Self-driven graduate research assistant pursuing degree in Biomedical Sciences. Highly skilled in conducting novel research, writing and reviewing manuscripts and grants. Extensive background spanning scientific research, python programming, machine learning, natural language processing, and pharmacy practice. Highly passionate and motivated in applying advances in machine learning and artificial intelligence in the health field.
Investigating the role of A1 and A2 neurons and the changes in supraoptic nucleus cell electrophysiological properties resulting in inappropriate vasopressin release and dilutional hyponatremia after bile duct ligation (BDL) surgery. Also worked with a team in analyzing mRNA expression in pig heart after heart failure.
Employed machine learning models to analyze regional differences in building energy efficiency to predict energy consumption to help maximize energy efficiency and reduce carbon emissions due to energy generation.
Machine learning
undefinedIBM Data Science Professional Certificate, University of London on Coursera
Courses: What is Data science?; Tools for Data Science; Data Science Methodology; Python for Data Science,
AI & Development; Python Project for Data Science; Databases and SQL for Data Science with Python; Data
Analysis and Visualization with Python; Machine Learning with Python; Applied Data Science Capstone.
• Application of python in data science, machine learning and data visualizations on real world datasets.
• Worked on a python project employing various skills in SQL, web scraping and building dashboards.
Machine Learning A-Z TM: Hands-on Python & R in Data Science, Udemy.com
• Learned multiple machine learning algorithms and their applications to real world problems.
• Built various machine learning models using Python and R.
Data Analysis with R, Duke University on Coursera.
Courses: Introduction to Probability and Data with R, Inferential Statistics, Linear Regression and Modeling.
• Experimented with statistical methods for data analysis using R.
• Analyzed huge datasets to find trends and associations, and visualized the results using R.
Introduction to Python, 365DataScience.com
• Learned the syntax of python, data types and structures, control statements, libraries, etc.