Raksheet Kota
Raksheet Kota

Raksheet Kota

Hi, welcome to my personal website : )

About me:

Hi I'm Raksheet, a Computer Science and Math Major studying at the University of Texas at Austin. I am passionate about full-stack development, cloud computing, and database administration. I am extremely passionate about leveraging technology to make a meaningful impact in people’s lives and am eager to engage in projects and collaborations that drive innovation and empower communities.




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Oracle | Software Consulting Intern
  • Led a successful delivery project with a small business, leveraging the Real Application Testing suite to benchmark and document an impressive 85% performance improvement in their primary database using SQL Tuning Advisor
  • Developed deep expertise in Oracle 23c database architecture through direct mentorship and shadowing of high-stakes client projects, gaining firsthand experience in cloud migration processes, disaster recovery planning, the implementation of scalable architectures, patching strategy, performance tuning.
  • Independently implemented an Oracle RAC database cluster from scratch, honing technical skills and gaining practical experience in database installation, configuration, and management.
Camelot Integrated Solutions Inc | Software Engineer Intern
  • Interfaced directly with prospective customers and federal compliance guidelines to develop NavTExT Travel, a travel claim processing application using AngularJS.
  • Worked with Oracle DBMS to streamline the application’s auditing system, simplifying the end-to-end workflow by 50%.
  • Implemented a seamless user experience with real-time editing across major browsers on Windows, Linux, and MacOS.
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Good Systems - A UT Grand Challenge | Undergraduate Research Assistant
  • Worked as part of the Making Smart Tools Work for Everyone team to investigate how workers can benefit from advances in technology, especially in the fields of Machine Learning and Artificial Intelligence.
  • Trained and deployed an accurate tinyML model onto a rotary hand tool with the purpose of detecting type of work.
  • Created a fully functional IOS companion app to receive inference results from an Arduino Nano via Bluetooth Low Energy and save and display them graphically using the Swift Charts API.
E2log Inc | Software Engineer Intern
  • Constructed Python script using the Pandas library to map contract rates from Logistics Service Providers to a machine-readable format for injection into a PostgreSQL database. Cut down manual workflow for onboarding new LSP contract rate schedules by 75%.
  • Upgraded PostgreSQL versions of development and QA environments and used Selenium automation testing.
  • Created AWS Lambda script to automate the ingestion of user login data from Auth0 to prod database.
  • Used static code analysis tools to assess and correct OWASP Top Ten security vulnerabilities in the code base.
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  • Currently piloting the development of a restaurant engagement platform. Developed a high-performance Python backend using the FastAPI framework connected to a PostgreSQL database hosted on AWS RDS
  • Efficiently managed data validation and API documentation with FastAPI, SQLAlchemy, pydantic, and SwaggerUI.
  • Ensured security through user authentication, leveraging OAuth2 token generation and access token verification
  • Streamlined development, testing, and deployment using Pipenv to manage virtual environments, Alembic for database schema migrations, GitHub Actions for CI/CD, and mangum to deploy to AWS Lambda behind an API Gateway
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  • Created and populated AWS RDS MySQL database with national parks info using scraped data from NPS API.
  • Created API using Flask to access database data through SQLAlchemy ORM and publicly hosted it using AWS EB.
  • Hosted webapp using AWS Amplify, configured load balancing with nginx and uWSGI, and set up Gitlab CI/CD pipelines to automatically deploy changes from respective environments to webapp: https://www.re-park-able.me/.
End-to-end ASR System:
  • Created pipeline to extract MFCC values from raw .wav files using NumPy and SciPy, plotted results with MatPlotlib.
  • Coded a DNN using PyTorch to read in the extracted MFCC feature values and classify into phonemes.
  • Used the Forward and Viterbi algorithms on the phoneme likelihood outputs to implement a HMM-based word recognizer.
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  • Expanded the functionality of the simple x86 ISA Pintos operating system framework to support higher-level features such as priority scheduling, argument passing on the stack, system calls, virtual memory, and a multi-threaded file system.
  • Utilized GDB Debugger to assess and correct race conditions and emulated the OS via Bochs to test for reproducibility.
  • Unfortunately, the code for this project cannot be shared, as the task will be reused in future years.
Non-CS Articles

Contact Me:

The best way to get in touch with me is to email raksheetkota@gmail.com