Motivated Artificial Intelligence Engineer with extensive experience in machine learning, deep learning, computer vision, and data analysis. Passionate about solving AI-related problems and committed to delivering innovative solutions. Enjoy working collaboratively within teams or independently to achieve quality and efficiency.
- Analyzing meteorological data and developing AI models to enhance weather forecast accuracy.
- Designing machine learning algorithms and processing climatic data for predictive insights.
- Conducting rigorous testing to improve model performance and ensure reliability.
- Providing innovative AI solutions to support meteorological operations using the latest AI technologies.
Working extensively with meteorological data formats such as NetCDF and GRIB for advanced data analysis.
-Utilizing tools like NCO (NetCDF Operators), CDO (Climate Data Operators), NCDUMP, and WGRIB for efficient data extraction, manipulation, and preprocessing of large-scale datasets.
- Collaborating with cross-functional teams to optimize.
-workflows and enhance decision-making processes.
-Trained in developing and applying AI models for weather data analysis.
-Gained experience across AI, technical support, networking, and applications departments.
-Conducted data analysis using specialized tools to derive meaningful insights from meteorological datasets.
-Utilized data visualization and analysis software to support research and improve forecasting models.
Technical Skills: Python, Linux,, Data Analysis, Machine Learning, Deep Learning, Computer Vision, MS Office, Power BI
Soft Skills: Communication, Leadership, Teamwork, Supervision, Event Management
- Developed an image processing project using deep learning techniques to detect differences between images, enhancing accuracy and efficiency in various applications.
- Created an AI-driven solution utilizing Convolutional Neural Networks (CNNs) for early pneumonia detection from chest X-rays, addressing diagnostic challenges and supporting radiologists, especially in remote areas.