Avinash Kori

Avinash Kori

Ph.D Researcher on XAI and Causality

News

  • March 2022: [Paper Submission] Paper submitted to MICCAI on model robustness and quantization

  • Oct 2021: Joined PhD at Imperial

  • April 2021: [Paper acceptance in Scientific Reports]

  • Feb 2021: [AAAIw Overall Best Paper] Our work on CNN Interpretability won Overall Best Paper Award

  • Feb 2021: [AAAIw Spotlight Presentation] Our work on CNN Interpretability got accepted in W3PHIAI for spotlight presentation.

  • December 2020: [Extended the work on Symbolic Regressor to classification tasks] Repo. and report: https://github.com/koriavinash1/Symbolic-Pursuit

  • November 2020: [Abstracting Deep Neural Networks into Concept Graphs for Concept Level Interpretability] Paper submitted to AAAIw, arxiv version: https://arxiv.org/pdf/2008.06457.pdf

  • Octobar 2020: [A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis] Paper submitted to Medical Image Analysis (MedIA), Computational Pathology

  • September 2020: [Graduated from IIT Madras] Completed my Dual Degree program at Indian Institute of Technology, Madras

  • January 2020: [Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches] Paper accepted in Frontiers in Neuroscience, Brain Imaging Methods

  • January 2020: [Demystifying Brain Tumour Segmentation Networks: Interpretability and Uncertainty Analysis] Paper accepted in Frontiers in Computational Neuroscience

  • January 2020: [Release of PyPi] Released python package for Neural Field Modelling (nfm)

  • November 2019: [Release of PyPi] Released python package for Explainability of Biomedical model (BioExp)

  • November 2019: [Release of PyPi] Released python package for deep learning based solution for histopathology analysis (DigiPathAI)

  • October 2019: [MICCAI Oral Presentation] Winning technique Presentation: for digestpath Signet-ring cell detection

  • October 2019: [Paper in MedIA] Paper accepted in Medical Image Analysis: IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge

  • September 2019: [Release of PyPi] Released python package for deep learning based solution for brain tumor segmentation

  • May 2019: [Research Internship] Visiting research internship at Stanford University (Poldrack Lab, Department of Psychology)