Western Digital (WD) -- Staff Data & ML Engineer
San Jose, CA (2025-Present)
Building ML/Statistical models and Agentic AI systems for hard drive engineering teams. Current directions: agentic AI for code translation and large scale data analysis. ML for hard drive manufacturing, from modeling to deployment and monitoring systems. Model construction for hard drive reliability/smear height prediction using large telemetry data.
Baylor College of Medicine -- ML Engineer in Radiation Oncology (Postdoc)
Houston, TX (2025)
Radiation oncology, brain cancer treatment: AI-assisted therapy (clinic-based).
Seagate Technology -- GenAI Plasmonic Design for Nano-Antenna (Intern)
Bloomington, MN (later remote) (2024-Dec 2024)
Developed an AI-powered pipeline for plasmonic NFT design, generating 2000+/h optimized structures - automating a process that traditionally requires years of expertise. Reducing it from 2 weeks to 18 hours. Work published in IEEE Transactions on Magnetics journal.
The University of Texas at Austin (UT Austin) -- Research Assistant in Semiconductors
Austin, TX (2022-2024)
Research assistant: Developed energy-efficient neuromorphic device using magnetic skyrmions: achieved 99.98% energy reduction (0.1 fJ vs. 40,000 fJ in domain wall MTJ) and ~98% faster updates (~1 ns vs. 62.5 ns in skyrmion creation). Applied advanced programming skills in Python/Mumax3/ML on TACC HPC for device modeling and data generation.
National Institute of Standards and Technology (NIST) -- Guest Researcher
Boulder, CO (Summer 2021)
Nanoscale Spin Dynamics group under Dr. Thomas J. Silva. Research on hopfion dynamics and resonant spin behavior in chiral magnets.
Seagate Technology -- ML Device Physics Modeling (Intern)
Longmont, CO (Summer 2022)
Storage team, led ML research on HAMR magnetization patterns: developed DNN achieving 90% faster parameter extraction and efficient magnetic domain image generation via GANs.
Oklahoma State University -- Research Assistant in Semiconductor Fabrication
Stillwater, OK (2019-2022)
Developed next-gen neuromorphic computing, achieving ~70% cost reduction via prob. signal decorrelation vs. conventional methods. Demonstrated strong problem-solving skills in Hall bar fab using Photolithography and LabVIEW for device testing (paper published).
Summer 2021: visited National Institute of Standards and Technology (NIST) as an International Associate. Joined Nanoscale Spin Dynamics Group, performing 500+ MuMax3 simulations, achieving 95% skyrmion detection accuracy with custom Python script.
National Science Foundation (NSF) -- NSF Scholar for Startup Idea
Stillwater, OK (2020-2021)
Led startup commercializing research on energy-efficient data storage. Won 3 competitions, secured grant for market research (70 interviews).
Gohm Electronics -- ML Research Engineer
Istanbul, TR (2018-2019)
ML for wireless network authentication and physical layer security: Built device fingerprinting system using SVM, KNN, and custom CNNs on spectrograms. Achieved 99% accuracy on IoT sensor identification. Method commercialized by GOHM for vehicle localization and data protection. Published at ELECO 2018.