Dania Abuhijleh
Computer Scientist at BROAD INSTITUTE INC
Boston, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolDania Abuhijleh is a multidisciplinary computer scientist and applied mathematician with six years of hands-on experience building cloud-native services and DevOps integrations. Currently studying Computer Science and Mathematics at Northeastern and pursuing graduate work in Applied and Interdisciplinary Mathematics at the University of Michigan, she blends rigorous quantitative training with practical software engineering. She has contributed backend and DevOps work to high-profile open-source projects such as hail-is/hail, implementing benchmark services in Python and integrating them with CI/CD and Google Cloud Storage. Comfortable moving between code, infrastructure, and data, she focuses on reliable, production-ready systems that support large-scale scientific workloads. Based in Boston, she brings a pragmatic, research-informed approach to engineering and a demonstrated ability to navigate both technical and operational challenges. Colleagues describe her as curious and detail-oriented, with a knack for turning complex benchmarking and cloud-auth problems into maintainable solutions.
6 years of coding experience
Master of Science - MS, Applied and Interdisciplinary Mathematics, Master of Science - MS, Applied and Interdisciplinary Mathematics at University of MichiganComputer Science and Mathematics, Computer Science and Mathematics at Northeastern University
Arabic, Turkish, German, English
Github Skills (14)
docker10
devops10
python10
dockers10
cicd10
gcp10
aiohttp9
data-engineering8
bioinformatics4
genomics3
genetics3
hail3
vcf-files3
software-design3
Programming languages (5)
Github contributions (5)
hail-is/hail
Jul 2020 - Jan 2021
Cloud-native genomic dataframes and batch computing
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:48 reviews, 29 commits, 74 PRs in 6 months
Contributions summary:Dania primarily contributed to the benchmark service, which is a cloud-native application. Their work involved implementing new features and fixing bugs within the benchmark service using Python. They also focused on integrating the benchmark service with the CI/CD pipeline by adding benchmark-related files to build configurations and configuring the authorization, demonstrating DevOps skills. The user also worked on integrating the service with cloud resources like Google Cloud Storage.
scalabledata-analysispythongeneticshail
Dania-Abuhijleh/hail
Jul 2020 - Jan 2021
Scalable genomic data analysis.
Contributions:664 commits, 2 PRs, 679 pushes in 6 months
scalabledata-analysispythonpipelinegenomic-data-analysis
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