Explainable AI

Program Overview

The Explainable AI PhD program at Loughborough University equips students with the skills to understand and implement XAI techniques, fostering critical thinking and problem-solving abilities in the field. The flexible structure allows students to tailor their studies, culminating in a dissertation that contributes to the advancement of XAI research and development. Graduates are well-positioned for careers in academia, industry, and government, where they can apply their expertise in making machine learning models transparent and interpretable.

Program Outline

Degree Overview:

The Explainable AI (XAI) PhD program at Loughborough University delves into the burgeoning field of artificial intelligence that focuses on making machine learning models transparent and interpretable.

Objectives:

• Equip students with the skills and knowledge to understand and implement XAI techniques across various domains.
• Foster critical thinking and problem-solving abilities in the context of XAI challenges.
• Enable students to contribute to the advancement of research and development in the field of XAI.

Outline:

The program offers a flexible structure, allowing students to tailor their studies to their specific interests and career goals.

Core Modules:

• Foundations of Explainable AI
• Explainable Machine Learning Techniques
• Interpretable Deep Learning Models
• Explainable AI Applications
• Ethical Considerations in XAI
• Advanced Topics in Explainable AI

Elective Modules:

• Students can choose from a range of elective modules in areas such as computer science, data science, and artificial intelligence.
• These electives provide opportunities to deepen expertise in specific areas or explore new research directions.

Dissertation:

• The PhD program culminates in a dissertation, allowing students to conduct original research under the supervision of a faculty member.
• Research topics can focus on developing novel XAI techniques, applying XAI to real-world problems, or addressing ethical challenges in XAI.

Assessment:

• Assessment methods vary depending on the module and may include coursework assignments, presentations, exams, and the dissertation.
• Coursework assignments typically involve problem-solving, analysis, and application of XAI techniques.
• Dissertation assessments involve comprehensive evaluation of research design, methodology, results, and conclusions.

Teaching:

• The program is taught by a team of internationally recognized researchers and educators in the field of artificial intelligence.
• Teaching methods include lectures, seminars, workshops, and individual supervision.
• The program promotes an interactive and collaborative learning environment, encouraging students to discuss, debate, and contribute to the advancement of XAI knowledge.

Careers:

• Graduates of the XAI PhD program are well-positioned for careers in various sectors, including academia, industry, and government.
• Potential career paths include:
• Research Scientist (Explainable AI)
• Data Scientist with XAI expertise
• AI Engineer with Explainability focus
• Machine Learning Engineer with Interpretability skills
• Lecturer or Professor in XAI
• Consultant on Explainable AI

Other:

• The program is designed to be flexible and adapt to the evolving field of XAI.
• Students are encouraged to participate in research projects and conferences to gain practical experience and network with researchers in the field.

UK fee: £4,712 Full-time degree per annum International fee: £26,000 Full-time degree per annum University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Fees are reviewed annually and are likely to increase to take into account inflationary pressures.