Carnegie Mellon University’s Mellon College of Science (MCS), one of PSC’s home institutions, announced in March the launch of a new degree program that serves as an exciting opportunity for students, faculty, and staff alike. The Master of Science in Data Analytics for Science (MS-DAS) degree is specifically designed for students with a background in the foundational sciences such as biology, physics, math, chemistry and related fields, and it aims to provide students with data science skills that are vital to any scientific career today.
This program is the result of a collaborative effort between MCS faculty and staff and PSC staff, and it will continue to be a collaborative effort throughout its lifespan. The development of the program was led by Physics Professor Manfred Paulini, who serves as the MCS Associate Dean for Faculty and Graduate Affairs. Professor Paulini led a group that featured experts from various disciplines, all of them with experience working with students in the sciences.
Members of PSC staff played an integral role in designing the curriculum for the program, and will continue to be part of the program as members of the faculty. Students will get a chance to work on the Bridges-2 platform as part of their coursework – a unique and extremely valuable experience. This is the first time PSC is formally integrating into the CMU curriculum, as told to us by John Urbanic, a Parallel Computing Scientist at PSC and one of the lead coordinators for the center on the MS program. John leads PSC-hosted XSEDE educational programs as an instructor, and teaches in the CMU Physics department.
As John put it, scientists right now are “trying to embrace big science and data analytics technologies because they aren’t just popular, they are effective.” He’s excited for the launch of the program, and to see it grow, due to what he sees as a need for this type of education in the scientific community. In his opinion, the MS-DAS gives students the tools they need to succeed in the real world, whether they follow a research or industry path.
As part of the MS-DAS, students will get to work with John, plus Senior Scientific Specialist Joel Welling, Director for AI & Big Data Paola Buitrago, and Director Shawn Brown. These PSC experts all bring their own teaching and big data experience to the table, and have perspectives to offer these graduate students that they can’t get anywhere else. They will help students use the Bridges-2 platform in their coursework, thus enabling them to, as John puts it, “leap off of laptops.”
According to John and Shawn, they want to show the graduate students the utility of the next level of computing, beyond using their laptops that have gotten them through their undergraduate studies. As John explained, nowadays, cutting-edge research that results in published work tends to be research that was enabled by supercomputers. The work that some of these students will be interested in, which John is familiar with due to his years of teaching, will be enhanced and brought to new heights on a supercomputer. Remaining on a laptop to complete their courses, he says, would be akin to “trying to do particle physics with an 18th century microscope.”
Here at PSC, we know the value of supercomputing. But, this program is a confluence of our machinery with not just our expertise, but more importantly the expertise of our incredibly talented CMU colleagues, taking advantage of existing synergies for the benefit of MCS students who have the potential to become the next class of published researchers. Hopefully, they’ll do so working on big data projects utilizing PSC machines, if John and Shawn have anything to say about it.
PSC and CMU have worked together on numerous projects over the years of our partnership, but this is the first time the two have collaborated to set up a long-term academic program. Our team is excited to be part of this program and see how it flourishes, and to continue expanding and improving the program for the benefit of the students.