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Software Engineer with less than a year in Machine Learning & Web Development
Aspiring Software Engineer with strong programming, problem-solving, and analytical skills. Experienced in Data Structures and Algorithms, object-oriented programming, and building scalable applications. Proficient in Python, Java, C, and full-stack development using HTML, CSS, JavaScript, and React. Worked on projects using OpenCV, YOLO, and LLM-based technologies for video analytics and customer segmentation. Enthusiastic about applying technology to real-world business challenges and continuously learning in collaborative team environments.
BVRIT Hyderabad College of Engineering for Women
B.Tech · Computer Science and Engineering
August 1, 2022 – June 30, 2026
Telangana Social Welfare Residential Junior College (TSWREIS)
Intermediate · MPC
June 1, 2020 – May 31, 2022
Telangana Social Welfare Residential School (TSWREIS)
Secondary School Certificate
June 1, 2019 – May 31, 2020
Portfolio Web Page
January 1, 2025 – December 31, 2025
Designed and developed a responsive personal portfolio website using HTML, CSS, and JavaScript. Implemented smooth scrolling, structured layout, and clean UI for improved user experience. Showcased academic background, skills, and projects effectively.
MarketMind: Smart Customer Segmentation using LLMs
January 1, 2025 – December 31, 2025
Implemented customer segmentation using SentenceTransformer (MiniLM) embeddings and K-Means clustering. Applied ECOD for outlier detection to improve clustering accuracy. Leveraged LLM-based semantic embeddings to generate meaningful customer behavior insights.
Video-Based Anomalous Activity Summarization System
January 1, 2025 – December 31, 2026
Developed a system for detecting anomalous activities in surveillance videos using YOLO for object detection. Performed frame extraction, preprocessing, and key frame extraction using OpenCV. Generated textual summaries and reports of detected anomalies for easy analysis.
Rainfall Prediction using Machine Learning
January 1, 2024 – December 31, 2024
Developed a rainfall prediction model using Linear Regression, Random Forest, and XGBoost on historical weather data. Performed data preprocessing, feature engineering, and visualization to improve model performance. Achieved high accuracy with XGBoost (R2 = 0.97, RMSE = 65.8 mm) while strengthening analytical and problem-solving skills.
Cultural Fit Analysis
The candidate's academic projects demonstrate a diverse interest in various technical domains, including web development, machine learning, natural language processing, and computer vision. This breadth of interest suggests adaptability and a willingness to explore different technologies, which can be a positive cultural fit for dynamic environments. The profile mentions enthusiasm for 'applying technology to real-world business challenges and continuously learning in collaborative team environments,' indicating a growth mindset and potential for teamwork. However, without professional experience, the extent of collaborative experience is limited to academic settings.
Soft Skills & Operational Fit
The candidate lists 'Problem Solving' and 'Communication Skills' as soft skills. Project descriptions indicate an ability to apply technical skills to solve real-world problems. However, without direct assessment data (e.g., psychometric or English test scores), it's difficult to fully evaluate the depth of these soft skills or operational fit in a collaborative environment. The candidate's academic projects suggest an ability to work independently on defined tasks.