Mona Elsayed Moawad Abdelgaid

overview

I am a Ph.D. candidate in the field of high-throughput computational design of heterogeneous catalysts at the Mpourmpakis Lab, University of Pittsburgh. Throughout my doctoral journey, I have harnessed the power of density functional theory, microkinetic modeling, and kinetic Monte Carlo simulations to unravel complex hydrocarbon dehydrogenation mechanisms on heterogeneous catalysts. I have developed a computational framework for descriptor-based screening of dehydrogenation catalysts. This research endeavor culminated in the discovery of novel aluminum nitride catalysts with remarkable dehydrogenation activity. I have also participated in multi-institutional collaborations, spearheading all computational efforts. As part of my graduate coursework and projects, I have applied machine learning techniques using Python, R, and MATLAB programming languages to address real-world challenges. In my current role as a Ph.D. candidate, I have supervised junior graduate students on various research projects while leading various computational funding proposals which have resulted in more than 9 million computational hours on multiple supercomputers being awarded to the Mpourmpakis Lab. Furthermore, serving as the Recruitment Chair of the Graduate Student Association in the ChE Department at the University of Pittsburgh, I coordinated the 2021 ChE Graduate Department recruiting weekend and organized social and volunteering events to promote community within the ChE graduate department.