Supervision
- PhD Thesis: (ongoing)
- Advisors: Z. Papandreou, C. Fanelli
- Topics: Deep learning for deep inelastic scattering; machine learning for clusters reconstruction in calorimeters
- Current position: PhD student, University of Regina
- PhD Thesis: (year 2022, to be defended)
- Advisors: Z. Papandreou, C. Fanelli
- Topic: working on spectroscopy for GlueX and AI-assisted design for EIC
- Current position: PhD student, University of Regina
- Publications: AI-assisted Optimization of the ECCE Tracking System at the Electron Ion Collider, C. Fanelli, Z. Papandreou, K. Suresh, et al., arXiv.2205.09185, accepted in Nuclear Instruments and Methods in Physics Research
- MSc Thesis: (year 2022/2023, to be defended)
- Topic: Machine Learning for PID of electromagnetic showers at JEF experiment
- Advisors: Z. Papandreou, C. Fanelli
- Current position: MSc student, Univesrity of Regina
- Publication: “Artificial Intelligence for Imaging Cherenkov Detectors at the EIC.” C. Fanelli and A. Mahmood 2022 JINST 17 C07011
- BSc Thesis: (year 2021, defended): A Novel Multi-Purpose Variational Clustering Architecture Applied to Neutron ID within the GlueX BCAL
- Advisors: Z. Papandreou, C. Fanelli
- Forthcoming position: PhD, Data Science, W&M
- Completing: U. Ottawa, MSc. Applied AI
- Publication: C. Fanelli, J. Giroux, and Z. Papandreou. “Flux+ Mutability: A Conditional Generative Approach to One-Class Classification and Anomaly Detection.” IOP, Machine Learning: Science and Technology (2022)
- BSc Thesis: (year 2020, defended) Porosity Optimization in Nanoporous materials via Machine Learning [link]
- Advisors: G. Romano, C. Fanelli
- Current position: Industry
Undergraduate Research Projects
