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Computer Science

Dr . Aishwaryaprajna

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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 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 

Prospective PhD students, please get in touch through email!

 

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