Hi there, Iām @LucaNyckees.
I am currently working on my Master's thesis (supervised by Prof. Kathryn Hess and Nicolas Berkouk) in the field of topological data analysis - we use topological optimization machine learning to tackle problems encountered in multi-persistent homology. I am interested in applications of topology to machine learning, data analysis and computational neurosciences. Along with my studies, I've been working on projects and internships within the Laboratory of Topology and Neuroscience at EPFL.
More generally speaking, I really enjoy addressing real-world problems through various types of data analysis - with an emphasis on both data visualization (e.g. interactive visualization with web applications) and on the adapted geometric framework(s) (what mathematical tools are best fit to the task?). I am interested in creating strong and task-specific coding pipelines that combine the fundamentals of machine learning and data visualization.
- key-interests : statistical and topological data analysis, optimization machine learning, computational geometry
- Python tools : pytorch, tensorflow, streamlit, networkx, pyvis, pandas, pyspark, numpy, plotly, matplotlib, NLTK