Michael Barone

Architected and lead a small team of developers building a production-grade video conference application that analyzes collaboration outcomes as they communicate with one another. Technology stack required a complex and scalable orchestration of several components including audio signal processing, speech-to-text translation, psycholinguistic enrichment of transcript, and other key NLP processing steps.

Full-stack data science implementations for GeniusWire application. GeniusWire was a software-as-a-service that provided brand managers with analytics on trending e-commerce stores. I developed classifiers, recommenders, entity extractors from text, as well as all of the designing, communication to stakeholders, and back-end engineering of the cloud-based solution.

Data warehousing and taxonomy generation. Work with global team to organize, extract value, and refine data management practices for massive international product line. Generation of metadata valuable to as many teams as possible within the company. Growing company culture around data, research, and analysis.

Building educational content on machine learning and artificial intelligence courses for a student base of over one million. Lead online e-degree courses, held podcast discussions, and build coursework. My coursework emphasises the importance of problem solving through programming issues from selecting the appropriate machine learning model to how to approach fixing coding bugs.

Worked alongside the university and hospitals to author four international conference and journal publications utilizing music with smart watches and shoe-embedded gyroscopes for people with fine motor conditions such as Parkinson’s disease.

Discussions on the integration of psychological experimental design, audio signal processing, and machine learning to generate novel insights for digital applications. Highlighted personal work and research which used these concepts to achieve results that were previously undiscovered.

Outlined the process of taking a untested psychological concepts/behaviors and building reliable, quantifiable analysis. Highlighted the importance of an interdisciplinary skill set where advanced psychological experimental design, data science, and machine learning are all necessary in order to innovate.