by Hangjie Ji, Duke University
~ I have found that it is very easy for graduate students to get immersed in their own filtered and narrowed research area without thinking about how to use their expertise in other applications. During my Ph.D. study in mathematics I was an active participant in several industrial workshops where graduate students have the opportunity to work in teams on real problems. In this post I will share my experiences at these workshops.
First of all, these workshops provide an industrial-like environment quite different from the usual academic setting. In the Mathematical Problems in Industry (MPI) series organized by Duke University, University of Delaware, NJIT and other institutes, engineers and scientists from industry introduce challenges that they face in business and the workshop participants form groups to tackle the problems. The initial proposed problems could be ill-posed in the mathematical sense, and require careful clarification and formulation to build workable models. During the weeklong workshop professors, postdocs, and graduate students work together, and usually spend at least the first two days on resolving the confusions of the problem setup and terminologies by communicating with the industrial participants. Once the mathematical model is established, various methods that we have learnt from our own research can then be applied to the problem, and the group members usually form smaller teams to tackle the problem from different perspectives. While at first it seems a little intimidating to speak up in front of a group of senior professors, observing the way people think and discuss is actually a very good learning experience for me, and junior mathematicians do contribute lots of fresh insights to the problems. At the end of the week, each team would present their results and it always amazes me how much work can be accomplished in a single week. One of my favorite moments of the final presentation is a display of Colemanballs quotes or bloopers that happen during the workshop like “F is so big it has to be zero!”
The other two modeling camps that I have participated in are designed for graduate student career development in interdisciplinary problem solving skills. At the Graduate Student Mathematical Modeling Camp (GSMMC) at Rensselaer Polytechnic Institute where graduate student teams get together to solve real problems that arise from industrial applications under the guidance of invited faculty mentors. These modeling camps are usually held one week prior to the MPI workshops, and part of the goal is to better prepare the grad students for the coming MPI workshop, as the weeklong collaboration with team members in a friendly and productive environment quickly adjusts us to more challenging projects at MPI. Another workshop that I participated in, the Industrial Mathematical and Statistical Modeling Workshop (IMSM) is sponsored by the Statistical and Applied Mathematical Science Institute (SAMSI) and NC State University and focuses more on data-driven industrial projects. In the IMSM workshop I worked with a group of seven graduate students from different universities on a project proposed by costal engineers from United States Army Corps of Engineers Costal Lab, and our goal was to estimate the underwater bathymetry in environmental flows. Using the measurement data from several sources and statistical learning methods, we successfully incorporated the data to a wave model that leads to reasonable estimates. In addition to the interesting results that we worked out for the projects, I am also really happy with the training that I received during the workshop on technological tools like Git repository and Python, handling unfiltered dirty data with simulations, and perhaps most importantly, scientific communication skills. For instance, learning how to speak with a costal engineer during the IMSM project turned out to be not so easy. Getting exposed to these skills, or at least being aware of the new tools people are using in industry, is very beneficial for PhD students who have interests in pursuing an industrial career after graduation. The projects during these workshops have always been nice talking points in my conversations with industrial people, and I believe that similar experiences could naturally contribute to a sparkling resume for potential employers as it shows interest and passion outside of one’s academic research work.
As a summary, my personal experience at these workshops has been consistently rewarding and enlightening. I have learnt a lot and have explored areas way beyond my expectation. As an extension of the MPI workshop, I worked on a side project in collaboration with Corning Inc. under the 2015 MPI Fellowship, and presented my results at the 2016 MPI workshop and in a research paper. Two years later, I am still in continuous contact with friends that I met during the first few workshops that I attended, and the connections that we built in those weeks were truly incredible and unforgettable. I am really grateful to the organizers and sponsors who made these workshops possible, and would like to encourage my fellow graduate students to grasp opportunities like these to explore the links between applied mathematics and problems of interest to industry, and to learn more about their own interests.
Photo: Group work session
For more info: https://services.math.duke.edu/conferences/mpi2016/