◙ Designed and developed advanced image encoding algorithms to enable the training of deep learning models for recognition and classification tasks. ◙ These techniques ensure that datasets, even when encoded to obscure the identity of individuals, remain usable for machine learning purposes. ◙ Worked extensively with state-of-the-art image recognition models to develop methods that protect individual privacy without compromising the accuracy and performance of the models.

◙ Supported graduate courses in Operating Systems, Human-Computer Interaction, and Digital Image Processing and undergraduate courses in Programming Concepts and Cybersecurity◙ Created scripts to automate students' workflows for running assignments in their virtual machines, and assisted preparation of class materials, and class sessions.

◙Deployed machine learning models using Docker and Kubernetes on AWS, reducing deployment times by 30% and improving system scalability.◙Utilized AWS services such as S3, EC2, and SageMaker to streamline model training and deployment, reducing cloud costs by 20%.◙Set up continuous integration and deployment (CI/CD) pipelines using Jenkins and AWS Code Pipeline, decreasing model release cycles by 40% and ensuring consistent updates

◙Developed and monitored Key Performance Indicators (KPIs) for mechanical parts data, creating interactive dashboards in Tableau and PowerBI that reduced the report generation time by 40%◙Utilized SQL Server Management Studio and PostgreSQL to manage and queryextensive datasets, implemented stored procedures, improving data retrieval speed and efficiency by 25%