Skills

Technical Skills Overview

Throughout my career in academia and industry, I have developed expertise across multiple domains including machine learning, software engineering, data engineering, and scientific computing.

Programming Languages

Proficient (5+ years):

• Python - Primary language for ML, data analysis, and scientific computing
• MATLAB - Numerical computing and signal processing
• C - System-level programming and embedded applications

Intermediate (2-5 years):

• Java - Enterprise applications and data pipelines
• R - Statistical analysis and data visualization
• SQL - Database queries and data manipulation

Working Knowledge:

• HTML, CSS, JavaScript - Web development and user interfaces

Machine Learning & Data Science

Frameworks & Libraries:

• TensorFlow, Keras - Deep learning model development
• PyTorch - Neural network research and development
• scikit-learn - Classical ML algorithms and model evaluation
• Pandas, NumPy - Data manipulation and numerical computing
• OpenCV - Computer vision applications

Techniques:

• Neural Networks (MLP, CNN, RNN, TDNN)
• Computer Vision (Template Matching, Hough Transform, Image Processing)
• Natural Language Processing (Keyword Extraction, Text Classification)
• Time Series Forecasting
• Surrogate Modeling

Databases & Data Engineering

Relational Databases:

• MySQL, PostgreSQL - Database design and optimization

NoSQL & Search:

• Elasticsearch - Full-text search and log analytics
• MongoDB - Document-oriented data storage

Big Data Tools:

• Talend - ETL pipeline development
• Cloud Dataflow - Stream and batch processing

Cloud Computing

Google Cloud Platform:

• Compute Engine, App Engine - Application hosting
• Cloud SQL, BigQuery, BigTable - Data storage and analytics
• Cloud Storage - Object storage
• Dataflow - Data processing pipelines
• Kubernetes Engine - Container orchestration
• Cloud GPUs - ML model training

AWS (equivalent services):

• EC2, Elastic Beanstalk, RDS, Redshift, S3, Data Pipeline, EKS

Certifications:

• Google Cloud Professional Data Engineer
• Google Cloud Associate Cloud Engineer

Software Development Tools

Development:

• Git - Version control and collaboration
• Docker - Containerization
• Jupyter Notebook - Interactive development
• Qt, PyQt5 - GUI application development

Scientific & Engineering:

• LabVIEW - Data acquisition and instrumentation
• Simulink - Model-based design
• SPSS - Statistical analysis

Productivity:

• LaTeX - Scientific document preparation
• Microsoft Power BI, Tableau - Business intelligence and visualization

Specialized Skills

Scientific Instrumentation:

• Real-time measurement systems
• Sensor calibration and data acquisition
• Magnetic field measurements
• Free electron laser diagnostics

Domain Knowledge:

• Accelerator physics and synchrotrons
• Quantum sensing technologies
• Semiconductor failure analysis
• X-ray optics and spectroscopy