Resume

Ph.D. in Physics & Astronomy – Johns Hopkins University (2018): Recognized with the Springer Thesis publication award for research on Higgs boson spin/parity measurements.
B.S. in Physics & Molecular Genetics – University of Rochester (2013): Dual degree; graduated magna cum laude and elected to Phi Beta Kappa.

Quantitative Researcher, JPMorgan Chase (2024–Present): Designing end-to-end analytical frameworks for mortgage-backed securities, including prepayment modeling; applying ML to optimize RMBS desk decisions (roles updated from LinkedIn).
Postdoctoral Researcher, UC Santa Barbara (2018–2024): Named Fermilab LPC Distinguished Researcher in 2024:contentReference[oaicite:6]{index=6}. Developed CMS-wide off-shell Higgs analyses tools, served as convener of the Off-shell, High Mass & Interference subgroup (2019–2021), and originated the Interpretations Task Force.
Graduate Researcher, Johns Hopkins University (2013–2018): Led simulation and data-analysis tool development for CMS Higgs boson measurements. Authored JHUGen/MELA and performed CMS tracker alignment calibration.
Undergraduate Researcher, Univ. of Rochester (2009–2013): Investigated neutrino flux measurement (Low-ν method) and conducted RNA biophysics experiments; tutored undergraduate physics.

Fermilab LHC Physics Center Distinguished Researcher, 2024
Springer Thesis Publication Award, JHU Physics (2018)
Provisional U.S. Patent (2025): RCNN-based surface-code decoding for quantum error correction

Co-author on Higgs boson property studies, including “New features in the JHU generator framework” (Phys. Rev. D 102, 056022 2020)
ORCID confirmed (0000-0002-1557-4424), with over 95K citations and h-index 156 on Google Scholar

Languages & Tools: C++, Python, Julia, SQL, Shell; PyTorch, TensorFlow, SciKit‑Learn; Qiskit, Cirq, Stim; NumPy, pandas, Matplotlib; Git, CI/CD
Domains: Statistical modeling, deep learning, quantum algorithm design, HPC, matrix-element simulations, quantum error correction
Languages: English, Turkish (native); German & Spanish (working proficiency)