Nova Linzai
Junior Analyst at Central Bank of Indonesia
West Java, Indonesia
Summary
🤩
Rockstar🎓
Top SchoolNova Linzai is a Junior Analyst with 11 years of professional experience blending finance, business strategy and hands-on technical work at the Central Bank of Indonesia. Currently completing an MBA in Finance, she applies quantitative rigor to policy and operational challenges while drawing on a background in geophysical engineering. Beyond analysis, Nova contributes to open-source ML projects—building and training lightweight, real-time face detection and tracking systems—demonstrating full-cycle machine learning skills from data and model training to deployment. Based in West Java, she pairs institutional experience with a curious, maker mindset (aptly summarized on GitHub as "Stay hungry") and a track record of practical problem-solving across banking, telecoms and energy internships.
10 years of coding experience
Master of Business Administration - MBA, Finance, General, Master of Business Administration - MBA, Finance, General at Institut Teknologi BandungBachelor’s Degree, Geophysical Engineering, Bachelor’s Degree, Geophysical Engineering at Institut Teknologi Sepuluh November
English, Indonesian
Github Skills (14)
object-tracking10
face-detection10
computer-vision10
pytorch10
opencv10
inference10
trainings10
tensorflow10
python10
modeling10
image-processing10
machine-learning9
deep-learning9
ncnn9
Programming languages (5)
Github contributions (5)
Linzaer/Face-Track-Detect-Extract
Aug 2018 - Jun 2019
💎 Detect , track and extract the optimal face in multi-target faces (exclude side face and select the optimal face).
Role in this project:
ML Engineer
ML EngineerContributions:51 commits, 2 PRs, 43 pushes in 9 months
Contributions summary:Nova primarily contributed to the development of a face detection, tracking, and extraction system. Their work included implementing and modifying core components related to face detection using MTCNN (Multi-task Cascaded Convolutional Networks) and facial landmark detection. The user also integrated the SORT (Simple Online and Realtime Tracking) algorithm for object tracking and added enhancements for improved video analysis. Further improvements included code optimization, bug fixes, and adjustments to parameters like thresholds and scaling factors.
face-recognitioncomputer-visiondetectmulti-targeteye-tracking
Linzaer/Ultra-Light-Fast-Generic-Face-Detector-1MB
Oct 2019 - Feb 2022
💎1MB lightweight face detection model (1MB轻量级人脸检测模型)
Role in this project:ML Engineer
ML EngineerContributions:159 commits, 17 PRs, 139 pushes in 2 years 4 months
Contributions summary:Nova's commits primarily focus on training a face detection model within the context of the repository's lightweight face detection model. The user is updating the training code, including the dataset loading, model architecture, loss function, and optimization parameters. Additionally, the user has modified detection scripts to use the trained models. The contributions showcase the user's involvement in the entire machine learning pipeline, from training to deployment and testing.
ncnnface-recognitioninferencemnnface-detection
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