Geri Skenderi
I am a member of technical staff at HASH and a founding researcher within the company's AI lab. My current research is centered around foundational graph deep learning.
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Research Interests
My main research interests sit at the intersection of AI and geometry. I like to think about how Neural Networks, in particular Graph Neural Networks, learn under geometric and structural constraints. Additionally, I am interested in using geometrically principled methods to build more effective Neural Networks, mostly for graph representation learning.
Background
Previously, I was a Postdoctoral Researcher at the Bocconi Institute for Data Science and Analytics, advised by Prof. Carlo Lucibello. During my stay there I was affiliated with the Statistical Physics & Machine Learning group, where I worked on theoretically understanding and also benchmarking neural boolean satisfiability solvers.
I did my PhD in Computer Science at the University of Verona under the supervision of Prof. Marco Cristani. I also had the privilege of being a J1 visiting scholar at the DSE Lab of Michigan State University, headed by Prof. Jiliang Tang.
Beyond research
I love reading and studying technical material, in particular physics, mathematics, and philosophy. I feel an equal amount of love for music and thus I try to produce my own. Finally, I was a student-athlete during my studies and played basketball during those years, thus I find sports and physical activity extremely enjoyable.