Diverse Descriptions of Experimental Practice as Supports for Learning. - Michael J. Ford (ICLS, 2004)

Writing Competitive Proposals for Programs in NSF's Division of Research in Learning in Formal and Informal Settings. - Ellen McCallie; Christopher Hoadley; Michael J. Ford (ICLS, 2014)

Impressive computational acceleration by using machine learning for 2-dimensional super-lubricant materials discovery. - Marco Fronzi; Mutaz Abu Ghazaleh; Olexandr Isayev; David A. Winkler; Joe Shapter; Michael J. Ford (CoRR, 2019)

Soft Magnetic Tactile Skin for Continuous Force and Location Estimation Using Neural Networks. - Tess Lee Hellebrekers; Nadine Chang; Keene Chin; Michael J. Ford; Oliver Kroemer; Carmel Majidi (IEEE Robotics Autom. Lett., 2020)

Active Learning in Bayesian Neural Networks for Bandgap Predictions of Novel Van der Waals Heterostructures. - Marco Fronzi; Olexandr Isayev; David A. Winkler; Joseph George Shapter; Amanda V. Ellis; Peter C. Sherrell; Nick A. Shepelin; Alexander Corletto; Michael J. Ford (Adv. Intell. Syst., 2021)

Accurate prediction of the properties of materials using the CAM-B3LYP density functional. - Musen Li; Jeffrey R. Reimers; Michael J. Ford; Rika Kobayashi; Roger D. Amos (J. Comput. Chem., 2021)