Leonardo Pinheiro
Senior Scientist at National Measurement Institute of Australia
Sydney, New South Wales, Australia
Summary
🤩
Rockstar🎓
Top SchoolLeonardo Pinheiro is a Senior Scientist in Sydney with 11 years of experience at the intersection of biometrology, molecular biology, and data-driven methods for high-accuracy nucleic acid measurement. He leads development and validation of biological standards at the National Measurement Institute, translating rigorous laboratory science into globally recognized measurement infrastructure. His background spans academia and industry, from postdoctoral molecular engineering to product-focused R&D and lab accreditation management. Recently he has extended his technical footprint into data, cloud and machine learning, contributing backend code to the high-profile microsoft/autogen project to implement image token counting for vision-enabled agents. That blend of hands-on wet-lab expertise, regulatory-quality processes, and practical ML engineering gives him a rare ability to operationalize complex bioinformatics and measurement problems. Colleagues rely on him for scientific rigor, reproducible systems, and pragmatic cross-disciplinary solutions.
11 years of coding experience
7 years of employment as a software developer
PhD Biochemistry, School of Molecular Sciences La Trobe University, Melboune, Australia (2002).
Stackoverflow
411reputation
89kreached
4answers
10questions
Github Skills (18)
openai-api10
integrate10
ai-agent10
pytest10
python10
testing10
autogen10
llm10
agent10
ai9
anaconda6
subset6
scikit-learn6
aws-lambda6
amazon-web-services6
Programming languages (5)
Github contributions (5)
microsoft/autogen
Oct 2024 - Mar 2025
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Role in this project:
Backend Developer
Backend DeveloperContributions:89 reviews, 46 PRs, 15 pushes in 5 months
Contributions summary:Leonardo contributed code related to image token count logic within the `microsoft/autogen` repository, indicating work on core functionalities. This involved modifying the OpenAI client, specifically the `_openai_client.py` file, to calculate vision tokens. The changes included implementing token calculations based on image size, incorporating constants like `MAX_LONG_EDGE`, and utilizing the `encoding.encode()` function. Additionally, the user updated tests within `test_model_client.py` to validate the newly implemented token counting logic.
agenticagentic-agiagentsaiautogen
lspinheiro/autogen
Oct 2024 - Apr 2025
A programming framework for agentic AI 🤖
Contributions:249 pushes, 34 branches in 6 months
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