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AI Research Engineer with less than a year in Data Science & Machine Learning
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Data Science enthusiast with expertise in predictive analytics, machine learning, and data visualization. Proven ability to enhance system performance, optimize marketing strategies, and drive data-informed decision-making. Adept at leveraging tools like Python, SQL, Tableau, Power BI, and various ML models to extract actionable insights and solve real-world problems.
Wichita State University
Masters · Data Science
January 1, 2025 – December 31, 2026
Osmania University
Bachelor of Engineering · Artificial Intelligence & Data Science
August 1, 2020 – July 31, 2024
NIAR CAD/CAM Lab, Wichita State University
Digital Twin Systems Engineering Graduate Research Assistant
May 1, 2025 – Present
India
Wichita State University - Industry Community Development
Innovation Campus Marketing & Communications Team Member
February 1, 2025 – May 31, 2025
India
MedTourEasy
Data Analytics Traineeship
March 1, 2024 – June 30, 2024
India
WeMakeScholars
HEST 2k24 Campus Delegate Intern
December 1, 2023 – December 31, 2023
India
The Sparks Foundation
Data Science & Business Analytics Intern
November 1, 2023 – December 31, 2023
India
Robust Autonomous Navigation with Lane Tracking
June 1, 2026 – Present
Developed a real-time lane detection system aimed at reducing road accidents by identifying lane markings, curves, and unintended lane shifts using Canny Edge Detection and Hough Transform techniques. Deployed the system on Raspberry Pi, ensuring lightweight and portable implementation, while addressing real-world challenges such as poor road conditions, variable lighting, and environmental diversity through image preprocessing and filtering techniques.
Wildfire Prediction Using Satellite Imagery
June 1, 2026 – Present
Developed a CNN model with TensorFlow/Keras to classify 42,850 Kaggle satellite images (350x350px) from MapBox API, achieving 91% accuracy and 99% recall on a 6,300-sample test set (2820 No Wildfire, 3480 Wildfire), using preprocessing (resizing, normalization) and training (Adam optimizer, 20 epochs) for scalable, real-time wildfire detection.
AI Fitness
June 1, 2026 – Present
Developed an AI-powered wellness system offering personalized recommendations for diet, fitness, mental well-being, and sustainable living, leveraging multi-source data (user preferences, health metrics, activity levels) to generate optimized meal plans, emotional tracking, and lifestyle insights. Integrated computer vision-based fitness tracking using OpenCV and pose estimation to monitor exercise form and repetitions in real-time, enhancing workout effectiveness and enabling intelligent feedback for personalized coaching.
Python 101 for Data Science
IBM
June 1, 2026 – Present
Workshop Into to R programming
Great Learning
June 1, 2026 – Present
Machine Learning with Python
IBM
June 1, 2026 – Present
Data Science Tools
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse academic projects (wildfire prediction, autonomous navigation, AI fitness) and internship experiences (data science, business analytics, digital twin systems) demonstrate a broad interest in applying AI/ML across various domains. The current Graduate Research Assistant role aligns well with a research-oriented position. The blend of academic rigor and practical application suggests a proactive and adaptable individual, fitting well into an innovative and research-driven culture.
Soft Skills & Operational Fit
The candidate's resume highlights collaboration with interdisciplinary teams, communication of insights to non-technical stakeholders, and adherence to privacy protocols, suggesting a good operational fit. Experience in marketing and communications also indicates strong communication and teamwork skills. The academic projects and research assistant role demonstrate problem-solving and critical thinking abilities.