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About Me
I am an AI Engineer passionate about solving practical challenges through structured model development. My work spans the entire machine-learning lifecycle, from data cleaning and experimentation to threat assessment, model refinement, and final evaluation. I enjoy building impactful solutions using transformers, transfer learning, and generative models, continuously improving model behavior through real-world feedback.
With over 2+ years of hands-on experience, I develop, refine, and validate ML/DL models for real-world applications, focusing on reliable, high-accuracy systems. I've contributed to production-grade AI pipelines, especially in security-driven computer vision, training and fine-tuning models using RLHF for improved performance.
Deep Learning & Computer Vision Innovations
Lip-to-Speech Synthesis
Collaborated with Varcons Technology to build a deep learning system converting silent lip-movement video into synthesized speech. Trained CNN + RNN architecture and experimented with feature extraction to improve intelligibility. Enhanced model output quality through iterative tuning and dataset cleaning.
Fruit Quality Detection
Developed a smartphone-camera-based real-time fruit-quality detection system using CNN-based image classification. Built a lightweight web interface for instant grading, enabling fast and scalable quality evaluation. Conducted extensive testing to improve classification consistency across real-world lighting and environment variations.