
I'm Sadx
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Vision-algos
February 2, 2026 – Present
A collection of computer vision algorithms and experiments.
View ProjectPhotometric-Stereo
January 15, 2026 – Present
A Repository for Understanding the Concepts of Photometric Stereo In Depth
View ProjectFourier-Transforms
January 3, 2026 – Present
My learnings/projects related to Fourier transforms..
View ProjectRobot-Kinematics
October 26, 2025 – November 21, 2025
Project repository for robotic arm kinematics, including code, math, and resources.
View ProjectAutonomousCar-v1
August 3, 2024 – March 15, 2025
Autonomous car powered by the Raspberry Pi with image processing (OpenCV)
View ProjectStereoVision
June 17, 2024 – Present
Calibration and Depth Map Generation for Active and Passive Stereo Vision Systems.
View Projectpetrol_indicator_server
April 9, 2024 – April 15, 2024
petrol_indicator_server — GitHub repository
View ProjectSimple-Arduino
December 23, 2023 – May 24, 2024
This repository consists of simple projects for getting started with Arduino.
View ProjectBoar-Hunting-YOLOv8
November 2, 2023 – November 12, 2023
YoloV8-based boar detection system with Arduino-triggered buzzer for enhanced security.
View ProjectCultural Fit Analysis
The candidate's projects are all personal and demonstrate a strong interest in robotics, computer vision, and embedded systems. While these areas align with data science in terms of analytical and algorithmic thinking, the direct application to typical data science problems (e.g., predictive modeling, statistical analysis, large-scale data processing) is not explicitly shown. The candidate's experience level is 0, indicating a lack of professional experience, which impacts cultural fit for a senior role. The diversity of projects is good within the computer vision/robotics domain, but lacks breadth in other data science sub-fields. Therefore, cultural fit is scored low due to the absence of professional experience and direct alignment with typical data science roles.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise and technically focused, but there is no information on collaboration, problem-solving approaches, or communication style in a team setting.