Daniele Paliotta is a machine learning researcher and software engineer with a decade of hands-on experience combining academic research and industry R&D. Currently a PhD student in Machine Learning at the University of Geneva, he bridges neuroscience, brain-computer interfaces and ML through his doctoral work and research assistantship. He has contributed to both startups and research labs—roles at Together AI and Cartesia complement academic projects like the ATLAS Collaboration—bringing practical ML engineering to experimental domains. His background spans end-to-end software development and applied research, from internships at TrueLayer to freelance engineering engagements in Italy. Based in Geneva, he is comfortable moving between prototype research and production-focused ML systems, with an unusual mix of particle-physics collaboration experience and BCI specialization. Colleagues describe him as someone who turns interdisciplinary curiosity into reproducible experiments and deployable models.
11 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at University of Geneva
School of AI, School of AI at Pi School
Computer Engineering, Computer Engineering at Sapienza Università di Roma
Master's degree Computer Engineering/Data Science, Master's degree Computer Engineering/Data Science at Politecnico di Torino
Contributions:1 PR, 58 pushes, 2 branches in 7 months
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