Saint Louis Machine Learning

Harsha Vardhan Reddy Bindela

Location: Saint Louis, USA

314-***-**** ad5c79@r.postjobfree.com LinkedIn WORK EXPERIENCE

Research Assistant, Lung Diseases Detection Project Jan 2024-Present Company: Saint Louis University Saint Louis, USA

Initiated research into Convolutional Neural Networks (CNN) for lung disease diagnostics, achieving a landmark 97% accuracy rate in detecting conditions, setting a new industry standard for diagnostic precision.

Orchestrated the development of research documentation and prepared content for submission to a pres- tigious 2024 conference, aligning with industry standards and best practices to enhance company visibil- ity and credibility.

Managed the development phase of a web application for immediate disease diagnosis via X-ray up- loads. Achieved an initial testing accuracy of 92%, with ongoing plans for enhancements to ensure user reliability and cost savings.

Teaching Assistant, Machine Learning Sept-Dec 2023 Company: Saint Louis University Saint Louis, USA

Led the development of an innovative machine learning curriculum, integrating industry projects and interactive labs, resulting in a 30% increase in student project completion and satisfaction.

Evaluated and graded 100+ student assignments in machine learning, delivering detailed feedback to enhance understanding and skills development, resulting in a 15% increase in average assignment scores and student engagement levels.

Directed the preparation and distribution of class documents and resources, empowering students to excel by providing structured support and facilitating efficient learning. PHP Developer Intern, Inventory Management System May-Aug 2023 Company: Saint Louis University Saint Louis, USA

Took charge of Gift Inventory Management, overseeing the creation of key elements including Gift-In and Gift-Out forms, Toy List, Current Inventory, Report Generator, and advanced sorting/filtering func- tionalities.

Engineered a robust system employing HTML, CSS, JavaScript, PHP, and MySQL to streamline gift track- ing and management, resulting in a 30% improvement in order fulfillment speed and a 20% reduction in tracking errors.

Implemented an innovative Ajax and jQuery system to retrieve prices in real-time, enhancing site respon- siveness by 50% and user experience by 40%, leading to a 25% surge in conversion rates. TECHNICAL SKILLS

• Languages: Python, PHP, JavaScript, SQL

• Database Management: MySQL, MongoDB

• Frameworks: CSS Bootstrap, Python Flask

• Development Tools: Excel, Tableau, Jupyter Notebook, Visual Studio Code, Postman

• Version Control: GitHub

• Operating Systems: Linux, Windows

• Other Skills: Data Analysis and Visualization, Pandas, NumPy, Matplotlib, Scikit-learn PROJECTS

Student Database Management System Jan 2024-Present

Engineered a record loading and search feature using Ajax and jQuery to enable real-time data retrieval and display, enhancing user experience.

Orchestrated the automated import of branch data from CSV uploads, streamlining the database update process and ensuring data integrity.

Crafted and integrated comprehensive role-based access control, ensuring secure and appropriate user interactions with the database system.

Pesticide E-Commerce Website Aug-Dec 2022

Led the development of a responsive e-commerce platform for direct pesticide procurement, utilizing HTML, CSS, JavaScript, PHP, and MySQL.

Integrated advanced project management and collaboration tools, including Jira and GitHub, to stream- line development and version control.

Conducted thorough testing and utilized Docker and CircleCI for containerization and continuous inte- gration, ensuring robust and scalable application deployment. PUBLICATIONS

Heart Failure Prediction using Artificial Intelligence Methods IEEE Link Mar 2024 Publisher: IEEE AIPR 2023 Saint Louis, USA

Directed the development of an SVM model with an RBF kernel, achieving a high classification accuracy of 91.85%, demonstrating potential in heart disease diagnosis.

Employed K-means clustering to unveil hidden patterns within patient data, aiding in the identification of potential heart disease subgroups for early intervention.

The study’s findings contribute to the advancement of personalized healthcare, underlining the effective- ness of machine learning in enhancing diagnostic precision. EDUCATION

Saint Louis University, Saint Louis, USA 18 May 2024 M.Sc. in Computer Science

GPA: 3.70/4.00

Bharath University, Chennai, India 30 May 2022

B.Tech in Computer Science

GPA: 9.0/10.0

CERTIFICATIONS

• Python for Data Science - IBM

• SQL and Relational Databases - Cognitive Class

• Tableau Training - SkillUp by SimpliLearn

• Data Science with Python - Spark Foundation

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