Data science is rapidly evolving as an essential interdisciplinary field, where advances often result from combinations of ideas from several disciplines. This annual conference, is for professionals and practitioners working in machine learning, deep learning, data mining, artificial intelligence, or big data problems broadly. Recognizing that discovery and innovation happens at interfaces of disciplines and communities, the conference aims to bring together a diverse set of people from multiple communities spanning academia and industry.
The conference will be a research, development, and innovation (RD&I) gathering, bringing together university and research labs (technology developers), key industry verticals (technology consumers), and IT industry (technology providers) that are looking at opportunities created by advances in AI, data analytics, machine learning and deep learning. It is structured to facilitate engagement and networking across all of these boundaries. The conference is specifically interested in highlighting use-cases that translate data to knowledge enabled by data and fueled by advances in data analytics, machine learning, deep learning, and AI.
Building on the model we have used very successfully in our annual Oil & Gas HPC Conference, the Data Science Conference will strike a balance between applied and fundamental data science, and academia and industry. This combination of research and application discussion will create a venue for networking, collaboration and partnership building.
With Houston being the fourth-largest city in the U.S., and recognized as a hub for energy, health, space, finance and transportation the conference will help foster collaboration and networking. In order to best capitalize on this dynamic industry landscape, technical themes will evolve based on local, regional and national needs.