As a D3EM fellow, I feel it is necessary to compliment the D3EM curriculum because I have benefited from D3EM significantly. However, I also feel it is necessary to give an honest and unbiased opinion on D3EM as a whole. Below is my opinion on each aspect of D3EM.
MSEN 655 – Materials Design Studio:
A capstone project course to solve a research problem with and interdisciplinary approach. The course covered the materials-as-designed-system (Olsen), sampling methods, robust design, and multi-objective optimization.
The project chosen was to use machine learning to predict material properties of shape memory alloys given a large experimental database. This course is, in my opinion, the most valuable and important course to the D3EM curriculum. It teaches students the value in everything they have learned in other courses by allowing the student to work on a research project with an interdisciplinary approach to the problem. Without this course, the curriculum would look like every other “multi-disciplinary” curriculum in that the courses are disconnected from each other. The materials design studio is the “glue” of D3EM. I feel the course material and lectures are overshadowed by the project and unless I immediately applied a lecture to my project, the material wasn’t revisited. Luckily, most material in this course is able to be applied to the project.
MSEN 689 (II) – Materials Informatics:
Introduction to machine learning concepts such as LDA, kNN, deep learning with images using CNNs, and more.
This course was a great supplementary course to my research. Learning about machine learning from a professor in Electrical Engineering department also gave me a better perspective on the applications outside of materials science. However, if I were not doing any artificial intelligence or machine learning based research, this course may have been more difficult and much less enjoyable. I believe the professor was great and the assignments were very good for allowing students to dip their toes into the great sea of data analytics. I personally feel there should be two courses dedicated to data analytics and artificial intelligence. One could deal with classification and regression problems (and basic statistics) and the next course can deal with unsupervised learning, neural networks and deep learning.
MEEN 601- Advanced Product Design:
In this course, we learned about Pareto fronts and multi-objective optimization for design.
The project my team and I participated on was biomechanical energy harvesting. In particular, we wanted to design a device that would have high energy output and was lightweight for military applications. This course was one of my favorites in content, but one of my least favorite for the project. The course is very well structured and the professor was very enthusiastic about the material he was teaching. The project portion of the course rapidly became a challenge. Whenever there is an interdisciplinary project between students (6 different students with a wide variety of backgrounds) it is harder to tell who is not contributing. It was disappointing because the project idea was so interesting and we could have delivered more. If I took the course again, I would have went with the minimum number of students for the group because communication would have been much easier and roles would have been easier to define.
Coffee talks are a way of bringing the D3EM students and faculty together to discuss various topics. The students would vote on the topic they were interested in and often a guest speaker or faculty member would come discuss the topic. I enjoyed getting to meet with other students and faculty that all share similar interests as myself. Many of the topics were very interesting and we all got to share different apps, sources, and tools we use to get through everyday life in academia. We had some talks on job applications which were extremely useful. However, there were some talks in which I would have rather skipped. Although I value opinions and ideas from everyone in the D3EM community, some topics were too personal while others were completely unrelatable. Also, I found myself sometimes not wanting to give any input out of fear it might be invalidated by someone. Topics such as work-life balance, organization, and networking are not one size fits all. Instead of discussing these topics, I think it would be more beneficial to discuss topics that have a less controversial answers such as tools for writing or learning.
The learning community was one of my favorite parts of D3EM. The learning community felt like I was being given tools of the trade from experts in networking, learning, and communication. These sessions were the closest that you can get to cheat codes for life. Such a seamless implementation of the lecture material into daily routine is what makes the Learning Community so valuable. Once you learn “the trick”, seemingly difficult tasks seem more much more manageable.
The writing community has to be the most valuable part of D3EM. As a graduate student, it is imperative to write and write well. Often times the hardest part of writing is starting. This community makes you to feel accountable to produce words, paragraphs, and eventually pages every week to make sure you stay on top of your writing. The structure, technicality, and throughput of my scientific writing has improved because of this writing community.