Bradley Dice, one of our current MolSSI Software Investment Fellows, is now completing his PhD in Physics and Scientific Computing at the University of Michigan with Prof. Sharon C. Glotzer, who is a former member of our Sciences and Software Advisory Board (SSAB)! Bradley is working with Dr. Doaa Altarawy on developing powerful parallel analysis tools for studies of soft matter, nanoparticles, and colloidal self-assembly.
I found my way to computational molecular science through a series of interests in programming and digital image processing (motivated by helping my father’s photography business), a desire to understand the physics engines of video games, and high school chemistry teachers who helped mold my interest in math into a pursuit of scientific research in college and graduate school.
The community of MolSSI Software Fellows bridges many fields, from biological materials to quantum chemistry. Being a part of this interdisciplinary group allows us to share best practices and learn from common experiences in the process of designing research software that serves the scientific community.
Doaa Altarawy’s emphasis on user-centered software design has helped me learn to create scientific tools that are intuitive and helpful for researchers in fields beyond my own. Though my project freud focuses on analysis of nano-scale particle systems, its implementations of tools from statistical physics have been broadly applied, including in studies of the layouts of buildings in urban settings and the characterization of crystallinity in brain matter. Interested readers can find more information about freud here, or via the project repository.
After my PhD, I’m excited to apply my passion for GPU computing and high-performance scientific software as a part of NVIDIA’s RAPIDS AI team (https://rapids.ai/). I’ve used RAPIDS’ open-source libraries for data science and machine learning in my own research, and I look forward to building the next generation of GPU powered computational tools for researchers to approach large datasets with ease.
I enjoy playing jazz piano and DJing electronic (house) music!
I find the most fulfilling part of science is sharing the feeling of discovery with a younger student or mentee. I’ve really enjoyed the opportunity to work with several exceptional undergraduate students on projects while in graduate school..
Making music or going for runs with Chad, my chocolate Labrador Retriever.
I’m really interested in how researchers manage their data. I maintain a software framework called signac (https://signac.io/, named after the pointillist painter) that helps researchers manage their data and automate computational workflows (data points, if you catch the metaphor). There are now several frameworks for assisting large-scale computational studies, and I’d like to study common practices in computational science that can improve productivity, data quality, and reproducibility.