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Dr . Aishwaryaprajna (she/her)
Lecturer
Computer Science
Dr. Aishwaryaprajna joined the University of Exeter as Lecturer in Computer Science (Education & Research) at the Faculty of Environment, Science and Economy in December 2023. Her research concerns the modelling of AI systems. She holds a bachelor’s and master’s in Mathematics, enabling her to explore the theoretical foundations and applied aspects of AI systems.
Her PhD from the School of Computer Science, University of Birmingham, was on noisy combinatorial optimisation with evolutionary computation. Her PhD established the superior performance of recombination-style heuristic operations in simple, constrained and multi-objective combinatorial problems in the presence of noisy fitness evaluations. Her PhD thesis discusses the runtime bounds of a novel Voting algorithm for solving combinatorial benchmarks in the presence of several noise models prevalent in machine learning scenarios. She received the U21 Birmingham Global Scholarship for a collaborative visit to the Department of Electrical and Computer Engineering, McMaster University, Canada, during her PhD to perform research on a multi-objective combinatorial optimisation problem for finding the surveillance path of Unmanned Aerial Vehicles (UAVs) with resource constraints and uncertainty arising due to weather factors.
She was a Postdoctoral Research Fellow at the Trustworthy AI Lab, Ontario Tech University, Canada, where she worked on self-aware multi-agent systems for sustainable foraging that have reflection capabilities on past behaviour and actions.
She is also interested in applications of AI systems in healthcare. She worked on clinical decision support systems for cancer susceptibility while working with interdisciplinary teams of healthcare professionals and bioinformatics experts associated with the School of Medical Science and Technology, Indian Institute of Technology Kharagpur.
Research Interest Keywords:
- Modelling AI Systems for Decision-Making
- Evolutionary Computation
- Analysis of Algorithms in ML and Optimisation
- Multi-Objective Optimisation
- Uncertainty Handling
- AI Applications to Healthcare
- Self-Aware Multi-Agent Systems
Current PhD Students:
- John Payne (Started September 2024)
- Varun Kulkarni (Started September 2025)
- Miles Rowbottom (Started September 2025)
Prospective PhD students, please get in touch via email!
- Machine Learning & Evolutionary Computation for Climate Model Emulation (In collaboration with Met Office and British Antarctic Survey) funded by NERC GW4+ Doctoral Training Partnership https://www.exeter.ac.uk/study/funding/award/?id=5744
- Evolving World Models: Learning the model of the world for Self-Adaptive and Autonomous Systems using Evolutionary Reinforcement Learning Techniques - funded by EPSRC Doctoral Landscape Award (apply here)
- China Scholarship Council Funding (https://www.exeter.ac.uk/study/funding/award/?id=5727 ) for projects such as Visualisation and Landscape Analysis Methods for Noisy Combinatorial Optimisation Problems in Machine Learning; Causal Deep Learning Models for Medication Treatment Outcomes in Patients with Heart Failure and Associated Comorbidities; Evolutionary Reinforcement Learning for Large-Scale Scheduling Optimisation;
