Core Expertise 

• Computational Biochemistry & Informatics – Manage structured and unstructured data using Python and R; extract insights, build robust models (as reflected in my publications and presentations), and automate data processing workflows.

• AI/ML & Large Language Models (LLMs) – Apply advanced methods to automate processes, improve interoperability, and communicate insights effectively; demonstrated in published work and cross-team collaborations.

• Cloud & Data Platforms – Design secure, scalable architectures on AWS, Azure, and GCP; implement HIPAA/FISMA-compliant workflows for RWD/RWE and scientific modeling.

• Leadership & Mentorship – Mentor teams and train over 300 scientists; guide proposal development, standardize reusable AI components, and foster collaboration across disciplines.
  
  

Certifications 

• Over 100 licenses and online Certifications from Coursera, Udemy, Edx, Stanford  OpenCourseware, including:    

  • AWS Cloud Practitioner (since 2022)

  • Project Management Professional (PMP; since 2018)

  • Several Udacity Nanodegrees 

Technical Skills/Experiences 

With proficiency in Python and R programming languages, as evidenced by my GitHub link, I am passionate about utilizing R/RStudio for biocomputing and teaching applications. I also have hands-on experience with cloud computing platforms such as AWS/Google/Azure, where I have used SQL to extract data from databases and applied ETL and ELT (E:Extract, T:Transform, and L:Load) processes to generate and utilize Data Warehouses. Additionally, I have expertise in Anaconda and Google Colab environments for efficient Python/R development and data analysis, with Github integration for version control and collaboration. Over the last two decades, I have gained extensive experience working in the Linux OS environment, specializing in compiling, installing, and testing codes within a Linux compute cluster environment. Moreover, I have skills in semantic modeling and LLM.