Jackinson Marcellus

Robotics Field Engineer with over 2 years of diverse experience in various fields, including [relevant field, industry or related experience]. Demonstrated expertise in [relevant technical skills], consistently delivering high-quality solutions that exceed client expectations. Proven track record of successfully contributing to the completion of numerous projects, ensuring timely delivery and adherence to strict quality standards. Committed to continuous learning and staying up-to-date with industry advancements. Seeking new challenges to apply strong problem-solving abilities and drive for innovation.

AUTOMATED ROBOTIC BOAT, EMEDDED C++, ARDUINO TECHNOLOGY

• Developed an automated boat to collect sensing data such as pH, temperature, and conductivity from the Halifax River
• Incorporated motor control, Esc, and Arduino Technology programming in embedded C++

AUTONOMOUS ROBOT, EMEDDED C++, ARDUNIO TECHNOLOGY

• Designed a robot that includes a dropping chip mechanism that autonomously navigates around a rectangular track using ultrasonic sensors, encoder motors, servo motors, and a compass
• Programmed the robot to successfully approach and detect a color-coordinated platform dropping the matching chip color on the correct platform using a trained pixy camera for object detection

ARTISTIC STYLE TRANSFER ALGORITHM, PYTHON, ARTIFICIAL INTELLIGENCE

• Implemented an Artistic Style Transfer Algorithm that transferred the style of an input image into another input image producing a new depiction with the respective content and style of two distinct images

RANDOM FOREST, DECISION TREE, K-NEAREST NEIGHBOR ALGORITHMS, PYTHON, MACHINE LEARNING

• At an accuracy of 92%, I utilized Machine Learning to design an automated method to classify thousands of stars from data collected by NASA
• Developed, analyzed and experimented with different algorithms, such as the Random Forest, Decision Tree and K-Nearest Neighbor algorithms to determine which method obtained the highest accuracy

MAC DYNAMIC BACK-OFF ALGORITHIM, JAVA, OBJECT-ORIENTED SIMULATION ENVIRONMENT

• Discovered that there is a dependency on the number of nodes and message size on the success rate of messages transmitted by implementing an extensive java simulation environment
• The environment simulated the communication at the data link layer between nodes, as a result performing exploratory and statistical analysis that can be used for further experimentation and discovery

CONVOLUTIONAL NEURAL NETWORK ALGORITHM, PYTHON, MACHINE LEARNING

• Developed a machine learning algorithm to locate and assess damaged buildings caused by hurricanes and other natural disasters
• Explored and researched ways to improve the performance of the Convolutional Neural Network (CNN), the machine learning method utilized