Deep Learning and Natural Language Processing in Product Suitability Analysis:
Developed software to assist financial organizations in determining the suitability of a particular product for a certain customer. Employed NLP and Deep Neural Networks trained to predict the most appropriate product recommendation for a certain customer from raw unstructured text data using NLTK, Keras, and Tensorflow.
IoT Enabled Industrial Machinery Automation and Data Analytics using Embedded Systems:
Developed commercial IoT platform for automating industrial machinery using AngularJS and Node.js. Deployed on embedded systems interconnected throughout the factory over our devices. Enabled data analytics to refine work efficiency and tool expectancies in the industry.
Currently pursuing my undergrad degree at SSN College of Engineering doing my 3rd year in the Computer Science and Engineering Department.
Holding CGPA: 8.55
School First
Percentage: 97.67%
School Second
Percentage: 98%
Developed a solution for combatting congested parking systems in major malls and shopping complexes. Used IoT and Embedded Systems (Arduino and Raspberry Pi3) to construct an efficient parking model adaptable to any commercial structure.
Processed images of chassis to detect rim location and orientation through observed features. Developed a system to calculate the exact disposition of the rim at the sub-pixel level and subsequently adjust the alignment of the wheel to correct deviations in inclination and rotation of the detected rim.