• Led the development of a globally accessible website and RESTful API on Azure using NodeJS, offering comprehensive city information including temperature, wind speed, humidity, population, and tourist attractions.• Integrated external APIs like OpenWeather and Google Maps to enrich data, enabling real-time retrieval of weather and tourist information for any city.• Strategically deployed web service across multiple Azure regions (Canada Central, Germany West Central) for global distribution and scalability.• Implemented Azure Front Door and Web Application Firewall (WAF) for enhanced security, utilizing Resource Groups, Virtual Networks, and Network Security Groups. Ensured API key security by leveraging Azure Key Vault for confidential storage and prevention of key exposure.• Managed monitoring and scaling using Azure Monitor, AutoScaler, Metrics, Logs, and Alerts for optimal performance.• Established a CI/CD pipeline with Azure Repos and Build and Release Pipelines, facilitating seamless integration and deployment across distributed servers.• Integrated authentication and authorization using Azure App Service Authentication for enhanced security measures.• Utilized Azure Cosmos DB, a distributed database, to store city information, ensuring scalability and availability.

• Designed and implemented a machine learning solution to address the issue of empty shelves detection in retail environments, leveraging advanced Convolutional Neural Networks (CNNs) technology.• Led the data collection effort by gathering and meticulously labelling over 100,000 boxes on a diverse dataset comprising of 15,000 high-resolution images of shelves, capturing various angles, lighting conditions, and perspectives to ensure comprehensive training data.• Executed rigorous preprocessing of collected images, including resizing to 256 x 256 pixels, conversion to grayscale, and normalization of pixel values between 0 and 1, ensuring standardized input for the machine learning model.• Engineered a sophisticated deep learning model architecture, incorporating multiple convolutional layers, a pooling layer, and a fully connected layer, to accurately detect empty shelves within retail environments.• Implemented a robust training strategy utilizing 70% of the dataset for model training, 15% for validation, and the remaining 15% for evaluating the model's performance, ensuring comprehensive assessment and optimization of the model.• Achieved exceptional model performance with an accuracy rate of 93.7%, accompanied by a precision score of 0.92, a recall score of 0.88, and an impressive F1 score of 0.90, validating the effectiveness and reliability of the developed solution in accurately detecting empty shelves in real-world scenarios.

• Led the strategic development of a resilient Development, Testing, and QA cloud infrastructure on AWS. Seamlessly integrated cloud solutions with Jenkins, SonarQube, and Airflow, enhancing automation, continuous integration, and quality assurance processes.• Implemented a comprehensive suite of security measures, including AWS Web Application Firewall (WAF) and Identity and Access Management (IAM), ensuring stringent data protection standards and regulatory compliance.• Orchestrated virtual hosting on Apache HTTP Server to proficiently manage multiple domains.• Leveraged diverse AWS technologies for scalable and resilient cloud solutions.• Conducted end-to-end testing of the infrastructure and vigilantly monitored for anomalies or performance issues, ensuring seamless operation and optimal performance.• Spearheaded the implementation of client case studies involving sensitive user data, such as card details, within a Java 2 Enterprise Edition (J2EE) environment, emphasizing commitment to data security and privacy.• Developed and integrated encryption and decryption Java JARs to safeguard sensitive data.• Employed SonarQube for comprehensive code quality analysis, vulnerability assessment, bug identification, and code refactoring, ensuring the delivery of high-quality, secure software products.• Designed and implemented JavaServer Pages (JSP) to dynamically generate interactive reports, facilitating informed decision-making for the sales, finance, and marketing teams.• Demonstrated agility in resolving production issues by leveraging JUnit test cases for rigorous testing and validation, ensuring robustness and reliability of deployed solutions.• Analyzed server storage efficiency and proposed optimizations for enhanced user experience.• Developed and documented business processes, including flowcharts and architecture diagrams.• Built CI/CD pipelines using Jenkins and integrated with AWS cloud environment.

• Constructed learning modules, presentations & lab exercises to teach Java, Machine Learning, Deep Learning, Agile, Design & Planning, Big Data courses to 300+ students.• Facilitated over 33 interactive doubt-clearing sessions that resulted in a 20% increase in student grades.• Directed 27 team-based labs & model-building projects with hands-on training, leading to successful completion by 80% of students.• Provided guidance to 60+ students through the international paper publication process for AI projects.• Develop comprehensive course materials and syllabi covering Java programming, artificial intelligence (AI), and machine learning (ML) concepts.• Conduct engaging lectures, tutorials, and practical sessions to facilitate student understanding and application of Java, AI, and ML principles.• Provide individualized guidance and support to students, including mentoring and tutoring sessions to address their specific learning needs.• Design and oversee hands-on programming assignments and projects to reinforce theoretical concepts and encourage practical implementation in Java, AI, and ML.• Collaborate with faculty members on research projects related to Java development, AI algorithms, and ML techniques, contributing insights and assistance as needed.• Assist in grading assignments, exams, and projects, providing constructive feedback to students to aid in their academic growth and improvement.• Stay updated on the latest developments and trends in Java programming, artificial intelligence, and machine learning fields to enhance teaching effectiveness and relevance.• Participate in departmental meetings, workshops, and professional development activities to exchange ideas and continuously improve teaching methodologies and practices.