Amos Ben-Zvi

Assistant Professor
7th Floor ECERF - Room 7-027
9107 - 116 Street
Edmonton, AB T6G 2V4
Phone: 780.492.7651
Fax: 780.492.2881
Email

Website 

Research Areas: modeling of biochemical and biomedical systems; development of computational and theoretical tools to test the identifiability of differential algebraic models, data analysis for control and optimization

Current Research Projects

  • Modeling and Control of the Hypothalamus-Pituitary-Adrenal Axis
    Co-Investigator: Dr. Gordon Brodrick, Dept. Medicine, University of Alberta
    Degree Programs: MSc, PhD
    The Hypothalamus Pituitary Adrenal (HPA) axis is critical for the regulation of the body's response to stress. Dysfunction of the HPA axis system leads to chronically suppressed blood cortisol concentration and is associated with a variety of illnesses including post-traumatic stress disorder. We are currently working towards two key goals: a) developing a comprehensive model of the HPA axis and integrating this model with existing models of the immune system; and b) developing a clinically applicable treatment course for HPA axis disregulation.
  • Modeling and Optimization of Oil Production in Microalgae
    Co-Investigator: Dr. McCaffrey, University of Alberta
    Degree Programs: MSc, PhD
    Algal oil is a valuable commodity that can be used in a variety of processes including food, pharmaceutical, and biofuel production. We are currently in the process of developing a mathematical model that will describe the kinetics of algal growth in a fed-batch bioreactor system. The proposed model will be used to control the algal growth process in order to optimize oil production.
  • Development of Process Analytic Tools for Process Systems
    Co-Supervisor: Dr. McCaffrey, University of Alberta
    Degree Programs: MSc, PhD
    Research Direction: In recent years, process analytic technology has become more affordable for a variety of applications. We currently have a Raman and near infrared (NIR) Spectrometers. We are using these spectrometers to develop online monitoring techniques for an algal bioreactor. We hope to develop tools to monitor substrate concentration, biomass concentration and algal oil concentration.