DILENDRA SAJINI

With 6 years of experience in Java back-end development, specializing in the Spring framework and Java 8, I have actively contributed to healthcare information systems, cloud-based learning platforms, and telecommunications projects. My expertise extends to microservices architecture, where I successfully restructured legacy backends into microservices, emphasizing REST APIs and message-driven architecture to enhance scalability and maintainability. My commitment to quality is evident in achieving an impressive 80% unit and integration test coverage with tools like JUnit, non-functional performance testing , memory (Jprofiler) and database profiling (SQLProfiler) . I adhere to clean code best practices, emphasizing backward compatibility and maximizing object-oriented design patterns for code reusability. My diverse technology stack includes EJB 2 development, Spring, Spring Boot, Swagger with OpenAPI, relational and document databases (SQL, MongoDB, CouchDB), Hibernate, Apache Maven, and Gradle build tools. I bring Agile best practices to the table, embracing CI/CD for efficient development cycles. Additionally, I have two years of experience in IoT-focused transportation truck-connecting app development, utilizing technologies such as PubNub, MQTT messaging, and AWS EC2 instance deployment. I've also strengthened security and user-friendliness by integrating Mobile Connect into core ASE products, implementing OAuth2 and JWT tokens. Furthermore, my role included finalizing upfront requirements and technical specifications for OpenStack Gateway, acting as middleware to translate between OpenStack cloud operating system APIs and native Infrastructure-as-a-Service. My diverse skill set and extensive experience make me a valuable asset for any software development team.

With three years of expertise in front-end development including SPA using Angular with NgRx and React with Redux frameworks, I bring extensive experience from various domains, including healthcare information systems, cloud-based learning platforms, and transportation systems. My skill set extends to MEAN stack (Mongo DB, Express.js, Angular, Node.js) development and the successful deployment of applications on AWS EC2 instances. I specialize in real-time data communication, utilizing various messaging protocols like PUBNUB and MQTT with the Mosquito broker. Notably, I've developed two Android applications that facilitate seamless interaction between truck drivers and customers within this ecosystem. My approach to SPA development revolves around creating modular and responsive UI components while ensuring efficient application state management through NgRx and Redux. I excel in managing asynchronous data fetching, handling events, and effectively managing side effects, all while prioritizing performance optimization techniques such as pagination and lazy loading. My commitment to code quality shines through my emphasis on reusable component design, reducing code duplication, and ensuring long-term maintainability. I consider unit testing and efficient dependency management as fundamental components of my development process. I possess a well-rounded skill set and a proven track record of delivering SPAs that meet stringent performance and usability standards.

I have a proven track record of significantly improving the accuracy and efficiency of breast cancer classification in high-resolution histology images. My approach involves utilizing patch-based image analysis, incorporating VGG16 transfer learning, and implementing an LSTM sequential data processing model while meticulously preserving the global context for critical structures and features. I excel in utilizing Python to implement advanced machine learning algorithms and techniques, and I have a talent for creating interactive data applications using Streamlit. Additionally, I conduct my research and development in Google Colab, showcasing my proficiency in this versatile platform. My commitment to staying at the forefront of technology and employing innovative methodologies to address complex challenges in the field of machine learning sets me apart as a forward-thinking and impactful professional in this domain. In the realm of Data Visualization, I have engineered an OLAP system tailored for university student progress tracking, featuring intuitive dashboards and Excel pivot charts. This system empowers stakeholders with the ability to perform visual data analysis, enabling informed decision-making. Furthermore, I have developed an Oracle Apex application designed to manage patient data, staff scheduling, and finances. This comprehensive solution not only ensures data integrity, security, and validations but also provides robust data visualization capabilities. My multifaceted expertise in both Machine Learning and Data Visualization reflects my dedication to leveraging advanced technologies and data-driven insights to address complex challenges effectively.