
MS (Computer Science), UC San Diego; Code Reviewer and Mentor @udacity; Former Data Scientist
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Lane-Detector-Node
June 14, 2019 – February 22, 2023
ROS Node for performing Lane Detection based on Lanenet/SCNN models
View Projectros-realtime-image-stitching
June 9, 2019 – February 22, 2023
ROS Node to perform realtime Image Stitching for synchronized/unsynchronized cameras
View ProjectDetect-and-Track
November 27, 2018 – December 9, 2018
Detection using Deep Learning and Tracking using Kalman Filter
View ProjectConvESN
November 16, 2017 – March 13, 2018
Implementation of Convolutional Echo State Network for Human Activity Recognition
View ProjectSemantic-Image-Segmentation
November 1, 2017 – October 18, 2018
Label the pixels of a road in images using a Fully Convolutional Network (FCN)
View ProjectPID-Control-For-Autonomous-Driving
June 25, 2017 – March 20, 2019
PID controller in C++ to maneuver a vehicle around the track.
View ProjectSign-Language-Recognizer
April 23, 2017 – April 25, 2017
Set of Hidden Markov Models to recognize words communicated using the American Sign Language
View Projectvehicle-and-lane-detection
February 27, 2017 – February 22, 2023
Vehicle Detection using HOF Features
View ProjectBeakedWhaleClassification
September 14, 2016 – December 12, 2019
Project whose goal is the automatic classification of Beaker Whales from recordings of their echo-location clicks
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and highly technical, focusing on computer vision, robotics, and machine learning. This indicates a strong passion for technical challenges and self-driven learning. However, without information on team projects or broader interests, it's difficult to assess cultural fit beyond a strong technical inclination. The projects align well with a Data Scientist role that involves computer vision or applied machine learning.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise and technically focused, but do not provide insight into collaboration, problem-solving approach, or communication style.