Daniel
David

2019-2021

Master of Science in Analytics, Georgia Institute of Technology

Atlanta, GA - US

Relevant Coursework: Analytics Modeling, Deterministic Optimization, Simulation, Computational Data Analysis, Data and Visual Analytics.

2013-2017

Bachelor of Mechanical Engineering, Centro Federal de Educação Tecnológica Celso Suckow da Fonseca

Rio de Janeiro, RJ - BR

Visiting student at Kansas State University & University of North Carolina at Charlotte

Relevant Coursework: Ordinary Differential Equations, Statistics, Computational Methods, and Finite Element Analysis.

2023-Present

Senior AI Software Engineer at HORIZON SURGICAL SYSTEMS

• Built convolutional neural network models to classify, segment, and track anatomical structures from digital microscope and optical coherence tomography.
• Enhanced efficiency in the data annotation process by implementing an epistemic scoring system that identifies the most relevant images for a given model, a tool that helps streamline model training and evaluation.
• Built a real-time software solution for displaying AI model outputs as overlays, including tool trajectory visualization.
• Implemented a comprehensive approach to managing workflows and artifacts across the machine learning lifecycle, integrating metrics, configuration files, and model weights for seamless reproducibility.

2022-Present

AI Consultant at TURING

• Provided high-quality data annotation to improve OpenAI's large language model ChatGPT.
• Worked closely with OpenAI researchers to identify and define requirements to improve the data annotation process.
• Provided contributions specifically in STEM fields, with a strong emphasis on data analytics and data science tasks.

2021

Senior Product Engineering Analyst at STELLANTIS

• Developed virtual sensors for electric vehicles, replacing costly physical sensors with deep learning models.
• Led the definition of onboard diagnostics for control modules in electric vehicles.
• Promoted the agile culture as a scrum master.

2018-2021

Research Engineer at MICHELIN

• Led the engineering development of a fleet monitoring program that uses digital diagnostics and machine learning to improve operational efficiency and asset visibility in real-time for fleet managers.
• Adapted existing tests, simulation methods and problem solving to new conditions.
• Optimized and developed models based in big data and machine learning techniques.
• Contributed to the design guide and performance knowledge.
• Contributed to projects with treatment, analysis and visualization of codified data in Python, R, and Matlab; creating reports and dashboards in order to bring operational insights and business opportunities.

2014

Brazil Scientific Mobility Program Scholarship

Issued by CAPES

• Scholarship awarded to the best national undergraduate students in the STEM fields.
• +$ 50,000 to cover tuition and living expenses.

2019

Hackathon Winner - Energy Cluster

Issued by HackingRio

• Winner in the largest South America hackathon, a 42-hour competition focused on creating technology solutions.
• Prototyped an algorithm to improve household energy savings in a 5-person team.

2019

Presenter - Workshop on Statistics and Mathematics in Innovation

Federal University of Rio de Janeiro

• Collaborated with graduate students to investigate the impact of rolling resistance on fuel consumption, using advanced statistical and mathematical techniques.
• Build a report with actionable insights that served as a foundation for the fleet monitoring program developed at Michelin.

2015

Remote Controlled Robot

University of North Carolina at Charlotte

• Designed and implemented an automated forklift controlled remotely in 5-person team using python.
• Awarded First Prize in the Junior Design Lab.