Aisha Aijaz

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PhD Scholar at IIITD

Research Interests: Ethical AI, Semantic Web Technologies, Knowledge Representation, Neurosymbolic Techniques, Ethics, AI Philosophy

Highlights

Education

PhD in Computer Science Engineering

M.Sc. in Data Science

B.Tech. in Computer Engineering

Research Projects

Ongoing:

APPL-E: An Applied Ethics Ontology to capture Ethical Theory and Contextual Information in various Domains

An Ontology to capture various abstract concepts in the field of ethical philosophy as entities and relationships.

A Dataset to Capture Ethical and Contextual Information about Real-world Cases with their Ethical Analysis

This dataset aims to document and annotate real-world cases where some moral reasoning takes place. The features selected for this dataset are carefully curated to represent the most vital contextual information that can imply the morality of the act. Each act can be labeled as either a morally right, wrong, or grey action. Ethical theory is also considered as schools of thought and the ethical principles violated. This dataset may facilitate ethics research in the field of AI applications and also aid ML and symbolic techniques for dilemma resolution.

A Survey on Techniques to Digitize Ethics and Ethical Decision-making

This survey paper looks at the various techniques used to capture ethical information in the computing space, and also the use of the latest technologies to facilitate ethical decision-making.

Completed:

Opacity, Transparency, and the Ethics of Affective Computing

Co-authored with M. Kumar, O. Chattar, J. Shukla, and R. Mutharaju. Published at the IEEE Transactions on Affective Computing, Special Issue on Ethics in Affective Computing 2023.

A Comparative Study on Approaches to OCR for Different Scripts

Masters Thesis under the supervision of Dr. Hind Zantout. Heriot-Watt University, 2019.

Cryptanalysis of Image Cryptosystem Using Synchronized 4D Lorenz Stenflo Hyper-chaotic Systems

Co-authored with M. Ahmad, S. Ansari, M. Siddiqui, and S. Masood. Published in Information and Decision Sciences, AISC, Vol. 701, Springer, 2018.

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