Resumo da palestra: Bate-papo com Thiago Bianchi, profissional com larga experiência e que conciliou a formação acadêmica de mestrado e doutorado com a carreira na indústria. Aproveite para fazer perguntas e tirar suas dúvidas.

Short Bio: I am passionate about science and its applications in computational systems, with a particular fascination for the multidimensional nature of data within the vast universe of technology. Currently, I am a Staff Software and Machine Learning Engineer at Meli (Mercado Livre), where I contribute to the development of the Data and Machine Learning platform and related products that serve more than 140MM customers across LATAM. In my previous role as Principal Software Engineer at ASML I contributed to the development of the ASML's Data & Analytics Platform. Before that, as the Principal Data  cientist for Credit Recovery at Itaú Unibanco, I led the data-driven journey by developing machine learning models capable of handling millions of clients and a diverse range of financial products. Additionally, during my tenure at Itaú Unibanco, I served as the technical leader of Itau's Data and Analytics  Platform, providing guidance in defining functional and architectural guidelines for the platform. My academic background includes a PhD degree in Computer Science and Computational Mathematics from the University of São Paulo (USP). Over the years, I have accumulated extensive industry experience, working for renowned companies such as Itaú, IBM, Casas Bahia, and Alstom. During my 13- year tenure at IBM Brazil Software Laboratory, I held positions as a senior software architect and data scientist. My contributions encompassed various projects and activities, including the authorship of 15+ patents related to AI applications in IBM products, participation in the patent evaluator board of IBM Brazil, architecture design of GIS products in the IBM Maximo portfolio, and research and architectural work involving machine learning based functionalities for the same portfolio. In the academic domain, I have served  as a visiting professor for Data Science disciplines at Fundação Dom Cabral, and I continue to be an invited advisor for the Data Science MBA program at USP ESALQ. I also collaborate as a researcher at USP. My areas of interest encompass Data Science Methodologies (such as CRISP-DM and SEMMA),  ig Data and MLOps Architectures, Machine Learning techniques, and Statistical Learning Theory.