Data Synthesis using GAN and TVAE

I am seeking an adept freelancer with expertise in Rust, TensorFlow, and the application of machine learning techniques like Generative Adversarial Networks (GAN) and Temporal Variational Autoencoders (TVAE). You'll be pivotal in creating a solution that can effectively synthesize data from various formats including tabular single table, multi table relational, sequential, images and PDF files.

Key Project Points:
- Data File Types: The project involves working with tabular single table, multi table relational, and sequential data, as well as images and PDFs.
- Desired Outcomes: The synthetic data generated should aim at improving data privacy, augmenting training datasets, and simulating scenarios.
- Data Characteristics: The synthetic data should reflect similar statistical properties, preserve data relationships, and exhibit realistic variability. An added benefit would be if it can also offer data profiling.

Ideal skills and experience:
- Proficiency in Rust, TensorFlow, GAN, and TVAE
- Extensive experience in data synthesis and manipulation
- Strong background in handling various data formats
- Ability to ensure privacy and security of generated data
- Proven track record of creating diverse and realistic synthetic data