For years I enjoyed a fruitful and edifying academic career. My research was focused on various aspects of Algorithms, Machine Learning and Data Science. My last position was as a Lecturer (Assistant Professor) of Computer Science at Queen Mary University of London.

Currently I am working in industry. I am enjoying the process of putting my theoretical knowledge to the test in practical, “real-world” problems. However, I try to remain active in research by staying in touch with my fellow academics and through personal projects.

An overview of my research:

• Graph Mining: I am interested in problems motivated by social networks, such as community detection, polarization and opinion formation. I tend to like spectral approaches. NeurIPS ‘20, WWW ‘20, WWW ‘20, CIKM ‘19.

• Approximation Algorithms: Recently, I have focused on constrained clustering, motivated by applications of algorithmic fairness and representation quotas. KDD ‘22, ECML-PKDD ‘21, DAMI ‘22, WWW ‘19.

• Matrix Approximations. I also focus on problems involving sampling and dimensionality reduction, and combinatorial optimization with a linear-algebraic flavor. ICML ‘22, WWW ‘21, Info. Sci. ‘19, ICDM ‘16.

• Machine Learning. I have done work on areas of machine learning, such as kernel methods and deep learning applications. ECML-PKDD ‘20, PLOS one ‘18.

I also like to write efficient Python code for fast prototyping and experimentation.

Don’t hesitate to send me an e-mail if you want to work with me or discuss any of my works.