Isaiah Murray

(781) 558-3863 | isaiah.j.murray@gmail.com | linkedin.com/in/isa-murray | isaiah-murray.com | github.com/IsaiahJMurray

Sophomore, Class of 2029 · U.S. Citizen · Embedded systems, instrumentation, and perception for physical hardware

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Experience

Formlabs — Electrical Engineering Intern, SLS & Materials R&D

Mar 2026 – Aug 2026 Somerville, MA
  • Built end-to-end powder-bed defect detection pipeline — GPU-accelerated classical CV region proposal feeding a ResNet-18 classifier over a nine-class taxonomy — replacing a binary detector with classified, severity-ranked results; surfaced order-of-magnitude defect-rate differences between machines running identical material.
  • Designed fleet-wide heater fault detection from first-principles physics after establishing no labeled fault data existed; root-caused a 9% false-positive rate to PWM phase jitter between hardware channels and restructured the check to 0% on healthy fleet data — caught a wiring fault on a unit 12h from shipping to a beta customer.
  • Replaced a manual filter-swap characterization procedure with a controlled-evaporation sweep producing a continuous pressure–flow surface in one run; built the resulting virtual flow sensor and validated it closed-loop against an independent sensor outside the control loop.
  • Built in-situ dielectric cure monitoring rig (PyQt6, VISA impedance analyzer, SSH-triggered exposure); identified cross-machine timing as the data-quality limit and added a dedicated fire-time recorder, enabling ~40 Hz transient capture across 300+ runs. Correlated ionic viscosity with FTIR, enabling FTIR emulation at ~300 Hz.
  • Built browser-native lifetime test runner (acoustic cycle detection, crash-safe resumable state, automatic Word/PDF report generation) and ran five qualification campaigns — longest logged 515 insertion cycles.

Cherish Health — Engineering Team

2024–2025 Cambridge, MA
  • Automated phased-array radar calibration; replaced manual gain/phase tuning with an FPGA-controlled workflow using spectrum analysis and algorithmic optimization, cutting calibration from hours to minutes and reducing side lobe interference 20% (TX) / 30% (RX).
  • Built internal tooling for storing and comparing radar characterization data; accelerated state annotation throughput.
  • Sourced alternative LED supplier and coordinated contractors for molded fiber packaging, reducing BOM cost by 5%.
  • CAM'ed and manufactured injection-molded and machined components.

MIT Chem-E — Strano Group, Laboratory Assistant

May 2023 – Aug 2023 Cambridge, MA
  • Selected for MIT's HIP-SAT summer research program (Strano Lab); investigated graphene nanostructure additives in octadecane-based phase change materials to improve thermal conductivity and raise thermal resonator output voltage.
  • Presented findings at HIP-SAT Symposium and Boston Mammalian Synthetic Biology Symposium.

Cherish Health — ML Intern

2022–2023 Cambridge, MA
  • Trained detection models and built data collection tooling in Python/TensorFlow.
  • Ran technical demos for CEO and CTO supporting a successful Series A round.

Additional Experience

Access Sport America — Coach

2024–2025 Dorchester, MA

Adaptive watersports programming for athletes with disabilities; specialized in nonverbal autism support.

Center for Student Coastal Research — Student Researcher

2016–2022 Cohasset, MA

Won Marjot grant to study Zostera marina; built automated environment chamber testing recovery in Labyrinthula zosterae-infected specimens.