Anusha Dudella

Informatics Student | Aspiring Software Engineer | UI/UX Developer

Austin, US.

About

Dynamic and results-oriented Informatics student specializing in Human-Centered Data Science, with a strong foundation in full-stack development, UI/UX design, and data analysis. Proven ability to lead projects, build responsive applications, and derive insights from complex datasets. Eager to apply technical expertise and problem-solving skills to innovative challenges in technology and data science.

Work

Texas Convergent

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Build Teams Member

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Summary

Contributes to the development of user-centered design systems and responsive UI components using modern frontend technologies.

Highlights

Designed user-centered wireframes and interactive prototypes in Figma, establishing scalable design systems for enhanced product development.

Developed responsive UI components with React Native, ensuring adherence to front-end architecture best practices for optimal user experience.

Integrated diverse APIs, third-party libraries, and development tools into the frontend stack, significantly enhancing application functionality and performance.

Collaborated cross-functionally with development and design teams, ensuring seamless alignment between technical implementation and strategic design objectives.

Institute for Computing in Research

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Intern / Researcher

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Summary

Conducted data-driven research on the correlations between public health data and mental health trends, utilizing advanced statistical methods.

Highlights

Conducted research under Los Alamos Laboratory scientist Dr. Sara Del Valle, analyzing correlations between COVID-19 case data and mental health search trends using advanced statistical methodologies.

Authored a research paper detailing the relationship between pandemic waves and psychological distress search patterns, contributing to public health insights.

Leveraged Google Trends API and Euclidean distance to quantify the alignment between COVID-19 trends and mental health queries, providing data-driven insights.

Code Ninjas

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Instructor

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Summary

Delivered engaging programming instruction and mentored students, significantly boosting their technical proficiency and project completion rates.

Highlights

Provided hands-on instruction in Python and Scratch to over 50 students, significantly improving student proficiency and boosting project completion rates by 80%.

Maintained consistent communication with parents and students, delivering progress updates and feedback that optimized lesson plans and fostered concept mastery.

Education

The University of Texas at Austin

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B.S. Informatics (Human-Centered Data Science) Grade: 3.70 GPA

Courses

Introduction to Human-Centered Data Science

Elements of Computers and Programming

Programming for Informatics

Research Methods for Informatics

The University of Texas at Austin

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Certificate Computer Science

Awards

NCWIT AspireIT Scholarship

NCWIT

Recognized for exceptional aptitude and interest in technology, supporting academic pursuits in computer science and informatics.

University Honors Student

The University of Texas at Austin

Achieved and maintained academic excellence, qualifying for the University Honors program.

Languages

Telugu

Native

Spanish

Conversational

Hindi

Basic

Certificates

IT Specialist - Java

Certiport

Microsoft Word

Microsoft

Microsoft Excel

Microsoft

Microsoft PowerPoint

Microsoft

CPR/AED/First Aid

American Heart Association

Skills

Programming Languages

Python, Java, SQL, React Native, HTML, R Studio, C, JavaScript, PHP.

Tools & Technologies

Figma, Git, APIs, Third-party Libraries, User-Centered Design, Frontend Architecture.

Data Analysis & ML

Statistical Methods, Google Trends API, Euclidean Distance, Cyclical Encoding, Gradient Boosting, Machine Learning.

Software & Productivity

Microsoft Word, Microsoft Excel, Microsoft PowerPoint.

Projects

Aurora Mobile Application

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Summary

An interactive mobile alarm system developed using React Native to encourage user physical engagement and productivity.

BreezeMetrics Machine Learning Model

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Summary

A machine learning model developed to predict wind speeds for optimizing insurance pricing and profitability.