-Salam, FMK Almalki, I Daqqa, MS Ali… - Appl. Math, 2025

 

Stochastic dynamics of solitary waves in the damped mKdV equation: analytical solutions and numerical simulations

M Zayed, HM AbdelSalam, I Daqqa, S Abdel-Khalek… - AIMS Mathematics, 2025

 

Uniqueness of the solution for the conjugation problem of third-order partial differential equations and its application in neural network regularization

NK Arkabaev, H Abdelsalam, I Daqqab, S Alkhalafc… - Thermal Science, 2025

 

Predictive modeling of breast cancer incidence: A comparative study of fuzzy time series and machine learning techniques

I Daqqa, AM Almarashi, MM Bashier, M Aripov… - Journal of Statistics Applications & Probability, 2024

 

Structural and magnetic properties of nanoparticle semiconductors La1-xSrxMnO3

ZMH El-Qahtani, AM Adam, A Elshafaie, EMM Ibrahim… - Thermal Science, 2025

 

Adaptive individual differences in math courses

MAE Pilotti, H Abdelsalam, F Anjum, I Muhi, S Nasir… - Sustainability, 2022

 

Is initial performance in a course informative? machine learning algorithms as aids for the early detection of at-risk students

MAE Pilotti, E Nazeeruddin, M Nazeeruddin, I Daqqa… - Electronics, 2022

 

Thermal case study of cilia actuated transport of radiated blood-based ternary nanofluid under the action of tilted magnetic field

N Saleem, T Ashraf, I Daqqa, S Munawar, N Idrees… - Coatings, 2022

 

Analysis and power quality improvement in hybrid distributed generation system with utilization of unified power quality conditioner

N Zanib, M Batool, S Riaz, F Afzal, S Munawar, I Daqqa… - Comput. Model. Eng. Sci, 2022

 

Predicting math performance of Middle Eastern students: The role of dispositions

MAE Pilotti, HM Abdelsalam, F Anjum, I Daqqa, I Muhi… - Education Sciences, 2022

 

 

Entropy production in electroosmotic cilia facilitated stream of thermally radiated nanofluid with ohmic heating

N Saleem, S Munawar, A Mehmood, I Daqqa - Micromachines, 2021

 

Mental Simulation Effects on Performance: Benefits of Outcome Versus Process Simulations in Online Courses

D Ibtisam, H Abdelsalam, MA Pilotti, H Al Mulhem - International Journal of Cognitive Research in Science …, 2020

 

 

The effect of cyberloafing on employee productivity

M Saleh, I Daqqa, MB AbdulRahim, N Sakallah - International journal of advanced and applied sciences, 2018

 

The subconstituent algebra of strongly regular graphs associated with a Latin square

B Curtin, I Daqqa - Designs, Codes and Cryptography, 2009

 

The subconstituent algebra of a Latin square

B Curtin, I Daqqa - European Journal of Combinatorics, 2009


 

 

Department of Mathematics and Natural Sciences, Prince Mohammad Bin Fahd University, Al Khobar 31952, Saudi Arabia

List research interests :

1. Nonlinear differential equations & soliton theory:

    - Exploring geometrical representations and uniqueness of solutions for higher‑order PDEs, with applications in neural networks.

2. Mathematical modeling & data‑driven analysis:

    - Applying fuzzy time series and machine‑learning techniques to predict medical phenomena

    - Studying structural properties of materials (nanoparticle semiconductors) using mathematical characterization.

3. Mathematics education:

    - Developing diagnostic measures and adaptive teaching strategies for Calculus, especially for disadvantaged learners, and analyzing individual differences in math courses.

 

Google Scholar

https://scholar.google.com/citations?hl=en&authuser=2&user=w4m694UAAAAJ

https://orcid.org/0000-0002-5379-3097

  • Assistant professor , Prince Mohammad Bin Fahd University, Khobar, KSA. 2008 –to date.
  • Associate Chair/ Math and Natural Sciences Department, PMU, Khobar,KSA 2012-2016.
  • Teaching Assistant, University of South Florida, Tampa, Florida. 2002– 2008.
  • Instructor, Hashemite University, Zarqa, Jordan. 1999–2002 .   
  • High School Teacher, Zarqa, Jordan. 1998–1999.    

 

1. Courses I taught at Prince Mohammad University:

  • Calculus (I), Calculus (II), Calculus (III).
  • Ordinary Differential equations.
  • Linear Algebra
  • Finite Mathematics.
  • Calculus for business.
  • Statistical Methods
  • Probapility and Statistics

2. Courses I taught at the University of South Florida:

• Pre-calculus Algebra/Trigonometry.

• College Algebra.

 

3. Courses I taught at the Hashemite University(Jordan):

• Calculus (I), Calculus (II), Calculus (III).

• Discrete Mathematics.

• Business Calculus.

 

 

1. Nonlinear differential equations & soliton theory:

    - Exploring geometrical representations and uniqueness of solutions for higher‑order PDEs, with applications in neural networks.

2. Mathematical modeling & data‑driven analysis:

    - Applying fuzzy time series and machine‑learning techniques to predict medical phenomena

    - Studying structural properties of materials (nanoparticle semiconductors) using mathematical characterization.

3. Mathematics education:

    - Developing diagnostic measures and adaptive teaching strategies for Calculus, especially for disadvantaged learners, and analyzing individual differences in math courses.