Work Experience

Worked on Research Problems  related to Adversarial and Expianable AI, such as : 

• Improving Attributional Robustness of Deep Neural Network for developing trust and transparency to end users.

• Improving Adversarial Robustness of Deep Neural Network against  adversarial attacks.

• Buliding Ante-hoc Explainable models for computer vision applications.

• Improving Robustness of Deep Neural Network against common unseen noisy corruptions data.

• Removing Backgroud Dependency for Object Recognition.

Extensively worked on broad range of Deep Learning Applications in Computer vision         as well as Natural Language Processing domain, such as:

• Object Detection, Semantic Segmentation, Multiple Object Tracking, etc.

• Text Summarization, Neural Machine Translation, Sentiment Analysis, Summary generation from structured  data, etc.

• Teaching Assistant for course on Computational Neuroscience.

• Build Computational Model of Spinal Cord Neuron for the aid of Surgical Analytics.