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In your final semester, you will enroll in CHEM 283: MSSE Capstone Project. This project is a course that is taken for credit - however, you will begin the process of thinking about and planning for your capstone before the semester actually begins. Your cohort will meet with Dr. Tony Drummond, the faculty member in charge of the capstone, in the Fall semester to discuss the requirements in depth and brainstorm your own project. This page is meant to give a general overview of the project requirements so that you can begin to think about what type of project you may want to pursue. Once enrolled, please refer to the bCourses page for the most up-to-date information and assignments. For frequently asked questions, click the button below.
Description
The primary objective of the capstone course is to provide MSSE students with a multifaceted experience managing a project of their choice involving the application and development of high-end computational software for computational science with an emphasis on molecular science. Students will exercise their leadership and team-building skills through individual class assignments, peer reviews, and a final capstone project report. The capstone project is an essential part of the MSSE program because it provides students with the opportunity to apply the skills learned in other MSSE courses in the real world. The capstone project will also provide MSSE students with professional networking opportunities; students may choose to work on a project with a company of their choice or a project with one of MSSE’s industrial and academic partners. This course is designed to be tightly integrated with MSSE Leadership Bootcamp, which MSSE students will undertake in their final weeks of the MSSE program. During the Leadership Bootcamp, students will build upon their capstone projects to practice entrepreneurial and leadership skills.
MSSE students have the option to work on their capstone projects either individually or with cross-functional teams. In either case, all work in this course will be submitted individually, and students working within a team will have a predetermined set of deliverables and responsibilities. This course is designed to provide students with tools and practices for designing project deliverables, planning and meeting project deadlines, giving presentations, writing technical communications, and providing constructive feedback to peers. Finally, students will complete a professional MSSE software portfolio, which meets software engineering best practices.
Tracks
Given the wide variety of student backgrounds, professional interests, and computational science topics covered in the MSSE program, the capstone projects will be classified into one of the following three professional interdisciplinary tracks:
Scientific Problem. A project on this track focuses on the research and development of a computational science application. Students understand the scientific problem at hand and the impact that their project will have in a particular field of science.
Large Scale Computing. A project on this track focuses on the development of large-scale software libraries, tools, or computational applications relevant to molecular science. Students understand the need for scaling a given computational application, the computational complexity of applications and key kernels, and the impact that the project deliverables will have in a particular field of science.
Software Engineering and Algorithms. A project on this track focuses on the development of a library or software package for computational sciences applying the best practices of software engineering and covering all elements of the software engineering cycle. Students understand the need for such a library or service to the computational science community.
Deliverables
All capstone projects regardless of the track chosen will result in four deliverables: (1) A pre-proposal and proposal that contain written descriptions of the project, deliverables, and plan; (2) Professionally written assignments and project assessment reports. Students work on six assignments during the Capstone Project course; (3) the Capstone Project presentation; and (4) the MSSE Professional Software Portfolio. In addition to these four deliverables, each track requires several additional products outlined below.
Scientific Problem. (1) A publication-quality research paper that follows the standards for publication in a computational sciences journal or well-regarded conference in the field; and (2) Results need to be reproducible. Data and scientific evidence of the results need to be presented and published.
Large Scale Computing. (1) A software package with corresponding documentation, computational scalability analysis, and scientific relevance of the accomplishments; (2) A publishable research paper in a high-performance computing journal or well-regarded HPC conference; and (3) Results need to be reproducible and all source programs included in the Software Portfolio.
Software Engineering and Algorithms. (1) A high-quality software package, well documented, and integrates relevant auto-tests, examples, and user interfaces. Complexity Analysis; (2) The product is a software package that can be distributed and maintained through a widely available software repository (i.e. GitHub, GitLab, etc); and (3) Results need to be reproducible and all source programs included in the Software Portfolio.
Schedule
Getting Started
Late Summer / Early Fall
Choose one of the tracks described above. Brainstorm project ideas and potential partners.
Meet with Dr. Drummond to discuss your ideas.
Formally identify a field expert who can provide you with technical feedback during your project. This could be a supervisor at your own place of work, an industry partner, a technical advisor, or a UC Berkeley faculty member. The supervision of a Capstone project requires a senior scientist or manager. A graduate or undergraduate student cannot be a Capstone project supervisor. Check with the Capstone project faculty on the suitability of an individual to be a Capstone project supervisor.
Late Fall / Early Spring
Write a Capstone project description, make sure you provide the following details:
Technical and scientific benefits of the project, (i.e. Why is this unique and relevant today? Why is it needed?).
Whenever applicable, detail the expectations from your employer and supervisors.
Make sure the project fits in one of the Capstone project tracks, that you will be able to present, and that there are no foreseeable hurdles for you to complete all deliverables. Check your company’s intellectual property and non-disclosure agreements (this may include who has access and can view the data and source codes). When applicable, consult your employer.
Submit the Capstone project description to the Capstone project faculty for review.
Investigate whether there are any restrictions to you presenting your project (including relevant data) to the public. It is possible that your project supervisor may not allow you to publish results without clearance or prior approval. Find out about any restrictions ahead of time, and make sure that you will be able to present your final project. In the event of proprietary data, investigate whether you can use alternative datasets or standard testing datasets to be able to demonstrate the scientific relevance of your project and publish the results.
Important Notes
If your Capstone project involves work with your employer, please note that MSSE students cannot be remunerated for their Capstone project work.
If you are interested in working in a group with classmates, check the Capstone Project FAQ for information on Cross-Functional Teams.
Past Projects
If you have any questions about the Capstone Project, email msse@berkeley.edu.
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