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Nicolo Chino

Nicolo Chino

Physcist, Machine Learning expert: Supervised and Unsupervised Model Building for data classification and prediction and image recognition

GERMANY flag
Karlsruhe, Germany
$20.00/hrEntry LevelOtherLabel Studio

Key Skills

Software

Other
Label StudioLabel Studio

Top Subject Matter

Electrical consumption analytics
Semantic segmentation for defects image detection
ML Pipeline builders for classification and prediction of data, and classification of image particularities

Top Data Types

TextText
Computer Code ProgrammingComputer Code Programming
ImageImage

Top Task Types

Classification
Segmentation
Computer Programming Coding

Freelancer Overview

Machine Learning Project: Supervised and Semi-supervised Model Building. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Science, University of Trento (2025) cum laude and Master of Science, Sorbonne Université, Institut Polytechnique de Paris, Université Paris-Saclay (2024) ranked 3rd in the class. AI-training focus includes data types such as Text and labeling workflows including Classification. Current PhD at KIT from March 2026 on the use of ML for the development and the optimization of perovskite material for solar cell application.

Entry LevelFrenchGermanEnglishItalianSpanish

Labeling Experience

PhD topic at KIT on use of ML for the development and optmization of perovskite material for solar cell application

ImageClassification
The first and nowadays part of the works is to write a code to train a Neural Network on recognition and classification of defects during the solidification from solution of the solar cell.

The first and nowadays part of the works is to write a code to train a Neural Network on recognition and classification of defects during the solidification from solution of the solar cell.

2026 - Present

Machine Learning Project: Supervised and Semi-supervised Model Building

OtherDocumentClassification
Developed supervised and semi-supervised models in Python to predict and analyze regional time- and space-resolved electrical consumption patterns. The process involved preparing datasets, designing appropriate features, and validating model performance. Conducted annotation and labeling of dataset outcomes to improve algorithm training and validation cycles. • Handled time-series and text-based data for training purposes • Applied classification labeling to electricity consumption trends • Used Python (NumPy, Pandas, scikit-learn) for implementation • Refined model performance through iterative labeling feedback.

Developed supervised and semi-supervised models in Python to predict and analyze regional time- and space-resolved electrical consumption patterns. The process involved preparing datasets, designing appropriate features, and validating model performance. Conducted annotation and labeling of dataset outcomes to improve algorithm training and validation cycles. • Handled time-series and text-based data for training purposes • Applied classification labeling to electricity consumption trends • Used Python (NumPy, Pandas, scikit-learn) for implementation • Refined model performance through iterative labeling feedback.

2023 - 2023

Education

S

Sorbonne Université, Institut Polytechnique de Paris, Université Paris-Saclay

Master of Science, Plasma and Fusion Physics

Master of Science
2024 - 2025
U

University of Trento

Master of Science, Physics

Master of Science
2023 - 2025

Work History

K

Karlsruhe Institute of Technology

PhD

Karlsruhe
2026 - Present
A

AIA Association

Football Referee

Rovereto
2019 - Present