Qualcomm logo
June 2026 – September 2026

Qualcomm

Position Engineer, Location Tech · Internship

Santa Clara, California

Work in location technology focused on multi-sensor positioning and the characterization of sensing errors for mobile and extended-reality applications.

  • Sensor fusion between visual-inertial odometry (VIO), IMU, and GNSS measurements.
  • Sensor noise and error characterization for positioning-system evaluation.
  • Analysis of relative and absolute sensing behavior, including drift and degraded-condition performance.

Public-facing summary only; proprietary implementation details are intentionally omitted.

Samsung logo
May 2023 – August 2023

Samsung Semiconductor

SoC Location System Engineer, Connectivity Lab · Internship

San Jose, California

Developed and evaluated oscillator phase-noise models for GNSS receiver simulation, with emphasis on how TCXO behavior affects acquisition and tracking performance.

  • Performed simulation studies on the impact of TCXO phase noise on GNSS signal quality, acquisition, and tracking-loop stability.
  • Built a parameterized phase-noise generator for both MATLAB simulation and a C++ hardware-aligned simulation model.
  • Integrated the TCXO/phase-noise model into a GNSS signal simulator for candidate crystal evaluation.
Micron Technology logo
May 2022 – September 2022

Micron Technology

Dry Etch Process Development Engineer · Internship

Boise, Idaho

Worked on semiconductor dry-etch process development for memory-device structures, combining process experimentation, data analysis, and cross-functional engineering collaboration.

  • Contributed to DRAM/HRAM dry-etch process development, with focus on word-line metal etch processes across multiple structures.
  • Applied machine learning to estimate material etch rate from metal blanket-etch studies.
  • Collaborated with CVD, metrology, and wet-process teams on vehicle design, testing, and process characterization.

Project details are kept at a high level because the work involved company IP and process-development information.

Technical Thread

Although these internships span different application domains, they share a common engineering theme: building models from physical systems, characterizing uncertainty and failure modes, and using simulation or experimental data to improve system-level performance.

That perspective carries directly into my current work in radar remote sensing and navigation, where calibrated sensing, error modeling, signal processing, and robust estimation are central to turning measurements into useful products.