I'm a Software Engineer specializing in Java backend development with proven experience building scalable, cloud-native applications. Currently architecting solutions across e-commerce platforms, energy management systems, and fintech applications—including payment gateways and digital wallet systems. Technical expertise spans Java ecosystem (Spring Boot, Spring Security), microservices architecture, containerization (Docker, Kubernetes), and AWS cloud infrastructure. Proficient in observability stack including Grafana, Mimir, Loki, and Prometheus, with hands-on experience across MySQL, PostgreSQL, and MongoDB. Background in Machine Learning and Natural Language Processing from previous research experience, with continued interest in integrating AI/ML capabilities into enterprise applications. Driven by clean architecture, system scalability, and emerging technologies.

Currently, I am working at Polygon Technology as a Software Engineer.

I'm currently learning Java, Spring Boot, Python, and Data Science to improve my development skills and stay up-to-date with the latest technologies. I believe that continuous learning is the key to becoming a successful Data Scientist.

• Backend Development: Java, Spring Boot, Microservices, Spring Security, AWS Cloud Services, Docker, Kubernetes, Database Management (MySQL, PostgreSQL, MongoDB
• Machine Learning & AI: Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, TensorFlow, PyTorch, OpenCV, Scikit-Learn, NumPy, Pandas
• DevOps & Tools: Git/GitHub, Monitoring & Observability (Grafana, Prometheus, Loki, Mimir)

• RAISS LAB WEBSITE (Research in AI, IoT, and Software Security): This project maintains lab information such as lab member profiles, lab news, project information, and publication information, and external members can also contact with the director. Technologies used: — HTML5, CSS3, JavaScript, PHP.
• Car Racing Game: This project allows players to simulate the experience of racing cars in various settings. These games typically involve players selecting a car and competing against other players or computer-controlled opponents on various tracks and terrains. Technologies used: — Python, Opencv, anaconda, Jupyter Notebook
• Decision Support System for Pest Control in Agriculture: The Decision Support System for Pest Control in Agriculture is a system designed to assist farmers and agricultural workers in making informed decisions about pest control. The system utilizes data analysis and modeling techniques to provide recommendations for the most effective pest control methods based on the specific conditions of a farm or field. This project is funded by the ICT Division, and it aims to improve the efficiency and sustainability of agriculture while reducing the negative impact of pest control on the environment. Technologies used: — Deep Learning, Python, anaconda, Jupyter Notebook.
• Rice Diseases Recognition and Pesticide Recommendation using Convolution Neural Network: In this project, Convolutional Neural Network (CNN) can be used to recognize different types of rice diseases and provide recommendations for effective pesticide management. The approach involves collecting a large dataset of images of healthy and diseased rice plants, preprocessing the data, training the CNN model, validating and testing the model's accuracy, and using the model to provide recommendations for pesticide application based on the specific disease, stage of infection, and type of rice plant. Also fine tuning the model parameter for better performance. Technologies used: — Convolution Neural Network, Python, anaconda, Jupyter Notebook.

• Handling Class Imbalance in Credit Card Fraud Using Various Sampling Techniques
• DECISION SUPPORT SYSTEM FOR AGRICULTURE: CROP DISEASE RECOGNITION AND CLASSIFICATION THROUGH AN OPTIMIZE CONVOLUTION NEURAL NETWORK (CNN)
• KRISHOKBOT: AN INTELLECTUAL AGENT FOR FARMERS

• Software Engineer at Polygon Technology
• Software Engineer (Trainee) at BJIT
• Machine Learning and Deep Learning LAB, Dept. of CSE, JUST, Research Assistant, Mar. 2021 - Jan. 2023.
  My responsibilities included conducting literature reviews, preparing and analyzing data, developing and implementing machine learning models, writing technical reports and presenting research findings, collaborating with team members, and staying up-to-date with the latest developments in the field. My one of greatest project is Decision Support System for Pest Control in Agriculture which funded by ICT Division. Technologies used: Deep Learning, Python, anaconda, Jupyter Notebook.

• Jashore University of Science and Technology, B.Sc. in CSE, 2023
• CGPA: 3.61 [Second Position]

• Machine Learning
• Deep Learning Specialization
• TensorFlow in Practice Specialization
• Computer Vision – Object Tracking with OpenCV and Python.
• Natural Language Processing Specialization.
• Introduction to Data Science in Python.

• Mathematics Olympiad (9th Position) [2022]
• 50 Days Badge 2023 on Leetcode
• Essay competition award from the Minister of Education (Second Position) [2015]