Junhyuk Lee

ARM CME · On-device AI · SW/HW Co-design & Evaluation

Junhyuk Lee

ARM CME · On-device AI · SW/HW Co-design & Evaluation

I currently focus on ARM CME, on-device AI software, and SW/HW co-design and evaluation. My experience at Samsung Electronics spans mobile NPU architecture and evaluation, AI frameworks, application processors, and multimedia optimization.

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Experience

Samsung Electronics

Principal Engineer

Mar 2023–Present

  • Mobile NPU architecture and evaluation, including work with AI frameworks.

Software Engineer

Aug 2019–Present

  • Mobile NPU model optimization and hardware analysis based on mobile use-case requirements.

Senior Software Engineer

Feb 2009–Present

  • Application processor system analysis and benchmarking using C/C++ and Python, including Neural Engine hardware IP and Qualcomm SNPE evaluation.
  • TensorFlow Mobile/Lite performance and power evaluation, on-device personalization, and participation in Samsung Mobile's MLPerf efforts.

Creative Lead

Aug 2018–Jul 2019 · Samsung C-Lab, Photo Teller

  • Led Photo Teller, using CNN, Word2Vec, and FastText, with TensorFlow/Keras for CNN/LSTM text generation on Android.

Technical Business Manager

May 2015–Jun 2017 · Samsung Electronics GmbH, Frankfurt

  • Coordinated with headquarters, supported carriers and B2B customers, and worked on local adaptation and technical workshops.

Software Engineer

Jun 2012–May 2015

  • Application processor solutions and wearable audio, including Yamaha Y831 bring-up.

Software Engineer

Feb 2009–Jun 2012

  • Tizen multimedia, Twitter, and instant messaging applications.

Expertise

  • C/C++
  • Python
  • Linux
  • TensorFlow / TensorFlow Lite
  • Keras
  • NPU architecture and evaluation
  • Audio codec / BSP
  • Arm FVP / AOSP bring-up

Credentials

  • Samsung SW Certification Pro
  • Data Science Level 2 · Sep 2024
  • OPIc AL · Jul 2017

Engineering Work

Arm FVP / Android Platform Bring-up

Investigated Android Open Source Project (AOSP) bring-up on Arm Fixed Virtual Platforms (FVP), tracing boot dependencies across kernel and init, APEX and linker namespaces, ART/JNI, framework services, and graphics. Documented startup and application-launch trace variability, including reproducibility factors such as runtime state, Binder activity, rendering, and scheduling.

  • Recorded a successful FVP boot milestone in May 2026; follow-up platform patches were still required.
  • Analyzed service-loading and graphics initialization failures while distinguishing observed progress from planned stabilization work.

Read the detailed FVP work record.

Selected Patents

I have filed 15+ patent applications. Selected publications and granted patents are listed below.

  1. Electronic device and operation method of electronic device for performing calculation using artificial intelligence model US20240202590A1 · Patent application publication
  2. Apparatus and method for determining a learning model for learning KR20240026050A · Patent application publication
  3. Electronic device and method of recognizing a force touch, by electronic device US11899884B2 · Granted patent document
  4. Electronic apparatus and controlling method thereof US11467642B2 · Granted patent document
  5. Electronic device and learning model determination method for learning of electronic device US20240077970A1 · Patent application publication
  6. Electronic device for processing neural network model and method of operating the same US20230072337A1 · Patent application publication
  7. Electronic device identifying force touch and method for operating the same US11874995B2 · Granted patent document
  8. Smart Alarm service using emoticon in instant messenger J2011-07-5800 · LinkedIn reference