Patricia Cobelli
Verified Expert in Engineering
Machine Learning Engineer and Artificial Intelligence Developer
Montevideo, Montevideo Department, Uruguay
Toptal member since November 8, 2022
Patricia is a self-taught machine learning engineer with expert knowledge of computer vision. She can handle every step of a machine learning solution, from data engineering to model training and deployment on AWS. Patricia is finishing her master's studies and collaborating on her thesis with researchers at Brown University.
Portfolio
Experience
Availability
Preferred Environment
GitHub, Amazon Web Services (AWS), Python 3, PyTorch, Trello, Slack
The most amazing...
...solution I've worked on uses computer vision models to automatically enhance eCommerce product images, improving conversion and decreasing design costs.
Work Experience
Back-end Engineer
Tired Banker
- Summarized documents using GPT-3, GPT-3.5, and GPT-4.
- Developed the REST API and deployed it to AWS API Gateway with Serverless.
- Created and populated the PostgreSQL database and deployed it to AWS RDS.
- Developed the data ETL combining AWS SQS and AWS Lambdas, which were scheduled to extract data, transform it and store it in the database.
Machine Learning Engineer
Pento
- Planned and guided the development of an object detection library. It allowed data scientists with no computer vision knowledge to add valuable information to their pipelines without the overhead of understanding computer vision models.
- Developed a web app that provides insights to improve online marketing KPIs. It involved data extraction and analysis, model implementation, API development with FastAPI, front-end development with React, and the deployment of all of them.
- Created an open-source tool to track and compare embeddings. We intended the result to be something we would use, leading to a robust and easy-to-use tool.
- Automated layer creation of an online mockup generator by implementing multiple computer vision models for segmentation, key point detection, etc. By developing the models, layer generation stopped being a bottleneck.
Researcher
Universidad de la República
- Implemented physics-informed neural networks for wind field reconstruction from LiDAR data points, being the 1st person in my country to use this technology.
- Applied Markov chain Monte Carlo algorithms (MCMC) to compute possible available power on a down-regulated wind farm, providing a single value output and a confidence range.
- Taught Fluid Mechanics to a class of engineering students.
Data Scientist
Renovus
- Developed endpoints for batch preprocessing of data, considering all the missing or incorrect data possibilities.
- Guided machine learning models implementation. By combining machine learning and wind energy expertise, I could recommend a solution that proved to be better in a cost-effective way.
- Developed an API that sends processed data to the front end.
Experience
Automatic Mockup Generation
Open-source Software Tool
Object Detection Tool
Web App for Digital Marketing Optimization
Computer Vision Model Hub
I developed and deployed the color detection model and image classification models. I also created the web pages where those models were used.
Wind Farm Analysis Tool
Renewable Energies Analysis Web App
https://www.renovus.tech/Super-resolution Paper
Investments Analysis Web Page
Education
Master's Degree in Energy Engineering
University of the Republic - Montevideo, Uruguay
Visiting Research Fellowship in Applied Mathematics
Brown University - Providence, Rhode Island, United States
Engineer's Degree in Mechanical Engineering
University of the Republic - Montevideo, Uruguay
Engineer's Degree in Chemical Engineering
Salamanca University - Salamanca, Spain
Certifications
Using Python to Access Web Data
University of Michigan | via Coursera
Python Data Sctructures
University of Michigan | via Coursera
Certificate of Proficiency in English
University of Cambridge
Skills
Libraries/APIs
PyTorch, React, Pandas, Node.js, REST APIs, SQLAlchemy, Pydantic, Scikit-learn
Tools
Git, GitHub, GitLab, PyPI, MATLAB, Trello, Slack, PyCharm, Amazon SageMaker, AWS IAM, Amazon Simple Queue Service (SQS)
Languages
Python 3, Python, JavaScript, SQL
Storage
PostgreSQL, MySQL, Elasticsearch
Frameworks
Flask, Tailwind CSS, Next.js, OAuth 2
Paradigms
Clean Code, REST
Platforms
Amazon Web Services (AWS), Linux, AWS Lambda
Other
Neural Networks, FastAPI, Machine Learning, Deep Learning, Data Visualization, Data Science, Artificial Intelligence (AI), Computer Vision, Datasets, Image Processing, Back-end, Physics Simulations, Data Wrangling, Simulations, Python Dataclasses, APIs, API Applications, Python Attrs, Machine Learning Operations (MLOps), Object Detection, Image Recognition, Early-stage Startups, Energy, Computer Vision Algorithms, Webhooks, Web Scraping, Website Data Scraping, Generative Models, Stable Diffusion, Open Source, PIP, Serverless, Generative Adversarial Networks (GANs), Object Tracking, OAuth, AI Programming, Models, Natural Language Processing (NLP), Generative Pre-trained Transformer 3 (GPT-3), Generative Pre-trained Transformers (GPT), Amazon API Gateway, Amazon RDS, Scraping, OpenAI GPT-3 API
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