Maria A. Castellanos, PhD

About me

I am a Postdoctoral Research Fellow at the Memorial Sloan Kettering Cancer Center (MSKCC), where I work with Dr. John D. Chodera developing computational methods to accelerate antiviral drug discovery for viruses with pandemic potential. My research combines structure-based approaches, such as Docking and Free Energy Perturbation (FEP), with machine learning to identify broad-spectrum antiviral candidates.

I am broadly interested in applying physics-based and AI-driven methods across various stages of the drug discovery pipeline to optimize the development of therapeutics for high-priority targets. For more details on my research interests and background, see here.

Education and Previous Roles

I completed my Ph.D. in Chemistry from the Massachusetts Institute of Technology (MIT) in November 2023, where I was a MolSSI Software Research Fellow. Under the guidance of Prof. Adam P. Willard, my graduate work focused on advancing computational methodologies to explore organic materials for solar energy applications.

I developed a Python workflow for high-throughput screening of properties in small molecules and DNA nanostructures, automating force field development, molecular dynamics, quantum chemistry, and machine learning steps.

Previously, I graduated with a Bachelor’s (BA) in Chemistry from Icesi University, in Cali, Colombia (in 2017, cum laude). During this time, I developed a model using genetics algorithms to analyze the energy landscape of ultracold atoms.
I was a quantum applications intern at IBM Research, San Jose, CA, during the summer of 2021 and 2022. During my internship I enhanced software to optimize the functionality of quantum computers to predict small molecule properties, such as electrostatic potentials and force field partial charges.

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Maria A. Castellanos, PhD

Education and Previous Roles

I developed a Python workflow for high-throughput screening of properties in small molecules and DNA nanostructures, automating force field development, molecular dynamics, quantum chemistry, and machine learning steps.

Previously, I graduated with a Bachelor’s (BA) in Chemistry from Icesi University, in Cali, Colombia (in 2017, cum laude). During this time, I developed a model using genetics algorithms to analyze the energy landscape of ultracold atoms.

I was a quantum applications intern at IBM Research, San Jose, CA, during the summer of 2021 and 2022. During my internship I enhanced software to optimize the functionality of quantum computers to predict small molecule properties, such as electrostatic potentials and force field partial charges.