In today's dynamic and ever-changing business environment, I remain committed to innovating new ways to deliver valuable insights from the data we collect–and even from data we do not yet know it will be worthwhile to collect–in an effort to provide IT-based solutions to businesses, organizations and society. As an industrial engineer and a Master's student in the Department of Management Sciences, I have conducted research across the years and helped beneficiaries extract insightful results from data, e.g., social media.
Today–at the University of California, Berkeley–my focus is centered on the cutting-edge field of protein design. My research involves the application of advanced computational tools such as large language models, Variational Autoencoders (VAEs), diffusion, and flow-matching techniques. This work is integral to understanding and innovating in the complex area of protein structures, a critical aspect of bioengineering.
The core of my work in protein design leverages these computational models to delve into the intricacies of protein structures and functions. By applying these techniques, I aim to contribute to groundbreaking advancements in therapeutic solutions and healthcare technologies. The integration of NLP and VAEs into the study of proteins represents a novel approach, bridging data science and bioengineering in a unique and impactful way.
As I continue to navigate the intersection of engineering, data science, and bioengineering, my objective is to develop solutions that are not only technologically advanced but also contribute meaningfully to the scientific community and society. My experience in protein design positions me to make significant contributions to the field of bioengineering, especially in areas where innovation is key to advancing our understanding of biological systems
And while I'm busy untangling the complexities of proteins, I'm still trying to figure out the best way to fold my laundry – it turns out proteins are a bit more cooperative!
