Belal Esawe

An automatic product tagging solution that uses advanced AI models to extract main categories and attributes from any product catalog, eliminating the need for manual tagging. This innovative solution automatically generates accurate tags, simplifying catalog management, saving valuable time, and enhancing efficiency and organization. It is a cutting-edge solution that revolutionized how product tagging is handled by replacing manual efforts with seamless automation and transforming the workflow of product categorization.

An eCommerce personalized recommendation system that, leveraging historical user interactions, processes vast data to deliver tailored recommendations. Through advanced algorithms, it analyzes purchase history, browsing habits, and demographics to generate accurate product suggestions, enhance customer satisfaction, drive sales, and foster loyalty with personalized recommendations that resonate. This system elevates eCommerce platforms, provides a dynamic shopping experience, and unlocks new growth opportunities in the competitive market.

An innovative product designed for eCommerce customers. Powered by machine learning, this system revolutionizes the shopping experience by seamlessly scanning outfit images and conducting a product search. It intelligently identifies all items within the image and presents them in a captivating carousel called Complete-the-look. This way, customers can effortlessly explore and purchase the entire outfit, enhancing convenience and style cohesion. Embracing the future of fashion shopping, where visual inspiration transforms into a seamless purchase journey, this system elevates eCommerce platforms by offering a curated shopping experience that drives conversion.

This innovative solution utilizes AI models to analyze multispectral satellite images, enabling spectral matching and precise mineral detection. By harnessing data from satellites like WorldView-3 and ASTER, this game-changing project targeting professional geologists in mining unveils unique spectral signatures for various minerals.

As it leverages rich multispectral data, Mineral Alteration Mapping aids exploration, resource estimation, and mining planning. With this system, geologists can efficiently detect and map mineral alteration, significantly reducing time and costs in the industry.

By automating the process, advanced AI models analyze the satellite images, providing invaluable insights into mineral presence and distribution so that geologists can focus on in-depth analysis and decision-making, bolstering productivity and accuracy.

Ultimately Mineral Alteration Mapping optimizes mineral exploration and mining operations and empowers geologists with an efficient tool to identify and map minerals, unlocking new discoveries and resource management opportunities.

A system that uses AI models to detect water bodies and produce accurate digital elevation maps (DEM). This solution streamlines the process by automating waterbodies detection in satellite imagery, allowing geospatial analysts to focus on data analysis. With precise zero-leveling of waterbodies, the project enhances DEM accuracy, benefiting hydrology, environmental modeling, and land management applications. I revolutionized geospatial analysis with this innovative project, optimizing workflows and delivering valuable insights for informed decision-making.

In this project, I focused on defect mapping in infrastructure. Leveraging the power of AI, I developed a robust system capable of mapping various types of defects, such as cracks, spalling, efflorescence, and joint failures. This model has been trained on a vast amount of data collected from diverse assets worldwide, ensuring its adaptability to different factors such as construction material, time of day, weather, and shadows.

By utilizing AI technology, this system can automate the process of identifying and quantifying defects in infrastructure assets like dams, chimneys, roads, and buildings. Accurately mapping defects is crucial in ensuring these assets' safety and structural integrity while simultaneously reducing the time and cost associated with manual investigations.

Through this project, on the one hand, I provided customers with valuable insights by quantifying defects and sorting them based on severity. On the other hand, by presenting defect information in a systematic and organized manner and evaluating and prioritizing defects, I empowered engineers to efficiently assess the condition of infrastructure assets and take appropriate actions.

I employed stable diffusion and Null-Text Inversion techniques to generate and/or locally edit characters. Furthermore, I leveraged a fine-tuned Language Model on character dialogues to create a chat style that aligns with the selected character.

By utilizing these advanced methodologies, I achieved impressive results and delivered high-quality outcomes for my client. My approach not only demonstrates technical proficiency but also emphasizes the ability to create engaging and dynamic content.

I believe that my expertise and passion for machine learning, combined with my strong problem-solving skills, make me the ideal candidate to undertake this project. I am committed to delivering exceptional results and exceeding your expectations.

I would welcome the opportunity to discuss your project requirements in more detail and showcase how my skills align with your needs. Thank you for considering my candidacy, and I look forward to the possibility of collaborating with you.