Walter Riviera

Thesis in Signal processing: ”Autochecker: a speech recognition tool for research validation”. 

Curriculum on Visual Computing and Pattern Recognition.
Thesis: ”Image aesthetics for people recognition applications”. Graduated with honors

Thesis: ” Advancing Federated Learning in Biomedical Applications:Tools, Best Practices, and Implementations”

I am currently running two parallel businesses:

"Walterbot.ai": Training, Consulting and Education on AI and public events. Already have customers and currently hiring.

Admin-member of AI Wonder: innovative Start-up building RAG applications fully private hosted on-prem!

Supports and coordinates activities for critical customers engagements for POCs, development and deployment of AI applications;

Deliver External and internal talks and training sessions at events;

My mission is to inform, support and drive the technical side of customer engagements across EMEA, with POCs on Data Analytics and AI.

Daily activities include (but are not limited to):
• Brainstorming with Data Scientists for development and deployment;
• Developing, testing and sharing Best-Known-Methods (BKMs) to simplify the adoption of Intel HW+SW AI tools;

• Delivering training and technical workshops on AI to customers and internal stakeholders.

Tools: Python, DL, ML, Tensorflow, MKL, mpi, HPC UGE/Slurm, Linux

Main activities:
- Support the Italian version of the voice cloning system
- Improve the Italian Text-To-Speech engine
- Front/Back end software development

Tools: Python, Linux, JavaScript, HTML, SW versioning

Analysis of the interaction between BizVento App and its users: KEBOP project.

The overall goal of this project is to leverage multiple data sources to:
1) build prediction functions for users profiling
2) Improve the usability of the app

Tools: Python, Statistical models and hypothesis testing, Clustering, Unsupervised learning

Design of novel data mining techniques (ML+DL) to automate the production of training datasets, for deployment on robotic platforms.

Tools: Matlab, SVMs, DNNs (Caffe), cross validations

Structural analysis of the bachelor degree in Biotechnology to find strengths and areas of improvements.

Tools: Online surveys, Python, Week reports

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