Phong Nguyen Ha

Data Scientist

https://www.opentalent.in/phong-nguyen-ha

PhD

University of Oulu

Key Strengths

Extensive experience in computer vision and 3D reconstruction, evidenced by numerous personal projects like lightDenseYOLO, RGBDNet, and semanticNERF.
Proficiency in Python, C++, and CUDA, essential for high-performance data science and machine learning tasks.
Demonstrated ability to work on complex, research-oriented projects, including those published at conferences (e.g., 3DV 2021 for RGBDNet).
Strong background in deep learning architectures for object detection, novel view synthesis, and depth estimation.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong focus on academic and research-oriented computer vision tasks, which aligns well with roles requiring innovation and problem-solving. However, the lack of diverse project types (e.g., industry applications, team projects) makes a comprehensive cultural fit assessment challenging. The current role as 'Data Scientist' at a university suggests an academic or research-driven environment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's profile primarily highlights technical project work.

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Projects

Fisheye-GSv2

November 19, 2024 – November 23, 2024

Fisheye-GSv2 — GitHub repository

View Project

hierarchical-3d-gaussiansv2

November 19, 2024 – November 23, 2024

hierarchical-3d-gaussiansv2 — GitHub repository

View Project

EmerNerfv2

November 19, 2024 – November 23, 2024

EmerNerfv2 — GitHub repository

View Project

GaussianOcc_modifyv2

November 18, 2024 – November 23, 2024

GaussianOcc_modifyv2 — GitHub repository

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Rendering-360-degree-view-with-few-input-views-by-PixelSplat

June 15, 2024 – June 15, 2024

Rendering-360-degree-view-with-few-input-views-by-PixelSplat — GitHub repository

View Project

Rendering-360-degree-view-with-few-input-views-by-UniDepth-Universal-Monocular-Metric-Depth-Estimat

June 15, 2024 – June 15, 2024

generate point cloud from depth map by Unidepth model and project in image plane

View Project

RGBDNet

January 11, 2022 – January 26, 2022

[3DV 2021] We propose a new cascaded architecture for novel view synthesis, called RGBD-Net, which consists of two core components: a hierarchical depth regression network and a depth-aware generator network.

View Project

semanticNERF

February 17, 2021 – December 6, 2021

semanticNERF — GitHub repository

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lightDenseYOLO

June 15, 2018 – June 15, 2018

A real-time object detection app based on lightDenseYOLO Our lightDenseYOLO is the combination of two components: lightDenseNet as the CNN feature extractor and YOLO v2 as the detection module

View Project

Edge-Based-TM

January 11, 2017 – January 11, 2017

Edge-Based-TM — GitHub repository

View Project

Key Strengths

Extensive experience in computer vision and 3D reconstruction, evidenced by numerous personal projects like lightDenseYOLO, RGBDNet, and semanticNERF.
Proficiency in Python, C++, and CUDA, essential for high-performance data science and machine learning tasks.
Demonstrated ability to work on complex, research-oriented projects, including those published at conferences (e.g., 3DV 2021 for RGBDNet).
Strong background in deep learning architectures for object detection, novel view synthesis, and depth estimation.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's profile primarily highlights technical project work.

Phong Nguyen Ha

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit