I'm Ashmita Rajkumar and I am an undergraduate student at Vanderbilt University studying Computer Science with a minor in Engineering Management.
I am highly interested in the overlap between technology and business as well as cybersecurity. I am open to any type of software or business related opportunities to continue learning and gaining experience in different disciplines.
Java
C++
C#
Python
Swift
HTML & CSS
ReactJS
Angular
Firebase
Microsoft Azure
Kali Linux
Data Structures
Intermediate Software Design
Operating Systems
Algorithms
Product Management
Software Engineering Intern, Mobile Application Team
Research Assistant
Reviewed 300 CT scans and annotated organs accurately to help physicians identify anomalies and diseases in a prompt manner. Discovered innovative deep learning algorithms using Python to immediately process CT scans to identify liver disease with 99% accuracy.
Cyber Security Intern
Conducted comprehensive penetration tests on client networks to determine vulnerabilities using Kali Linux
Data Analysis Intern
Examined and extracted data from all United Nations member countries’ medical requirements for space exploration. Collected large amounts of data from NASA medical requirements for space exploration and determined the discrepancies in medical protocols across an international apparatus.
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Developed a spatial awareness navigation planner using Swift and XCode tools. Used Firebase for backend and storage of users.
Competed in Ryerson University Hackathon. Used Google Calendar APIs to integrate event planning and reminder features. Awarded RU Top 20 prize along with Wolfram Alpha's special award.
Developed a shopping platform that connects elderly users to shoppers during the COVID-19 pandemic. Deployed on Heroku and developed with React.
Developed a motivational quotes application to spread positivity during the COVID-19 pandemic using Swift. Used randomly generated database of 50,000 quotes to alert user with positive sayings throughout the day.
Developed an mHealth application that determines the acne type on the user's face upon taking a picture based on color saturation and redness and personalizes experience to match the needs of the patient.