**Developed enterprise-grade Python application** for hyperspectral imaging analysis, architecting a full-stack solution with responsive GUI (tkinter, Matplotlib), robust backend data pipelines, advanced workspace management, real-time spectral visualization, and comprehensive drillcore geological analysis.
**Achieved exceptional performance optimization** with 70-85% overall performance improvement, reducing memory usage by ~65% and increasing UI responsiveness by ~90% when processing multi-gigabyte hyperspectral datasets through advanced algorithmic optimizations and intelligent resource management.
**Architected scalable scientific computing platform** featuring multi-tabbed interfaces, intelligent file system explorers, and dynamic data caching (EnhancedDataManager), implementing advanced techniques including event throttling, multi-level caching, memory-mapped file access, asynchronous rendering, and weak reference management for complex scientific workflows.
**Designed enterprise-level caching architecture:** Built sophisticated multi-tier caching system with AdvancedMemoryCache, PersistentMetadataCache, and SpectralDataCompressor, implementing weak references, intelligent LRU eviction algorithms, memory pressure detection, and cache warming strategies to efficiently handle multi-gigabyte hyperspectral datasets with sub-second retrieval times.
**Implemented comprehensive performance monitoring:** Developed advanced metrics tracking system including cache hit rates, memory usage analysis, retrieval time optimization, and efficiency scoring algorithms, with automatic resource optimization based on real-time system monitoring and usage pattern analysis.
**Engineered specialized data compression:** Created custom compression algorithms for scientific spectral data using gzip compression, precision reduction techniques, and structured data serialization, achieving 60%+ storage savings while maintaining full data integrity for critical wavelength/reflectance datasets.
**Built advanced interactive visualization platform:** Developed real-time spectral data dashboards using Matplotlib integration and custom Treeview widgets for complex data exploration, incorporating performance-critical optimizations including throttled event handling, intelligent canvas redrawing, background processing, and memory-efficient rendering.
**Developed high-performance geological analysis system:** Created spectral plotting engine capable of processing multi-gigabyte geological datasets through innovative caching strategies, memory-mapped file access, and asynchronous data loading, enabling smooth real-time interaction with complex drillcore visualization workflows and scientific analysis tools.
**Implemented robust workspace management:** Architected comprehensive project management system with JSON-based configuration, SQLite persistence, automatic backup/restore functionality, workspace integrity checking, recent project tracking, and seamless data migration capabilities across application versions.
**Created advanced threading and concurrency framework:** Built thread-safe background processing system with progress tracking, batch operations, and non-blocking UI updates, ensuring responsive user experience during intensive data processing operations while maintaining data consistency and application stability.
Data Analyst
May 2023 – Aug 2023
Finance Department, University of Calgary, Calgary, AB, Canada
Performed wallet address labeling on Ethereum blockchain data using Julia, developing efficient scripts to categorize and analyze transaction patterns for financial insights.
Conducted web scraping to gather supplementary blockchain data, optimizing data pipelines with Julia for real-time processing and reporting, enhancing stakeholder decision-making.
Data Analyst
Sep 2014 – Sep 2020
Physics Department, University of Tabriz, Tabriz, Iran
Applied advanced analytical techniques to process experimental physics datasets, leveraging Python scripts for precision data handling and visualization.
Developed technical reports and presentations, utilizing optimized data workflows to communicate actionable insights derived from complex scientific data.