Passionate about green technology and reducing the environmental impacts of engineering.My journey began during my undergraduate and graduate studies at KNTU, where I focused on minimizing the environmental impacts of liquefying natural gas processes. At Concordia University, I co-developed a high-order unstructured solver using flux reconstruction and discontinuous Galerkin methods for advanced flow analysis. My Ph.D. research at Concordia led to the creation of a multi-layer parallel aeroacoustic shape optimization framework, significantly contributing to aviation noise reduction. As an aerodynamic and aeroacoustic specialist at Limosa, I played a key role in the conceptual and preliminary design of electric aircraft, in particular electric Vertical Take-Off and Landing (eVTOL) vehicles. I developed numerous Python scripts to automate the design process, along with developing a low-fidelity propeller design and optimization framework.Currently, as a Postdoctoral Fellow at Polytechnique Montreal, I am expanding my expertise in Artificial Intelligence (AI) and Machine Learning (ML), developing Physics-Informed Neural Networks (PINNs) to create digital twins for hydraulic turbines in collaboration with Maya HTT and Hydro-Quebec. My passion lies in applying advanced computational methods and AI to tackle climate change in engineering applications.