Zhachary B.
Senior Physics Data Scientist & Experimental Lead
Experience
Senior Physics Data Scientist & Experimental Lead
Google DeepMind
- Directed a 15-member global team in curating 500,000+ high-fidelity simulated and real-world datasets for quantum many-body systems and HEP models, achieving 98% inter-annotator precision.
- Engineered Python-based automation pipelines with NumPy, SciPy, and Pandas, reducing manual data handling by 40% in collider and cosmic ray workflows.
- Oversaw cosmic ray muon tracking and LHC event classification for dark matter and beyond-Standard-Model searches.
- Led waveform annotation and matched filtering for LIGO/Virgo gravitational wave transients across multi-detector networks.
- Integrated CERN ROOT and Open Data Portal with custom 3D reconstruction tools for neutrino interaction modeling.
Computational Physicist
Fermilab National Accelerator Laboratory
- Managed curation of 150+ TB of proton-proton collision data, implementing track reconstruction and calorimeter clustering for CMS and DUNE.
- Designed statistically robust QA protocols using scikit-learn and ROOT macros, ensuring sub-percent alignment between data and Monte Carlo.
- Enhanced GEANT4 simulation suite for liquid argon TPC response, contributing core modules to the DUNE software stack.
- Mentored early-career scientists in CMB foreground subtraction and GW transient detection, boosting analysis throughput by 30%.
Graduate Research Assistant
University of Michigan Particle Physics Group
- Processed 80,000+ MadGraph/Pythia events for jet substructure and MET-based new physics searches.
- Built real-time C++/Python event taggers deployed in CMS Tier-2 computing clusters.
- Pioneered ML-assisted anomaly detection in xenon-based dark matter detectors using early graph neural networks.
- Prototyped end-to-end track reconstruction with PyTorch Geometric, reducing fake rate by 25%.
Summary
Visionary Physics Ph.D. candidate with over 5 years of high-impact experience leading experimental data pipelines, Monte Carlo simulations, and detector-grade event reconstruction at the frontier of particle physics and cosmology. Proven track record of curating petabyte-scale datasets for LHC, neutrino, and gravitational wave observatories using ROOT, GEANT4, and PyTorch. Spearheaded automation initiatives that slashed processing time by 40% and elevated data fidelity to 98% agreement across distributed teams. Passionate about translating raw detector signals into groundbreaking discoveriesseeking to drive next-generation physics at CERN, Fermilab, LIGO, or a leading research institute.
Languages
Education
University of Michigan
Physics · Ann Arbor, United States
University of Michigan
M.S. · Physics · Ann Arbor, United States
Missouri University of Science and Technology
B.S. · Physics · Rolla, United States · 3.8/4.0
Certifications & licenses
AWS Certified Machine Learning Specialty
Google Professional Data Engineer
Certified Scrum Master
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