Audrey St. John specializes in theoretical computer science, with her research focusing on the "rigidity theory" of structures motivated by applications such as robotics, computer-aided design (CAD) and computational biology. In 2013, she received a Faculty Early Career Development (CAREER) award from the National Science Foundation (NSF) to develop a Rigidity Theory for Multi-Robot Formations. St. John's commitment to broadening participation in computer science and STEM at large is demonstrated through curricular development and co-curricular activities. She is a co-PI on a Google Computer Science Capacity Award for the MaGE: Megas and Gigas Educate peer mentorship program and is involved in the newly established Makerspace.
St. John enjoys the interdisciplinary nature of her research — the core theory spans computer science and mathematics while the applications range from engineering to biology, allowing her to collaborate with faculty from other disciplines and students with varying interests. Her NSF CAREER award supports research towards developing algorithms for autonomous control of multi-robot formations, motivated by scenarios such as search-and-rescue where collective transport of objects is required. St. John’s involvement in the NSF-funded Four College Biomath Consortium (4CBC) gives her the opportunity to work on computational methods for analyzing the flexibility of proteins, which has applications in drug design.
Having discovered computer science in college herself, St. John works to broaden participation in the field and the tech community at large. She believes engaging and challenging curriculum can empower students to reimagine their own interests and pathways and seeks to infuse excitement and ownership of the material in the courses she teaches. A 2015 recipient of the Mount Holyoke College Faculty Award for Teaching, St. John applies this philosophy in introductory-level courses (e.g., COMSC 101: Problem Solving & Object Oriented Programming and COMSC 201: Advanced Object Oriented Programming) and upper-level courses (her favorite is COMSC 311: Theory of Computation). It has also inspired her to create new courses, such as COMSC 106: iDesign Studio, created for students that might see themselves as “tech-phobic” and is now part of Makerspace programming. In addition, she is actively involved in co-curricular programming, including the development of MaGE with PI Heather Pon-Barry and co-PI Becky Wai-Ling Packard. This academic peer mentorship program centers on a rigorous training course to prepare students to become effective mentors equipped to create an inclusive learning environment for their peers.
Selected news links
- “Computing for social impact,” MHC News, April 2017
- “BCC Hacks: Students, engineers set to hack new ground,” The Berkshire Eagle, May 2016
- “Tech-tinkering class: A STEM gateway,” MHC News, September 2015
- “The Power of Undergraduate Researchers,” AMS Blog on Teaching and Learning Mathematics, April 2015
- “Google funds new computer science initiative,” MHC News, March 2015
- “Less Geek, More Chic,” Clare Boothe Luce Momentum (inaugural edition), Spring 2014
- “Embracing Change: Mount Holyoke women lead in ways big and small,” MHC Alumnae Quarterly, November 2013
- “Major NSF Grant Funds Robotics Research,” MHC News, September 2013
(* indicates undergraduate author)
- Alyxander Burns*, Bernd Schulze, Audrey St. John. Persistent Multi-Robot Formations with Redundancy. In Proc. of 13th International Symposium on Distributed Autonomous Robotic Systems (DARS ’16), 2016.
- Heather Pon-Barry, Audrey St. John, Becky Packard, Barbara Rotundo. Megas and Gigas Educate (MaGE): A Curricular Peer Mentoring Program. Poster in Proc. of 47th ACM Technical Symposium on Computing Science Education (SIGCSE 2016), Memphis, TN, 2016.
- James Farre*, Helena Kleinschmidt*, Jessica Sidman, Audrey St. John, Stephanie Stark*, Louis Theran, Xilin Yu*. Algorithms for detecting dependencies and rigid subsystems for CAD. Computer Aided Geometric Design, 47: 130-149, 2016.
- Rittika Shamsuddin*, Milka Doktorova*, Sheila Jaswal, Audrey Lee-St.John and Kathryn McMenimen. Computational Prediction of Hinge Axes in Proteins. BMC Bioinformatics, 15(8), 2014.
- Audrey Lee-St.John and Jessica Sidman. Combinatorics and the Rigidity of CAD Systems. Computer-Aided Design 45(2):473-482, 2013. (Best Paper Award, Symposium on Solid & Physical Modeling, Dijon, France, October 2012.)