fall students

Data Science

Masters Program: Data Science for Chemical Engineering and Materials Science

The program core provides fundamental knowledge of statistical and data analysis, machine learning, and optimization, as well as their application in chemical, biological, and materials science and engineering problems. Elective courses allow students to specialize in artificial intelligence, high performance computing, systems engineering, automation and robotics, or data analytics, depending on their specific interests and needs. Students have the option to complete a capstone project under the supervision of CEMS faculty, possibly in collaboration with faculty from other departments or industry advisors.

IPRIME: Data Driven Discovery and Design Program (4D)

The ever-increasing availability of data and computing power has led to rapid adoption of artificial intelligence and machine learning methods in a broad range of applications in cheminformatics, bioinformatics, and materials design. Data generated in these fields can be massive or sparse, time-varying or steady, low-dimensional or high-dimensional, discrete or continuous, low-fidelity or high-fidelity, uncertain and noisy, biased, and typically constrained by physical laws. The 4D program aims to address the above challenges and accelerate the application of data science in industry. More information can be found below:

NSF Research Traineeship: Data-Driven Discovery, and Engineering from Atoms to Processes (3DEAP)

This National Science Foundation Research Traineeship program bridges chemical, biological, and materials engineering with data science and systems engineering, through convergent education and research and industry-university collaboration.   

The 3DEAP NRT comprises:

  • An integrated graduate curriculum that teaches the fundamentals of data science and their domain application. This curriculum will leverage and build on the newly established coursework-based M.S. degree in Data Science for Chemical Engineering and Materials Science (MSDS CEMS) launched by CEMS.
  • A collaborative, interdisciplinary research program that addresses holistically challenging problems in chemicals and materials discovery and design as they relate to energy, sustainability, and health. Typical research projects will combine atomistic simulations, data science, systems engineering, and experimental methods to build models that integrate multiple data sources and scales and to address product discovery and synthesis along with process design and optimization.
  • An industry-university collaboration framework, comprising design and research projects, internships, an industry-academia forum, and a short course for industry.
  • A suite of coordinated training activities aimed at improving skills necessary for competency in the workforce. These include communication, leadership, project management, ethics, mentoring, teamwork, cultural competency, and mental health awareness.
  • An outreach and recruiting program that will focus on students from socio-economically disadvantaged and/or low-level educational populations attending undergraduate programs in the Twin Cities metro area


Core Participants 

  • Prodromos Daoutidis (CEMS), Director
  • Sapna Sarupria (CHE), Associate Director
  • Chris Bartel (CEMS)
  • Natalie Boehnke (CEMS)
  • Emily Goff (Goff Group) 
  • George Karypis (CS)
  • Theresa Reineke (CHE)
  • Ilja Siepmann (CHE)
  • Ellad B. Tadmor (AEM)
  • Qi Zhang (CEMS)
     

Funding from the 3DEAP program is available to Ph.D. students with interests in materials and chemical/biochemical engineering research. Funding awards will be made for one year, with the possibility of renewal for one more year. 3DEAP will also incorporate (in an unfunded capacity) students pursuing an MSDS CEMS as a terminal degree as well as other Ph.D. students from our departments doing research related to data science.