Sebastian
Sebastian is a Tech professional with vast experience in a wide range of technical and business fields: Data Science, Machine Learning, AI, Product Strategy, Sales, Marketing, Analytics and Online Advertising.
He currently leads the Data Science team at OliPay. Before that, he worked as a Deep Learning consultant at SAP SE, developing Chargrid: a state-of-the-art neural information extraction system with 1M/month API hits by Concur's customers.
Before that, he conducted his Msc. in Data Science at New York University, sponsored by Fulbright scholarships. Before that he worked at Google, leading the SMB long term product strategy for the whole Spanish Speaking Latin America region.
He has also conducted internships at Capital One Bank, Microsoft, and Liveperson.
Felipe
Felipe is a machine learning researcher and engineer who specializes in the design and evaluation of deep learning models
Prior to funding Goby Studio, he developed deep learning solutions for the cybersecurity industry at Sophos AI, which got integrated into hundred of thousands of endpoints. This work also led to a number of scientific publications, and participation in several InfoSec conferences.
He has also worked and collaborated with a number of startups in expanding they’re AI capabilities (from life sciences to finance). During his time at the Center for Data Science at New York University as a masters student and Fulbright scholar, Felipe focused his research on adversarial learning applied to generative models. In a previous work-life he designed satellite connectivity solutions.
Felipe has a curious and versatile mind which allows him to understand and conceptualize needs and opportunities for partners across a number of industries.
Michael
Michael is a mathematician and data scientist specializing in Natural Language Processing and Data Visualization.
During his 5 years at Liveperson, Michael was the Science Lead for several innovative products including: a novel quality measurement strategy for dialog systems; tools to aid in taxonomy creation; intent discovery; and a patented method for augmenting the understanding of bots with live-agents.
Michael has a masters in Data Science from NYU, and a BA in Mathematics from Umass Amherst. He has an avid passion for mathematics, and is especially adept at the rapid prototyping of novel ideas.