Always Learning!

Results-driven junior control systems engineer transitioning into a computer vision engineer role with 2 years of experience in the automotive industry. Seeking to use Python and AI-related libraries to solve accessibility-related social issues.

  • Fast Lane Detection in CARLA using BiSeNet V2

    ● Built an improved model in inference speed from my previous lane detection model using UNet architecture in CARLA datasets. ● Utilized BiSeNet V2 as the backbone of architecture; the focal loss function for semantic segmentation loss and the discriminative loss for instance segmentation loss. ● Implemented in Python using the TensorFlow and Keras libraries ● Was able to achieve mean IoU at around 78% with an inference speed of 73 fps, as opposed to the previous implementation of 50% mean IoU with 15.8 fps of inference speed.

  • Sign Language Recognition using I3D in WLASL Dataset

    ● Built sign language recognition in TensorFlow and Keras utilizing I3D architecture with the inputs of RGB and optical flow. ● Trained the model with the pre-trained weights on Kinetics. This resulted in 65.7% of top-1 accuracy


In the future

I would like to utilize my abilities and experience in the past such as Python, TensorFlow, ROS, etc, in a working environment to improve efficiencies such as programming related to AI technology and autonomous driving technology.

CBSテクノ3 years



Control System Engineer (Dispatch Employee of CBS Techno, Ltd.) at Subaru, Ltd., Ota July 2020 — February 2021 Vehicle Communication Controller Team, Electronic Controller Development Division

Bandung Institute of Technology (ITB)5 years

Electrical Power Engineering


GPA: 3.21 of 4.00 Thesis Title: Study of Regenerative Braking as A Substitute to Frictional Braking System

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