Projects

Community Programs

I enjoy creating or leading programs that help expand the CS community at every level. Programs I have developed or actively maintain include:

  • High School Summer Research Program. Since 2022, this annual program provides research opportunities for local area high school students by matching pairs of students to a faculty mentor. Students in the program receive direct mentorship from faculty members and have access to both regular social events as well as summer seminars to expand their knowledge on a variety of research related topics.
  • CS Summer Research Program. The SRP annually admits students from all over the world to take part in summer research with CS-affiliated faculty. In addition to the core research experience, the SRP includes networking and social events, weekly lunch seminars, and a capstone research symposium.
  • Trick or Research. This annual research showcase gives researchers an opportunity to share their work with students interested in exploring computing and data science research opportunities.
  • Undergraduate Research in Scientific Advancement (URSA). The URSA Research Program is an interdisciplinary program in the College of Engineering pairing freshman and sophomore undergraduates with research mentors. The general goal of the program is to encourage underclassmen to explore research at an early stage in their academic career and are given the opportunity to present their work in an end-of-semester poster symposium.
  • Illinois Summer Teaching Workshop. Because faculty need communities too! Since 2021, this annual workshop has brought together hundreds of college instructors involved in CS teaching or pedagogy in a two-day workshop.

Pedagogy Research

I am primarily interested in developing methods, tools, and pedagogical approaches for large-scale CS education. Currently my research projects include:

  • PrairieLearn for Theoretical Computer Science. The focus of this research endeavor is to develop better automated assessments and practical exercises for teaching CS theory at scale. This work is funded by a UIUC SIIP grant and is being developed alongside other CS faculty, headed by Jeff Erickson.
  • Accessible Education. Many of the projects I have built focus on broadening participation in computing. As part of continued efforts to expand or improve these programs, I work to assess the success of various mentorship or outreach efforts through surveys, focus groups, interviews, and various quantitative data measures.
  • Scalable Data Science Projects. I have been a strong advocate for the benefits of team projects throughout my teaching career. However, it is difficult to scale manually graded assessments to classes consisting of multiple hundreds to a thousand or more students – a regular problem for many classes at UIUC. Currently I am exploring approaches to improving a single team final project in CS 225 and approaches to combine autograded assessments with open ended student submissions (which I call ‘mini-projects’) in CS 277.

Computational Biology Research

My research background was based around developing methods and software that improve scientists’ abilities to store, search, and analyze large data collections. This included computational theory work, practical open-source software, and replicable analyses on genomic indices. Although I am primarily interested in pedagogy and program development, I do still undertake limited research projects with undergraduates interested in genomics research. Select publications include:

  • Brad Solomon, and Carl Kingsford. “Fast search of thousands of short-read sequencing experiments.” Nature biotechnology 34.3 (2016): 300-302.
  • Brad Solomon, and Carl Kingsford. “Improved search of large transcriptomic sequencing databases using split sequence bloom trees.” International Conference on Research in Computational Molecu- lar Biology. Springer, Cham, (2017).
  • Guillaume Marçais*, Brad Solomon*, Rob Patro, and Carl Kingsford. “Sketching and sublinear data structures in genomics.” Annual Review of Biomedical Data Science (2019). *Co-first author
  • Nae-Chyun Chen, Brad Solomon, Taher Mun, Sheila Iyer, and Ben Langmead. “Reference flow: reducing reference bias using multiple population genomes.” Genome biology 22, no. 1 (2021): 1-17.
  • Christopher Wilks, Shijie Zheng, Feng Chen, Rone Charles, Brad Solomon et al. “recount3: sum- maries and queries for large-scale RNA-seq expression and splicing.” Genome biology no. 1 (2021): 1-40