M.S. Computer Science, Georgia Institute of Technology, 2012
B.S. Computer Science, Eckerd College, 2008
Ms. Borck is a SIFT senior researcher specializing in Artificial Intelligence. Her expertise includes prediction, recognition, and goal reasoning. She joined SIFT in 2020 with 10 years experience in small business AI research. In previous work as she designed and validated a Case-Based Reasoning (CBR) action prediction system using video from an AR device. Her previous projects also include behavior prediction and recognition of UAVs in beyond visual range combat. She has a breadth of expertise within the AI community including contributing and publishing on projects on program diversification for fault tolerant systems, automated test generation for cyber-physical systems, and generation of synthetic datasets for optical character recognition.
Ms. Borck is an expert in CBR and has published and served on organizing committees for conferences within the CBR community. She has served as the chair for the workshop on Evolutionary Computations and Case-Based Reasoning at the International Conference on Case-Based reasoning (ICCBR) 2018, the co-chair for the ICCBR workshop program for 2019-2021, co-chair of the CBR track at the Florida AI conference (FLAIRS) 2019 and 2020, and on the reviewing committee for various AI conferences and workshops including ICCBR, FLAIRS, ACS, and the goal reasoning workshop at IJCAI since 2016. She won the best poster award at the International Conference on Software Analysis, Evolution, and Reengineering (SANER) 2016 and the best video award at ICCBR 2017 and 2018.