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Robotics | Computer Vision | Deep Learning | Sensor Fusion | ROS
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livecell-segmentation-U-Net
December 8, 2024 – December 17, 2024
livecell-segmentation-U-Net — GitHub repository
View Projectbottle_detection_synthetic_data
July 15, 2024 – July 22, 2024
bottle_detection_synthetic_data — GitHub repository
View ProjectMachine-Learning-by-Coursera
July 4, 2022 – July 4, 2022
This repo is of my submissions for all the course assignments of Machine Learning by Stanford course on Coursera ( https://www.coursera.org/specializations/machine-learning-introduction? )
View ProjectComputer-vision-notebooks
July 2, 2022 – July 4, 2022
Python notebooks implementing various CV models
View ProjectLIDAR-Obstacle-Detection-Sensor-Fusion-Udacity-Program
May 4, 2020 – May 4, 2020
Obstacle Detection, using PCL library fuctions, to detect objects in a point cloud data from a LIDAR mounted on a Self-Driving Car.
View ProjectRGB-D-Fusion-For-Real-Time-Detection
December 6, 2019 – December 8, 2019
Final Project for Visual Learning and Recognition
View ProjectENPM673-P5-Visual-Odometry
September 24, 2019 – September 24, 2019
Estimated camera pose by calculating Essential and Fundamental Matrix using 8-point algorithms through RANSAC. And the plotted the camera coordinates in world frame to estimate optimal pose of the camera.
View ProjectENPM661-P5_Easy-Shopper-i.e.-Path-Planning-for-Shopping-Robot
September 13, 2019 – September 13, 2019
This project represents a novel method to calculate the path. It is a combination of A* and dynamic A* which is implemented on the common task of the shopping cart. Please review the PDF for more info.
View ProjectENPM661-P3-Implementation-of-A-star-algorithm-on-Turtlebot
September 8, 2019 – June 24, 2022
This project involves navigating a differential drive robot (TurtleBot 2) in a virtual environment from a given start point to a given goal point, with simulation carried out on V-REP
View ProjectGeometric-Tracking-Control-of-a-Quadrotor-UAV
July 31, 2019 – July 31, 2019
It is a known fact that quadrotor UAVs are in general under-actuated and nonlinear system and it is a challenge to control them, especially in case of aggressive maneuvers. Our goal in this project is to study the nonlinear geometric control approach to control a quadrotor. The configuration of the quadrotor system described on smooth nonlinear geometric configuration spaces has been briefly discussed, and analyzed with the principles of differential geometry. This allows us to avoid any kind of singularities that would otherwise arise on local charts.
View ProjectCultural Fit Analysis
The candidate demonstrates a strong interest in robotics, computer vision, and machine learning through a variety of personal projects. This aligns well with a data scientist role, particularly one focused on computer vision or robotics applications. The breadth of projects suggests a proactive and self-driven learning attitude. However, the lack of professional experience or team projects makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving orientation and an ability to apply theoretical concepts to practical scenarios. However, without specific psychometric test results or interview data, it is difficult to assess soft skills like teamwork, stress handling, or communication clarity in a professional setting.