I am an Experimental Physicist and Data Scientist focused on data analysis and Machine Learning with more than 20 years of experience in quantitative research, international collaboration and scientific leadership.
I received my PhD in Experimental Physics from the University of Bonn and continued research at George Washington University and the University of Mainz. My work has included large scale data analysis, complex simulations, development of new experimental and analysis methods, as well as Machine Learning methods for event identification in experiments at electron accelerators. These projects required solving non-trivial experimental and quantitative problems, extracting information from multidimensional data, comparing models and simulations, and validating results against independent evidence. One example is first author experimental work which, together with analyses by the BnGa Partial Wave Analysis Group, contributed to resonance properties later used by the Particle Data Group as primary references.
Within international collaborations, I have taken on responsibilities including scientific referee, experimental run coordinator, hardware coordinator and interim spokesperson. I also have broad experience in teaching and supervising scientific staff, undergraduate and PhD students. I have initiated and led competitively funded projects with more than €300k in total funding, including a postdoctoral fellowship from the Carl Zeiss Foundation, research funding at the University of Mainz and a postgraduate fellowship at the University of Gießen. These activities covered scientific concept development, experimental strategy, uncertainty assessment and validation, resulting in publications in high-tier peer-reviewed journals.
In recent years, I have increasingly transferred this approach to Machine Learning and real world Data Science. This includes work in the Multimodal AI and System Integration group at the Institute of Information Systems at Hof University, as well as Machine Learning and Data Science methods for entity resolution and record linkage. My broader technical profile includes Scientific ML, Deep Learning, Multimodal AI, Machine Learning in Physics, Medical and Biomedical AI, and Computational Biology.
Selected scientific and Machine Learning projects:
https://vsokhoyan.github.io/selected_scientific_projects/
I have authored or coauthored more than 60 peer-reviewed publications, with more than 2,600 citations and an h-index of 31 on Google Scholar:
https://scholar.google.com/citations?user=7leLPVMAAAAJ
