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Shani R.
Bio
Software developer with strong analytical thinking, high motivation, and excellent communication skills. I learn independently and quickly adapt to new tools, technologies, and work environments. I bring high precision and thoroughness together with solid organizational skills and an ability to meet deadlines.
Skills
Python
C++
Node.js
.NET
React
PostgreSQL
MinIO
Docker
Redis
FastAPI
TensorFlow
PyTorch
VS Code
GIT
Bootcamp Project
A complete classical + deep-learning denoising system for SEM images
Mentored by: Applied Materials
Mentors:
Data Science Bootcamp 2025 (Data)
Responsibilities:
Developed a complete noise-reduction pipeline for SEM images, including preprocessing, structured model execution, and unified evaluation.
Implemented classical denoising baselines—Gaussian, Bilateral, Non-Local Means, and BM3D—within an extensible benchmarking framework.
Trained U-Net denoising models in Python/PyTorch on custom SEM datasets with optimized augmentation and hyperparameters.
Designed and deployed a FastAPI + Docker backend exposing REST endpoints for image upload, model selection, and result retrieval.
Integrated PostgreSQL and MinIO for storing images, benchmarks, and inference results, using Git for version control and team collaboration.
Built an automated evaluation suite computing PSNR and SSIM metrics and generating consistent comparisons across classical and deep-learning models.
Created a PyQt desktop client supporting model execution, visualization of every pipeline stage, and interactive comparison between methods.
Research: Dataset analysis and selection — evaluated multiple SEM datasets, created synthetic noisy samples, and studied which data sources yield the most effective denoising performance.
Research: Performance optimization with parallel execution of multiple models; benchmarking showed limited benefit for production use.
Implemented multi-client support, MinIO-based benchmark selection, and improved visualization features inspired by open issues, enhancing usability and scalability of the system.
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Additional Projects
Developed a complete end-to-end language-learning platform that combines a modern React interface with state-management using Redux Toolkit and dynamic forms built with React Hook Form and PrimeReact. The client delivers an engaging user experience featuring personalized progress tracking and seamless file uploads.
On the backend, the project includes a secure Node.js + Express API with JWT-based authentication, responsible for managing users, courses, and learning content. All data is stored in a scalable MongoDB database, creating a robust and production-ready full-stack system.
English Level
Fluent