👋 Hi, I'm Nahime a ML Engineer with 4 years of experience with particular focus on Computer Vision. I had the opportunity to work in different projects concerning environmental applications (Illegal Landfills Detection, Mountain Peaks Detection, Snow Estimation). I have developed technical skills in Software Engineering, Mobile and Web Development, Machine Learning, Computer Vision, as well as soft skills such as Communication, Project Management and Leadership.
✨ About me:
class Nahi:
def __init__(self):
self.firstname = 'Rocio'
self.middlename = 'Nahime'
self.surname = 'Torres'
self.education = { 'PhD':'PoliMi (It.)', 'Msc':'UNLP (Arg.)'}
self.projects = ['PeakLens', 'SavagerAI', 'ODIN']
self.experience = {'Research Felllow': ['PoliMi', 'UNLP'], 'Teaching Assistant': ['PoliMi', 'UNLP'], 'Java Developer': ['Global Logic'], 'Functional Analyst': ['Accenture']}
self.interests = ['SE', 'ML', 'CV', 'RS', 'Environmental Monitoring']
self.languages = ['Spanish', 'English', 'Italian']
self.hobbies = ['Dancing', 'Cooking']📌 Projects:
- PeakLens: an AI+CV powered Android applicationfor engaging people in mountain exploration. With more than 1M downloads it was voted Most Popular App on 2020 Huawei App Innovation Contest
- AerialWaste: a dataset for the discovery of illegal landfill. The dataset contains +10.000 satellite images from three different sources at high resolution. The dataset emerges as part of the Savager AI project to detect illegal landfills from Satellitary Imagery in collaboration with Regional Environmental Protection Agency of Lombardy (Italy)
- ODIN Diagnosis Tool: an open-source framework assisting the life-cycle of ML applications (computer vision, time series, and generic classification) in the phases of data preparation, prediction performance evaluation, and error diagnosis. ODIN is agnostic to the training platform and input formats and can be extended with application- and domain-specific meta-annotations and metrics with almost no coding.
📫 How to reach me:
