• Reviewed and provided feedback for 40+ AI, ML, and programming language courses for ensuringaccuracy and relevance to industry standards.•Conducted in-depth reviews of course materials, including videos, scripts, quizzes, and exercises, toensure clarity, accuracy, and engagement• Worked with developers, and instructional designers to implement revisions and deploy coursesseamlessly.

• Engineered a novel ensemble model leveraging attention mechanisms for solar panel segmentation,achieving an impressive 0.93 IoU.• Developed an unsupervised neural network for image enhancement, significantly improving solar panel segmentation performance using hyperspectral images.• Authored and published a research paper on solar panel segmentation from remote sensing imagery,contributing to advancements in the field.• Mentored an intern, providing expertise in hyperspectral decomposition pipelines and neural networkdevelopment, fostering their professional growth.• Fine-tuned hyperspectral decomposition techniques, enhancing the accuracy and efficiency of solarpanel segmentation models.• Designed and implemented 5+ innovative band selection methods for hyperspectral images, boostingsegmentation performance.• Created a solar panel segmentation model using U-Net architecture, delivering robust and scalablesolutions for remote sensing applications.

• Engineered a real-time fall detection algorithm integrating LSTM and MediaPipe, achieving animprovement in classification accuracy.• Developed AI-driven data reduction solutions using WGAIN and CNN architectures, optimizing data efficiency and processing speed.• Designed and implemented a genetic algorithm for Neural Network’s hyperparameter tuning, significantly enhancing the model’s performance and reducing training time.• Created a machine learning-based kick classification algorithm for smart trunk openers, leveragingDoppler histogram analysis to improve functionality and user experience.