Ngaatendwe
Dumbarimwe

Leveraging generative machine learning for general-purpose calibrations in the CMS experiment at CERN, working with Dr. Spandan Mondal.

• Applied state-of-the-art generative machine learning techniques to high-energy physics problems within the CMS experiment at CERN.
• Developed and evaluated modern generative models — diffusion models, Conditional Flow Matching, normalizing flows, CycleGANs, and optimal transport methods — to improve the calibration of simulated Large Hadron Collider collision data using real detector observations.
• Worked extensively with PyTorch, deep learning, domain adaptation, workflow automation, scientific computing, and large-scale experimental datasets.
• Strengthened skills in ML research methodology, experimentation, and model evaluation on complex scientific challenges.

• PyTorch
• Diffusion Models
• Flow Matching
• Normalizing Flows
• Optimal Transport
• Scientific Computing

Trained with Meta Production Engineers on how large-scale production systems are designed, deployed, monitored, and maintained.

• Worked closely with Meta Production Engineers to learn how large-scale production systems are designed, deployed, monitored, and maintained.
• Gained hands-on experience with Linux, networking fundamentals, shell scripting, Git, Python automation, containers, and production engineering workflows.
• Developed projects emphasizing infrastructure automation, reliability, and operational excellence.

• Linux
• Networking
• Shell Scripting
• Python
• Containers
• Git

Advanced technical interview preparation focused on algorithms, system design fundamentals, and software engineering practices.

• Completed advanced technical interview preparation focused on algorithms, system design fundamentals, and software engineering practices.
• Solved complex coding problems and received mentorship from experienced software engineers.

• Algorithms
• System Design
• Mentorship

Intensive technical development program covering interview preparation, engineering best practices, and career readiness.

• Participated in an intensive technical development program focused on interview preparation, software engineering best practices, and career readiness.
• Collaborated with peers on technical challenges while strengthening data structures, algorithms, and problem-solving skills.

• Data Structures
• Algorithms
• Problem Solving