Nikita Belooussov

Developed a 3D pose-estimation solution using Apple LiDAR point-cloud data for paint-coverage accuracy, architected AWS data pipelines, and designed technical roadmaps for client pitches at international forums.

Engineered a Docker-based framework for platform interchangeability, implemented a TensorFlow object detection model for defect identification, and performed root-cause analysis and A/B testing on production models.

Implemented an object detection model in Python for automated quality control and enhanced decision tree algorithm performance by cleaning datasets and tuning parameters.

Developed scalable systems for prioritizing tests during chip quality-control operations and designed a data-cleansing program to correct structural errors in batch data.

Developed automated Python and R scripts to monitor testing processes and designed an interactive managerial dashboard in Spotfire to track global chip production.

Designed and implemented testing scripts for the Mars 2020 rover's SHERLOC instrument, developed a PyQt GUI for test procedures, and conducted data validation in Python.

Master of Science in Artificial Intelligence from Universitat Politecnica de Catalunya, completed in January 2023.

Master of Science in System Design Engineering from Fachhochschule Karnten, completed in 2020.

Bachelor of Science in Electrical and Electronics Engineering from New Mexico Institute of Mining and Technology, completed in 2018.