Summary
Sol Benkel is a PhD student and multidisciplinary researcher based in Berlin with 9 years of experience blending experimental physics, data science, and software engineering. Holder of MSc degrees in both Physics and Computer Engineering, he has built production-grade HEP analysis and detector alignment software, optimized reconstruction algorithms, and deployed ML-driven solutions for particle and astrophysics projects. His recent work includes neural-network online reconstruction for an EIC dRICH detector and Bayesian regression for RR Lyrae labeling, alongside teaching and open-source contributions to CLAS12 toolsets. Equally comfortable in C, C++, Java, and Python, he has a track record of shipping applied research—ranging from EPICS slow controls and ventilator R&D during COVID to blockchain and IoT integrations—that reveals a talent for translating academic methods into resilient, real-world systems.
9 years of coding experience
1 year of employment as a software developer
IBM Professional Certificate in Machine Learning, Computer Science, IBM Professional Certificate in Machine Learning, Computer Science at Coursera
Master's degree, Physics, Master's degree, Physics at Universidad Técnica Federico Santa María
English, Spanish, Norwegian, Chinese, Italian