I'm a graduate Computer Engineering student, with a strong passion for Artificial Intelligence.
Based in 
Rovigo, Italy but my heart will be forever in my Erasmus home 
Prague, Czech Republic.
Available to move anywhere in the world.
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Machine Learning:
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Robotics:
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App Programming:
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OOP:
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Web Development:
An Empirical Study on Ensemble of Segmentation Approaches: (🔗Code | 📄Published Paper)
- Empirical search of the best ensemble architecture to perform colorectal polyps segmentation
- Tested ensembles with different backbones, data augmentation methods and loss functions
- Personally, I implemented several loss functions to create ensembles with greater diversity
- Achieved 0.893 Dice score
- Developed with MATLAB
Sentiment Analysis for Climate Change: (🔗Code | ✍️Blog Article)
- Sentiment Analysis over a tweets dataset regarding climate change with BERT and other Machine Learning techniques (e.g. SVM)
- Category 13 of the Sustainable Development Goals defined by the United Nations: Climate Action
- Achieved 0.86 F1-Score
- Developed with Tensorflow, Pandas, Scikit-learn, Python
Better Quality Embeddings for Node Classification Combining Classificiation with Link Prediction in Graph Neural Networks (🔗Code | 📄Paper)
- Implementation of Link Prediction as self-supervised pre-training technique in Graph Neural Networks for node classification.
- Tested with GCN, GAT and GraphSAGE (with mini-batch generation) with MLP for improved learning during Link Prediction task.
- Personally, I developed the whole training loop. My colleagues implemented grid search algorithms.
- Developed with Pytorch, Pytorch Geometric, Python
🌤️ Multi-dataset Weather Classification: (🔗Code | 📄Report)
- Image classification over weather images coming from multiple datasets.
- Usage of joint training for classes having similar features across different datasets.
- Handling of dataset and class imbalance.
- Usage of histograms with Linear Neural Networks for testing over fully unseen dataset.
- Achieved 0.994 Accuracy
- Developed with Pytorch, OpenCV, Python
🐢 Sea Turtle Face Detection for Ocean Conservation: (🔗Code | 📄Report)
- Object detection of turtles' heads with RetinaNet algorithm
- Category 14 of the Sustainable Development Goals defined by the United Nations: Life Below Water
- Achieved 0.878 IoU score
- Developed with Tensorflow, Pandas, Python
Grayscale to RGB for CNN training: (🔗Code | 📄Report)
- Conversion of 16 grayscale foraminifera images to a single image in RGB format
- The goal is to improve the classification accuracy of a CNN, the conversion is done with unsupervised learning techniques
- Achieved 0.805 accuracy
- Developed with MATLAB
Where Am I? (🔗Code | 📄Report in Italian)
- Android application to track in real-time the longitude, latitude and altitude of the device. Showing also the history of the past 5 minutes. Everything on a map as well.
- Developed with Kotlin
and many others... Just look at my repositories.