Viviane Alencar

Advises on visual identity and design decisions, evaluates options against professional communication standards, and reviews web content and technical publications for clarity and consistency.

Planned and executed controlled experimental tests on optical transceivers by defining measurement setups and systematically documenting results. Identified an unconsidered lens reflection effect impacting signal stability and helped refine technical specifications to prevent downstream rework.

Translated and maintained UI, reference help, What’s New, training, and marketing content for the full Delcam product portfolio through Autodesk’s acquisition and subsequent product consolidation. Established and managed an internal Wiki on Confluence, centralizing product-specific terminology, technical How-Tos, and troubleshooting guides to ensure global consistency across a distributed, multilingual team.

Built translation databases, glossaries, and localization framework for the Delcam product suite, covering CAD/CAM documentation across multiple domains. Translated all documentation types and standardized review methodologies, reducing onboarding time by 75%.

Grade: Thesis awarded highest grade in the program

Activities and societies: Thesis: Embedding Space Analysis and Zero-Shot Learning in CLIP-Like Models. Trained and benchmarked 17 custom neural network models against OpenAI's ViT-B/32 baseline; analyzed effects of batch size, dimensionality, and dataset scale.

B.Sc. in Applied Mathematics and Physics at Technische Hochschule Nürnberg Georg Simon Ohm (Oct 2020–Mar 2025). Thesis focused on embedding-space analysis and zero-shot learning in CLIP-like models, including benchmarking 17 custom neural network models against a ViT-B/32 baseline.