Welcome! I am currently a 3rd year Ph.D. student in the Department of Chemical and Biomolecular Engineering at the Johns Hopkins University. I work with Dr. Rigoberto Hernandez to build data-driven models for material property prediction across multiple length scales. These models are used in conjunction with black box optimization algorithms to design materials with bespoke properties. We are currently interested in building these models for Metal Halide Perovskite Solar Cells. Learn about this work here.

Prior to joining in the Ph.D. program, I completed my Masters degree in the same lab where I worked on developing simulation tools to study the dynamics of unfolding of large proteins. My interest in studying biomolecules grew from my undergraduate research where I worked on building pseudo-kinetic models for Loop-Mediated Isothermal Amplication of DNA.

My goal is to develop tools to aid scientists in extracting insights from their data and accelerate the discovery of new materials.

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News Flash !

  1. [Sep 11] Judge for JHU AICheE UG and MSE Poster Symposium.

  2. [July 9] Mentoring Bryan Zhan, a highschooler interning at PNNL for the summer. Going through the basics of Python and Machine Learning with him.

  3. [July 24 - July 26] Reviewer for ML4LMS Workshop. Part of ICML 2024.
    Program Committee

  4. [July 2] Started my internship at Pacific Northwest National Lab ! Working with Dr. Jinhui Tao to develop machine learning models for designing crystal growth modifiers to yield calcite crystals with desired morphologies.

  5. [March 27 - March 29] Team lead in Bayesian Optimization Hackathon for Chemistry and Materials. Worked with Maitreyee Sharma Priyadarshini, Gigi (Yiren) Wang and Jarett Ren to use BO with local GP to find Covalent Organic Frameworks (COF) with the best methane storage capacity.
    Project Description Code link

  6. [March 1] Selected for round 2 in Merck Innovation Cup.

  7. [Feb 9 - Feb 10] Participated in Greenhacks to come up with solutions to reduce the climate and ecological impact of commercial farming.

  8. [Sep 27] Presented in AI-X Foundry Symposium.
    Twitter Link

  9. [July 18] Taught in a Summer workshop on Python and Machine Learning Fundamentals organized by Dr. Pratyush Tiwary from UMD. Contributed to tutorials explaining how to use PyTorch for building Machine Learning models.
    Workshop Link

  10. [Aug 21 - Aug 25] Presented at American Chemical Society Conference, Chicago, IL, USA, 2022. Talk title : "Mutational Assay of an Actophorin Protein using Adaptive Steered Molecular Dynamics"

2024 2023 2022