Postdoc at Johannes Kepler Uiversity Austria
Summary:
Dr. Amira MEDDAH is a senior postdoctoral researcher at Johannes Kepler University, Linz, specializing in stochastic modelling, numerical analysis, and hybrid dynamical systems. Her research integrates mathematical modelling with real-world applications in neuroscience and finance. Dr. MEDDAH has collaborated with experts across disciplines to model brain tumor invasion and develop financial prediction models. She is dedicated to advancing mathematical frameworks while ensuring their practical relevance. Her work has been recognized in high-impact peer-reviewed journals, and she is passionate about mentoring young researchers and promoting interdisciplinary innovation.
Profile:
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Orcid Profile
Education:
Dr. Amira MEDDAH earned her PhD in Applied Mathematics from Johannes Kepler University (JKU), Linz, Austria. Her doctoral research focused on stochastic modelling, numerical analysis, and their interdisciplinary applications in neuroscience and financial mathematics. Dr. MEDDAH has a strong academic foundation in applied mathematics and computational modelling, with a deep emphasis on developing innovative methods for complex real-world problems.
Professional Experience:
Dr. MEDDAH is a postdoctoral researcher at JKU Linz, where she specializes in stochastic modelling and numerical analysis with a focus on hybrid dynamical systems. Her work spans interdisciplinary domains, including neuroscience, where she collaborated with clinicians at Kepler University Hospital to model glioma (brain tumor) invasion, and finance, where she developed advanced stochastic hybrid models for pricing American options. She has supervised master’s students and actively participates in academic teaching at JKU. Dr. MEDDAH is also engaged in industry collaborations, such as validating predictive models for financial data with Sparkasse bank and the Statistical and Data Analysis Institute. Her professional memberships include Austrian Women in Mathematics (2021–2022).
Research Interests:
- Stochastic Modelling: Developing models for hybrid systems, particularly Piecewise Diffusion Markov Processes (PDifMPs).
- Numerical Analysis: Designing novel computational methods for simulating stochastic processes.
- Financial Mathematics: Applying stochastic hybrid systems for American option pricing and risk assessment.
- Tumor Modelling: Investigating glioma invasion dynamics to improve medical predictions through mathematical modelling.
Top Noted Publications:
“A Stochastic Hierarchical Model for Low-Grade Glioma Evolution”
- Authors: E. Buckwar, M. Conte, A. Meddah
- Journal: Journal of Mathematical Biology
- Volume and Issue: 86 (6)
- Year: 2023
- Citations: 3
- Description: This paper presents a stochastic hierarchical model to study the dynamics of low-grade glioma growth. The model incorporates stochastic processes to simulate the complex and heterogeneous behavior of glioma cells, providing new insights into tumor progression.
“A Stochastic Hierarchical Model for Low-Grade Glioma Evolution” (Duplicate Title, Alternate Listing)
- Authors: A. Meddah, M. Conte, E. Buckwar
- Journal: Journal of Mathematical Biology
- Year: 2023
- Citations: 3
“Numerical Approximations and Convergence Analysis of Piecewise Diffusion Markov Processes, with Application to Glioma Cell Migration”
- Authors: E. Buckwar, A. Meddah
- Platform: arXiv Preprint
- Preprint ID: arXiv:2401.13428
- Year: 2024
- Citations: 2
- Description: This work introduces novel numerical approximation techniques for Piecewise Diffusion Markov Processes (PDifMPs), which are applied to simulate glioma cell migration. The convergence analysis ensures the robustness of these methods for practical applications.
“American Option Pricing Using Generalized Stochastic Hybrid Systems”
- Authors: E. Buckwar, S. Desmettre, A. Mallinger, A. Meddah
- Platform: arXiv Preprint
- Preprint ID: arXiv:2409.07477
- Year: 2024
- Description: This paper employs generalized stochastic hybrid systems to model and price American options, contributing to financial mathematics by introducing innovative techniques for handling the complexities of financial derivatives.
“Stochastic Hybrid Dynamical Systems for Simulating Low-Grade Glioma Evolution”
- Author: A. Meddah
- Year: 2024
- Description: This standalone work by Dr. Meddah develops stochastic hybrid dynamical systems specifically tailored for simulating the evolution of low-grade gliomas. The research bridges clinical insights with advanced mathematical tools, enhancing tumor modelling accuracy.
Conclusion:
Dr. Amira Meddah is a strong candidate for the Best Researcher Award, given her interdisciplinary impact, innovative methodologies, and commitment to mentoring. Her ability to integrate complex mathematical tools with real-world applications positions her as a leading researcher in applied mathematics. However, enhancing her citation impact, expanding industry-academic collaborations, and assuming leadership roles in her field could further solidify her profile for such awards. With her current trajectory and dedication, Dr. Meddah has the potential to become a highly influential figure in both academia and industry.