Akshit Achara

King's College London, UK

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I am a doctoral candidate associated with the Motion Modelling & Analysis Group at King’s College London supervised by Prof. Andrew King, Prof. Alexander Hammers and Dr. Esther Puyol Antón. My interests broadly lie in all aspects of deep learning. I am currently working on fairness in deep learning with special focus on medical imaging. Specifically, I am interested in invariant representation learning for fairness, bias attribution using interpretability methods and fairness metrics.

Previously, I was a Research Engineer at GE Healthcare, Bangalore, India where I primarily worked on NLP approaches for timeline based report summarisation.

In my spare time, I play sports (primarily Cricket and Football), listen to music and catch-up with my friends.

I am always looking for research collaboration on fundamental problems in deep learning. Feel free to email me!

news

Jan 22, 2025 Our paper entitled “Watching the AI Watchdogs: A Fairness and Robustness Analysis of AI Safety Moderation Classifiers” has been accepted at the NAACL 2025 Main Conference. I am grateful for the mentorship I received from Dr. Anshuman Chhabra.
Oct 1, 2024 I have started my PhD with the Motion Modelling & Analysis Group group at King’s College London as a part of the DRIVE-Health programme. I will be exploring algorithmic fairness in medical imaging.
Jun 25, 2024 Our paper entitled “Efficient Biomedical Entity Linking: Clinical Text Standardization with Low-Resource Techniques” has been accepted at the BioNLP Workshop @ ACL 2024.
Jan 11, 2024 Our paper entitled “Revealing the Underlying Patterns: Investigating Dataset Similarity, Performance, and Generalization” has been published at Neurocomputing.
Dec 8, 2023 Our paper entitled “TrueDeep: A systematic approach of crack detection with less data” has been published at Expert Systems with Applications.
Jun 30, 2023 Our paper entitled “CoreDeep: Improving Crack Detection Algorithms Using Width Stochasticity” has been accepted at CVIP, 2023.