Jake Uribe

GPA: 3.6/4.0

Coursework: Advanced Quantum Computing (PHYS 779), Quantum Computing Laboratory (PHYS 707), Optics (PHYS 625), Electrodynamics (PHYS 721), Quantum Field Theory (PHYS 831)

GPA: 3.259

Coursework:Discrete Mathematics, Numerical Linear Algebra, Circuits & Electronics, Atomic & Quantum Physics

University of Wisconsin-Madison — Saffman SNAQ Lab

• Developed and maintained hardware control tooling in Python using the ARTIQ quantum OS; designed and documented internal APIs
• Built automated data pipelines for experimental parameter extraction (trap depth, loading rate, single-atom fidelity), replacing manual workflows and enabling systematic benchmarking
• Automated polarization drift correction in SM fiber optics via Python feedback loop reading analog photodiode data through NI DAQ
• Designed electromagnetic field simulations at 6.8 GHz in COMSOL; used pyLCP for hardware-aware validation of trap geometry configurations
• Built Rubidium trapping experiment almost entirely from scratch (electronics, frequency matching, UHV hardware, atom trapping, beam characterization)

University of Wisconsin-Madison — Yavuz Lab

• Developing analytic solutions for different superradiant systems in neutral-atom ensembles; modeled collective decay in multi-atom systems, finding compressed representations that permit efficient solutions for subsets of states
• Designing the next phase of the simulation pipeline with tensor-network methods on GPU-capable libraries (PyTorch, JAX, Quimb) to enable simulation of larger atom ensembles
• Transforming research prototypes into structured Python library code: building a package for Pauli String Hamiltonian summation and exponentiation within the ZXW Calculus framework with version.

Brookfield, WI

• Developed production backend infrastructure for client applications in C# and SQL, conforming to code review and style requirements
• Managed CI/CD pipelines and cloud resource deployment using Azure DevOps, Azure Resource Manager, and Azure Data Factory
• Conducted QA testing with structured test plans; compiled release documentation for production deployment

• Built a custom FDM solver to simulate the Stern-Gerlach effect; validated against historical experimental data
• Optimized particle propagation using Monte Carlo simulation with Boltzmann velocity distribution, processing ~19,000 trajectories

• Implemented dissipative encoder for the Toric Code using the Lindblad master equation in QuTiP; benchmarked logical fidelity under error mitigation protocols (>99% noise-free)
• Characterized robustness against parameter errors (±15%); achieved ~92% singlet-state preparation fidelity

• Full-stack local-first research tool with AI-assisted paper discovery, tagging, and semantic visualization
• MCP server enabling LLM-native access to the entire research database