Monaf Gawish, M.Sc.

Am Schwarzenberg-Campus 4 (C)

21073 Hamburg

Building: C - Room: 2.003

eMail: Monaf Gawish

Phone:++49 (0)40 42878-6113

Short Biography

Monaf Gawish received his Bachelor of Science degree in chemical engineering in 2019 from King Fahd University of Petroleum and Minerals (KFUPM) in Dhahran, Saudi Arabia. After graduation, he worked as a research assistant in the Department of Chemical Engineering at KFUPM, where he focused on researching novel heterogeneous catalysts and developing adsorbent and enzyme-assisted systems for wastewater remediation. 

In 2021, he joined Hamburg Technical University to pursue a master's degree in Chemical and Bioprocess engineering. His Master's thesis, which he conducted at the Institute of Process Systems Engineering, was focused on the large-scale screening and evaluation of intensified distillation configurations, with the additional consideration of heat exchanger networks, optimized for energy demand, exergetic efficiency, and costs. Starting in February 2025, Monaf joined the Institute of Process Systems Engineering as a research assistant further pursuing a Ph.D. degree.

Field of Research

Monaf’s research focuses on improving the energy efficiency, sustainability, and economic viability of chemical processes to meet the evolving demands of the industry. This includes not only the identification of novel process concepts but also the evaluation of various technologies for energy integration such as heat exchanger networks and heat pumps. By integrating advanced model-based optimization techniques, his work aims to develop cost-effective and computationally efficient methods for generating heat and work recovery networks, facilitating enhanced energy recovery and process integration

A key component of his research is the optimization of energy and material flows, ensuring that process systems are designed with minimal thermodynamic losses. To achieve this, second-law thermodynamic analysis is employed to pinpoint inefficiencies and identify opportunities for improvement. By leveraging process modeling, advanced simulations, and tailored optimization algorithms, his research contributes to the development of next-generation energy-efficient processes for the future.