Document Type

News Article

Abstract

I work in the broad areas of computational intelligence, artificial intelligence, neural networks, machine learning, deep learning, game theory, mathematical logic, and natural language processing. I am also actively working in the area of algorithmic fairness and explainable AI (XAI). Currently, we are developing neuro-symbolic logic learning systems for common sense reasoning, which aims to augment the existing conventional artificial intelligence, which is logically based. The neuro-symbolic logic-based systems will provide more accurate results than their GOAI (Good Old Artificial Intelligence) version. We are also working on the area of abstractive summarization methods. We intend to develop an efficient abstractive summarization model which overcomes the metric level limitation of the existing evaluation metric for the abstractive summarization model and produces abstractive summaries which are at par with the summaries generated by humans. We are also developing a suitable model and framework for autonomous vehicles that are robust to adversarial attacks. There are specific common working grounds in game theory and machine learning. We are exploring to come up with a framework that exploits the power of game theory and machine learning.

  1. https://www.sciencedirect.com/science/article/pii/S1568494622002897
  2. https://ieeexplore.ieee.org/document/9513266
  3. https://link.springer.com/article/10.1007/s10489-021-02348-9
  4. https://link.springer.com/article/10.1007/s00521-020-05351-2

Publication Date

Winter 11-1-2022

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