Ahmedur Rahman Shovon

Software Engineer

Ministry of Posts, Telecommunications and Information Technology•  June 2019 - August 2021

Contribute to the development of e-Governance and e-Services solutions. As a field-level officer of the ICT Division, I am serving directly to achieve "Smart Cities and Communities" to attain Sustainable Development Goals (SDG).

Software Engineer

Cefalo•  December 2017 - June 2019

I was a consultant for NHST Media Group. Our team was continuously developing and maintaining five publications of this Norwegian media conglomerate. We followed agile methodologies to carry out the tasks in a disciplined manner. I mostly used Python (Django, Django REST Framework), JavaScript (React, jQuery) to develop web applications, and various CI/CD (continuous integration and continuous deployment) tools to automate the application deployment process. The tasks include: 1. Development and maintenance of scalable web applications. 2. Collaboration with cross-functional teams to define, design, and ship new features. 3. Development of RESTful APIs and integrating them into the existing system. 4. Bug fixing and improving application performance. 5. Continuously discover, evaluate, and implement new technologies to maximize development efficiency.

University of Illinois at Chicago, Chicago

Computer Science, PhD•  August 2023 - Present•  GPA: 4

- Developing GPU applications focusing on high-performance relational algebra primitives [C7]. - Extending the topological data analysis pipeline to apply persistent homology on temporal brain networks. - Designing multi-node multi-GPU applications to solve iterative high-performance relational algebra tasks.

University of Alabama - Birmingham

Computer Science, PhD•  August 2021 - August 2023•  GPA: 4

- Demonstrated the feasibility of a high-performance relational algebra backend for a subset of Datalog applications leveraging GPU parallelism. - Developed a visualization tool to create Kaplan Meier survival probability graph for cancer data analysis. - Designed a topological data analysis pipeline to apply persistent homology on brain networks resting state fMRI data.