Aishwaryaprajna worked as a postdoctoral research fellow in the Trustworthy Artificial Intelligence Lab at Ontario Tech University. She is interested in developing computational self-awareness to enable reflective artificial intelligence, targeting increased trustworthiness of AI systems.

Aish did her PhD at School of Computer Science, University of Birmingham, UK. Her doctoral research focuses on understanding the performance of evolutionary and voting recombination mechanisms in solving combinatorial optimization problems when large levels of noise are present in the optimization process. Several noise models existing in optimization and learning scenarios have been investigated. Her novel voting algorithm provides state-of-the-art performance in solving a combinatorial benchmark in presence of noise.

She worked at Department of Electrical and Computer Engineering, McMaster University, Canada for a research collaboration during her PhD, funded by Birmingham Global U21 PhD scholarship during summer 2020. The research focused on efficient path planning of Unmanned Aerial Vehicles in presence of occlusions resulting from weather factors, with multi-objective evolutionary algorithms.

She moved on from the lab in 2023, to take up a position as a Lecturer in Artificial Intelligence at the University of Exeter, UK.