Mauro Mora
PhD Student, Computer And Electrical Engineering at Khalifa University
Abu Dhabi Emirate, United Arab Emirates
Summary
👤
Senior🎓
Top SchoolMauro Mora is a PhD student and experienced machine learning engineer with nine years of industry and research experience bridging AI and renewable energy systems. He develops forecasting tools to optimize power ramping in large-scale PV plants and has built end-to-end web deployments of AI models using frameworks like PyTorch and TensorFlow. His background spans academia and applied roles—from the University of Toronto and Khalifa University to startups—covering NLP, image/video processing, and energy applications. Known for clear communication and teamwork, he brings both practical software engineering (full-stack cloud deployments) and rigorous research skills to projects that require moving models from prototype to production. A less obvious strength is his cross-disciplinary training in medical science and computer engineering, which sharpens his ability to apply ML to diverse, high-stakes domains.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Engineering - BE Computer Science, Bachelor of Engineering - BE Computer Science at Tecnológico de Costa RicaDoctor of Philosophy - PhD Computer and Electrical Engineering, Doctor of Philosophy - PhD Computer and Electrical Engineering at Khalifa UniversityMaster of Science - MS Medical Science, Master of Science - MS Medical Science at University of TorontoSoftware Developer Technician Ingeniería de software, Software Developer Technician Ingeniería de software at Calle Blancos Professional Technical High School
English, Spanish
Github Skills (30)
convolutional-neural-networks10
tensorboard10
wandb10
pytorch9
semantic-segmentation9
kaggle9
segmentation9
deep-learning8
evaluation-function8
cnn-classification7
podcast6
image-segmentation6
reboot6
classification6
artificial-neural-networks6
Programming languages (4)
Github contributions (5)
PARMAGroup/UNet-Instance-Cell-Segmentation
Nov 2018 - Jan 2019
[Pytorch] This project aims to perform well at instance segmentation on the BBBC006 cells dataset. We tested UNet over several configurations including the loss function, evaluation function and the datasets.
Contributions:4 commits, 1 push in 2 months
evaluation-functioninstance-segmentationpytorchsegmentationunet
mamemo/mamemo
Feb 2023 - Feb 2026
Contributions:3 pushes, 1 branch in 3 years
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