Email: pritom007@live.com
Mobile: +971 524106710
Highly skilled software developer with 4 years of experience in SDET and SDE roles. Demonstrated expertise in developing and implementing automation scripts, debugging software defects, and collaborating with cross-functional teams. Proven ability to learn quickly and adapt to new technologies
Shanghai Jiao Tong University Scholarship, Top 5%
Chinese Government Scholarship (A type), Graduation Ceremony Speaker
- automation test architecture and implemented CI/CD pipeline for software version deployment.
- Wrote and executed test cases, analyzed test reports, and reported bugs.
- Worked closely with the development team to ensure timely and accurate testing of new features and enhancements.
- Technologies used: python, k8s, Docker, python, selenium, azure etc.
- Conducted data extraction and processing to build a simulator for a machine learning-based ranking prediction system using Python, MSSQL, and Flask technologies.
- Developed and implemented supervised machine learning algorithms to predict rankings by achieving an accuracy of 78%.
- Coordinated and collaborated with team members to ensure efficient project development and completion.
- Developed new drag and drop and resize components using PixiJS.
- Implemented Dijkstra's algorithm to optimize Forklifts' routes, resulting in significant efficiency gains.
- Contributed to full-stack development efforts by integrating front-end with back-end.
- Enhanced codebase readability through refactoring and documentation improvements.
- Developed new functions using REST API for monitoring system, enhancing its functionality and improving user experience.
- Designed and implemented a user-friendly web interface using JavaScript to visualize database information, increasing accessibility and usability for stakeholders.
- Produced comprehensive documentation of the project, including technical specifications and user guides, ensuring easy maintenance and future development.
- Utilized technologies such as Gemfire, JMS, OQL, Maven, and Spring to deliver a high-quality, robust system.
1) Forecasting popularity of the news article by title analyzing with BN-LSTM network.
2) A Dynamic Network Traffic Classifier Using Supervised ML for a Docker-based SDN Network.(Dataset)
3) Dinamico: A Dynamic Multi-Controller Assignment Algorithm for SD-WANs. (Ongoing)
Docker-Based Cloud Application Automation Deployment (Chinese Patent Application No. 2019112242339)
Machine Learning, Natural Language Processing(NLP), Big Data, Software Defined Network (SDN)
- collected more than 300K network packets(69Gb) from the lab. Using nDPI analyzed the packets.
- implemented supervised machine learning algorithms to make the network traffic classifier. The accuracy already improved by at least 2%.
- proposed an accuracy accelerator
- grouped similar applications according to CoS rule. Which eventually made a significant impact on the classifier accuracy.
- made an efficient crawler that collected more than 3 Million questions and answers from Stackoverflow.
- using the crawled data trained classifier to detect the types of search. Got 90% accuracy for DNN model which made the search feature dynamic.
- added top search feature, fixed bugs and maintained the quality of code. Wrote the documentation/report of the project.
- implemented PCA to reduce the dimensionality of the data-set.
- implemented SVM, DNN and Logistic Regression algorithm and compared the accuracy of classifiers.
- created Facebook data scraper using selenium. The scraper is able to collect data from official pages, send messages and post in the Facebook wall.
Project Code(on request)
- created Bengali newspaper scraper. Collected nearly 5 years of news data.
Project Code
English(Expert), Chinese(HSK-5), Bengali(Native), Hindi(Advance)