Because almost all data are stored and transported in cyberphysical infrastructures of some sort, optimizing and securing cyberphysical systems has a strong implication for efficient and secure data processing and analytics. Furthermore, new computing architectures, devices and circuits promote new computing paradigms and allow artificial intelligence to penetrate into systems of all scales. The faculty in this thrust focus on fundamental and translational research that involves big in areas including medicine, health care, biology, materials, climate change, environment, and business. The diagram below shows the different areas that inform the state-of-the-art in data science and engineering as well as some of the application areas that the CoE faculty are engaged in.
Mission
The Data Science and Engineering Thrust of the CoE aims to:
- 1. Advance the state-of-the-art in data science and engineering;
- 2. Collaborate with the different units at UM including the School of Arts and Science, Miami Herbert Business School, the Miller School of Medicine (MSoM), School of Architecture (SoA) and the Rosenstiel School of Marine and Atmospheric Science (RSMAS), to identify and address challenges associated with their domain-specific applications through the use of data science and engineering methodologies. The collaborations will be facilitated by the Institute of Data Sciences;
- 3. Incorporate data science and engineering pedagogies into the curricula to better prepare our graduates for successful careers in this promising field.
To advance state-of-the-art in data science and engineering, it is imperative to incorporate basic research in statistical and computational techniques that enable large scale analysis of data such as AI, Machine Learning and Pattern Recognition. It also calls for the development of new techniques for domain specific problems. These domain specific problems involve applications that are worked on collaboratively with other departments and schools that will provide the domain knowledge. Equally important is the need to update the college’s curricula to complement the advancements in the field, while preparing graduates for successful careers in data science and engineering.
