Hi I'm
Raghuram Sadineni
I am a Software Developer II at Turner Industries
Hello there! My name is Raghuram Sadineni, and I am a Software Developer II at Turner Industries. I played a pivotal role in enhancing and maintaining critical applications. I collaborated on the development of innovative features, transforming tools to streamline processes. I was also responsible for developing new modules, fixing bugs, and improving overall functionality, enhancing the user experience and operational efficiency.
With over four years of experience as a Software Developer, I have worked on multiple enterprise applications, and I'm always looking for new opportunities to grow and expand my skill set.I'm confident in my ability to leverage my knowledge and expertise to help businesses develop applications that align with their vision and goals.
If you're interested in learning more about my experience and how I can help your business, feel free to connect with me.I'm always excited to explore new possibilities and collaborate with like - minded individuals.

Developed a robust and visually appealing website for Sindia Ristorante, significantly enhancing their online presence and streamlining the management of their online traffic. This website has improved user engagement, leading to a 60% increase in visitor retention and smoother navigation for users.

Developed a user-friendly WYSIWYG editor using EditorJS, enabling teachers to effortlessly create engaging lessons. Integrated into the BrBytes ecosystem, resulting in a 80% increase in lesson creation efficiency and positive feedback from 95% of teachers.

Successfully deployed the Bhamni open-source healthcare management system in a public hospital, Slashed patient wait times by 75% through implementation of face recognition technology for efficient patient record retrieval in OpenMRS.

Created a user-friendly web app utilizing TypeScript to implement a shift-reduce parser. The app parses strings based on a pre-defined context-free grammar, displaying the final goal state. Perfect for anyone interested in shift-reduce parsing.

Implemented an expert system recommending textbooks with comprehensive information and online/download links by using automated software to search the internet and gather relevant information, which is then presented in a desktop application, saving users an average of 2.5 hours per query.

Implemented various machine learning algorithms including KNN, Decision Tree, Random Forests, SVM, and ANN on Iris and Breast-Cancer-Wisconsin datasets, demonstrating proficiency in machine learning techniques and data analysis.