This repository archives technical projects developed during my Bachelor’s degree at Bocconi University. The work contained herein reflects a dual focus on rigorous independent research and collaborative development within student-led technical organizations.
Key highlights include:
- Developed a soft-max-biased simulated annealing framework for grid-based stochastic optimization, incorporating topological landscape analysis
- Implementation of Graph Transformer Convolutional Networks and custom experimental layers for molecular property prediction (BELKA Competition)
- Research in Quantum Machine Learning using JAX and Pennylane, specifically targeting gradient-free optimization and stochastic quantum circuits.
- Collaborative initiatives with BAINSA (Bocconi AI & Neuroscience Association) and BSDSA (Bocconi Students Data Science Association)
- Description: A collection of projects done in collaboration with BAINSA, BSDSA and BSML, reflecting my engagement with data science and machine learning
- Key Learnings: Hyperparameters optimization, Feature Map explanation, Dimensionality Reduction, Sequential Model architecture, External API usage, Image processing, Object Detection, Adaptive Data Loading
- Description: This project involves using the BERT model for sentiment analysis of financial headlines, offering insights into market trends and investor sentiment
- Key Learnings: Introduction to NLP Models
- Description: This project was a submission for the BELKA competition hosted on Kaggle, where the objective was to predict the binding affinity of a given molecule and protein
- Key Learnings: Parallel Processing, Graph Transformer Convolutional Network, Implementation of Experimental Layer proposed here
- Description: This folder contains all the required and elective projects I completed during my studies
- Key Learnings: R, Pennylane, JAX, Quantum Machine Learning, Exploratory Data Analysis, Model Evaluation and Interpretation, Feature Engineering, Genetic Algorithms, Randomer Forest, Deprecated Library Restoration, Data Imputation, Stochastic Optimization, Gradient Free Quantum Optimization
Feel free to explore the projects and reach out if you have questions or want to collaborate!