- 👀 I’m interested in data science, particularly deep learning, natural language processing (NLP), statistical modeling, and computational musicology.
- 🌱 I’m currently working on my thesis in computational musicology, where I apply deep learning techniques to analyze musical patterns. I’m also learning advanced deep learning techniques, diffusion models, and exploring novel AI applications in text and image generation.
- 💞️ I’m looking to collaborate on data science projects involving NLP, generative models, music analysis, and computational musicology.
- 📫 You can reach me via LinkedIn or explore my projects on GitHub.
- 😄 Pronouns: He/Him
- ⚡ Fun fact: In addition to being a data scientist, I’m also a professional violinist!
Popular repositories Loading
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SchedNoise-Diffusion
SchedNoise-Diffusion PublicImplementation of diffusion models with varying noise distributions (Gaussian, GMM, Gamma) and scheduling techniques (cosine, sigmoid) to assess generative performance using KL divergence and dynam…
Jupyter Notebook
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Goodreads-Fantasy-Subgenre-Classification
Goodreads-Fantasy-Subgenre-Classification PublicThis repository classifies Goodreads Fantasy book reviews into subgenres using advanced topic modeling techniques like NMF, LDA, and BERTopic. A dataset of 2M English-language reviews is analyzed, …
Python
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Robust-KCentroids-Clustering
Robust-KCentroids-Clustering PublicA comparative study of K-centroid clustering algorithms, including KMeans, CustomKMeans, Fermat-Weber KMedians, and Weiszfeld KMedians, highlighting their performance on separated and non-separated…
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