SABEEN MUSTAFA
[email protected] | (857) 832 0413 | Boston, MA | LinkedIn
Led development of American Sign Language detection using Mediapipe and ML models (SVM, 2D-CNN, YOLOv4-TINY, YOLOv5) in Python, achieving accuracy of 99.5%, laying the foundation for deaf-blind individuals.
Implemented SQL-based data management system to streamline the storage and retrieval of hand movement data, fostering a 20% increase in data processing efficiency.
Developed advanced ML models (LSTM, Bi-LSTM) using Keras and TensorFlow to forecast stock price movement for U.S. market, boosting investment decision-making efficiency by 30%.
Implemented stacked autoencoder on 50k+ dataset to streamline data analysis, reducing features, and leveraged ARIMA to capture diverse temporal structures, accelerating processing speed by 20%.
Leveraged sentiment analysis on stock-related data, utilizing social media data from platforms like Stock Twits and Twitter to construct a comprehensive investment strategy that yielded a 15% increase in portfolio returns.
Designed Tableau dashboard to provide meaningful insights into performance monitoring metrics and resulted in 40% increase in usage by client.
Engineered Lip Speech Recognition web interface utilizing 3D CNN for real-time text conversion from lip movements, capturing facial features, and achieving 75% accuracy, vital for individuals with speaking disabilities.
Developed an algorithm to shrink video file sizes using advanced OpenCV techniques (Fourier transformation, energy coefficients, repetitive motion analysis), resulting in 61% reduction in storage space while preserving video quality.
Utilized Computer Vision techniques to accurately predict seven emotions through a three-layer CNN, achieving a 66% accuracy rate, and generated custom image visualizations using Python's matplotlib.
نظام التوظيف التشغيلي المعتمد على الذكاء الاصطناعي أولاً، الذي يوحّد ويؤتمت دورة التوظيف بالكامل للمؤسسات الحديثة حول العالم.
د.جوب منطقة حرة ذ.م.م. 2026 © جميع الحقوق محفوظة
