About Me​

 

I am currently a data scientist at Microsoft Research where I apply generative deep learning methods to study protein design. I completed my PhD in Chemical Engineering at University of Washington under the supervision of Jim Pfaendtner as an NSF GRFP Fellow. During my PhD I applied and developed computational methods to probe interfacial phenomena that govern biological processes at the microscale, informing their behavior at the macroscale. Previously, I was a FURI undergraduate researcher synthesizing 2D materials in the Tongay Research Group and graduated Magna Cum Laude in Chemical Engineering at Arizona State University.

 

My goal is to gain a deeper understanding of the fundamental driving forces in biological systems, so that we as scientists can rationally design efficient and promising bioinspired technologies. I am motivated by biological phenomena which can be studied through the lense of computational research and molecular level design. Specifically, I am interested in leveraging powerful machine learning approaches to increase the speed at which these molecules can be studied. Read more about my research here.  

 

I am passionate about equitable access and representation in the computational research space. I am the first person in my family to go to college, and grew up in a Colombian/Iranian immigrant household. Like so many other first-gen students the journey to being a researcher has never been straightforward, or easy. When I decided to pursue a PhD, I took a risk and pivoted into the world of computational research. While it's been filled with ups and downs, I feel lucky to have found my passion. Sadly, this isn't the norm for all URM students in one of the most underrepresented fields in STEM. This has driven me to increase equitable access to academia and provide underserved students the tools, guidance, and mentorship they need to be successful. 

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Feel free to contact me with any questions