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Academic Credentials
  • Ph.D., Subatomic & Astroparticles Physics, Universite Grenoble Alpes, 2016
  • M.Eng., Fundamental Physics and Nanoscience, Grenoble INP Phelma, 2013
  • M.S., Quantum Fields & Fundamental Forces, Imperial College London, UK, 2013
Academic Appointments
  • Marie SkÅ‚odowska-Curie Fellowship
  • King’s College of London (UK) / University of Tokyo, Kavli IPMU (Japan)
Professional Honors
  • ICRR Inter-University Research Program
  • Kashiwa (University of Tokyo, Kavli IPMU (Japan)
  • Hyper-Kamiokande OD PMTs QA, Â¥450 000,00, and Â¥100 000,00 for 2022
  • Marie SkÅ‚odowska-Curie Fellowship
  • King’s College of London (UK) / University of Tokyo, Kavli IPMU (Japan)
  • EUR279 228,48
Professional Affiliations
  • American Physical Society, Member
  • Institute of Physics, Member

Dr. Zsoldos specializes in building data-driven applications using physics-based machine learning, computer vision, and advanced data analytics. With expertise spanning scalable data architectures, data cleaning, statistical analysis, and dashboard creation, he effectively transforms complex datasets into actionable insights. He integrates state-of-the-art AI techniques with physics-driven methods across industries including mining, finance, and radiation safety. In mining, Dr. Zsoldos developed geological mapping solutions utilizing deep learning and remote muon imaging via raytracing to precisely identify geological features such as shafts and mineral density variations. In finance, his quantum-inspired modeling accurately quantifies volatility risks surrounding market events, aiding informed investment decisions. On the experimental and hardware side, Dr. Zsoldos has significant experience in radiation and nuclear physics, including precision dosimetry, shielding design, ionizing medical devices, and Monte Carlo simulations of radiation-material interactions. He also provides rigorous optical device characterization supported by computational modeling and precise measurements, consistently delivering impactful solutions tailored to client needs. 

Dr. Zsoldos was a Marie Curie Fellow in Particle Physics at King's College London and the Kavli Institute for Physics and Mathematics of the Universe at the University of Tokyo. His doctoral research focused on detecting and characterizing cosmic-ray muons in large neutrino detectors located deep underground. He has extensive programming experience in multiple languages including C/C++, Fortran, Python, R, Julia, Java, Kotlin, Go, JavaScript, and Matlab, as well as expertise with ML frameworks such as TensorFlow, PyTorch, and JAX, and Bayesian analysis frameworks including Stan, PyMC, and TensorFlow Probability.