Hello!

Fascinated by the mysteries of evolution, I began my career in academia as a Professor of Microbiology. Through my research, I became adept at managing big datasets, coding, and applying statistical tools, which naturally led me to the field of data science.

In my transition to becoming a data scientist, I found that my love for solving complex puzzles was vital. I take great joy in deciphering the stories hidden within data, transforming them into meaningful insights. My experience includes training in machine learning models, coding with Python and R, and completing full-stack data science projects.

I’m always eager to tackle new challenges and am particularly interested in opportunities at the intersection of biology and data science.

EXPERIENCE

Forecasting Acute Stress Using Wearable Devices | 2023

| Colab Notebook | Code |

Detection of Pneumonia using Neural Networks | 2022

| App | Notebook | Code |

Vaccination Hesitancy Prediction Using Machine Learning | 2022

| Notebook | Code |

Elucidation of a Raft-Partitioning Motif in Transmembrane Proteins | 2017

| Code |

Rapidly Characterizing the Fast Dynamics of RNA Genetic Circuitry with Cell-Free Transcription–Translation (TX-TL) Systems | 2014

Chromosome Copy Number Variation and Control in the Ciliate Chilodonella uncinata | 2013

| Code |