Gnanasenthil P.

Key Skills

Software

Other

Top Subject Matter

Medical/Clinical research and medical education (Physiology)

Computational simulation and automation for biomedical/analytical workflows

Top Data Types

Text

Top Task Types

Prompt + Response Writing (SFT)

Freelancer Overview

Medical Doctor & Associate Professor of Physiology (AI workshops, prompt engineering training). Brings 14+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include python programming using Google Colab. Education includes Doctor of Medicine, Christian Medical College (2012) and Bachelor of Medicine and Bachelor of Surgery, Government Mohan Kumaramangalam Medical College (2007). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Prompt + Response Writing (SFT), Computer Programming, and

Labeling Experience

Computational Simulation & Automation Architect (automation for AI-ready workflows)

Automated analytical and high-throughput data processing tasks using Google Colab scripts. Developed reproducible computation pipelines to replace manual calculations with code-based workflows that can support downstream AI/analysis steps. Leveraged scientific Python libraries to handle large numeric tables reliably. • Used Google Colab to orchestrate batch processing • Applied NumPy and SciPy to automate large-table numerical calculations • Converted spreadsheet-based steps into versionable scripts for reproducibility • Produced computation workflows suitable for AI-assisted analysis augmentation

2013 - Present

Medical Doctor & Associate Professor of Physiology (AI workshops, prompt engineering training)

OtherTextPrompt + Response Writing (SFT)

Conducted workshops teaching researchers how to use modern AI tools for systematic literature reviews and clinical data discovery. Supported participants in applying prompt engineering practices to improve the quality and reliability of AI-generated outputs for academic research workflows. Integrated Python and Google Colab materials to automate parts of training and educational workflows. • Taught usage of Gemini, ChatGPT, SciSpace, and Research Rabbit for literature review acceleration • Emphasized prompt engineering to improve AI reasoning and response quality • Helped apply LLM outputs to cross-specialty clinical data discovery workflows • Delivered hands-on Python/Colab-based automation tied to AI-enabled research tasks

2013 - Present

Education

Work History