Hey there!

Experience

IBM

Frontend Development Intern

July 2024 - August 2024

• Designed and implemented responsive user interfaces using HTML, CSS, and JavaScript, ensuring cross-browser compatibility and a seamless user experience.
• Enhanced application performance by optimizing load times through efficient use of assets, lazy loading techniques, and code minification.
• Refactored existing code to improve maintainability and readability, adhering to best coding practices and standards.
• Integrated dynamic features using JavaScript to improve interactivity and user engagement, such as modals, animations, and form validations.
• Collaborated with cross-functional teams, including designers and backend developers, to refine designs and ensure alignment with user requirements.
• Conducted user testing sessions to gather actionable feedback, iteratively improving the user interface and experience.
• Utilized developer tools and analytics to monitor and resolve UI-related issues, improving usability metrics.
• Documented design processes and implemented changes to facilitate knowledge sharing within the team.

Education

Prasad V. Potluri Siddhartha Institute of Technology

Bachelor of Technology in Information Technology

November 2021 - March 2025

• Relevant coursework:
Data Structures and Algorithms Machine Learning Database Systems Operating Systems Computer Networks Cloud Computing Artificial Intelligence Software Engineering

---

SRI CHAITANYA EDUCATIONAL INSTITUTION, Vijayawada

Class 12th

2021

• PERCENTAGE 75%

---

SRI CHAITANYA TECHNO SCHOOL, Vijayawada

Class 10th

2019

• CGPA 9.3

---

Projects

Multiple Disease Prediction

Machine Learning, HTML, CSS, JavaScript

• Created a web-based prediction tool with Random Forest and Logistic Regression algorithms.
• Designed an interactive and user-friendly interface using HTML, CSS, and JavaScript to enhance accessibility.
• Preprocessed patient data, including symptom encoding, feature scaling, and missing value imputation.
• Implemented a secure backend system to handle user inputs and provide real-time predictions.
• Achieved an accuracy of 92.6% through hyperparameter tuning and iterative optimization of models.
• Incorporated visualization tools to display prediction results and relevant statistics for user comprehension.
• Tested the tool across multiple datasets to ensure robustness and reliability in predictions.

---

Women Crime Hotspot Prediction

Machine Learning, HTML, CSS, JavaScript

• Developed an application to analyze high-crime areas using K-Means Clustering.
• Designed an intuitive and responsive web interface with HTML, CSS, and JavaScript for data visualization.
• Preprocessed crime data, including handling outliers, normalizing location coordinates, and time-stamping incidents.
• Optimized clustering algorithms by selecting the best K value through the Elbow Method and Silhouette Score.
• Achieved a 93.4% accuracy rate in identifying crime hotspots by refining data segmentation techniques.
• Incorporated dynamic mapping tools to visually highlight crime-prone areas for better accessibility and understanding.
• Integrated real-time data updates to ensure the application remains relevant and accurate.
• Collaborated with stakeholders to align the application's functionalities with real-world safety needs and use cases.

---

Certifications

• Python Certification - Hackerrank (March 2023)
• Problem Solving Certification - Hackerrank (March 2023)