Engineering Dissertation Titles

Info: 672 words(1 pages)Engineering Dissertation Titles
Published: 14th July 2025 in Engineering Dissertation Titles

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Introduction

This paper highlights Ph.D. dissertation topics in biomedical and aerospace engineering that harness AI advances in healthcare and precision measurement aerospace. It describes significant research areas such as maximization of AI within personalized medicine; increasing healthcare access in low-resource environments for healthcare practices; and integration of AI in preventive healthcare. This paper also outlines challenges associated with measurement of micro-gaps for aerospace applications in terms of precision, resiliency, and integration of AI and digital twins, as well as real-time measurement. These topics contribute to the research gaps and needs of industries.

Biomedical Engineering Dissertation Titles

1. Ethical Implications of AI in Healthcare: Reducing Bias and Enhancing Transparency

Focus: Exploring ways to reduce bias and improve transparency for the AI algorithms that are used in health care, with an emphasis on the ethical frameworks for fairness and accountability in the medical decision-making process.

2. Enhancing access to AI in low-resource health contexts: Optimising technology in rural areas

Focus: Investigating methods of using AI, AI-driven and data-focused technology in a rural, low-resourced context, exploring the complexities and limitations of local infrastructure to appropriately recognise costs, meet challenges, and overcome known barriers to access in marginalised communities.

3. AI in personalised medicine: Predictive modelling and personalised treatment

Focus: exploring ways to build technology that can provide personalised treatments through the use of AI in a healthcare context, based on unique genetic histories, medical histories, and clinical context. The unique and profound challenges of data quality and diversity, and specifically AI-based predictive modelling capabilities and reliable clinical performance, will be examined.

4. AI in Preventive Healthcare: Early Detection and Disease Prevention

Focus: Investigating the role of AI for detecting and preventing chronic diseases, including predicting outcomes and estimating the likelihood of outbreaks in order to reduce the burden on the health system.

5. Legal and Regulatory Challenges in AI-Driven Healthcare: Data Privacy and Accountability

Focus: Investigating AI and alleged rights in relation the myriad of legal and regulatory concerns regarding the use of AI in health care; specifically ‒ privacy of health-related information, informed consent.

Aerospace Engineering Dissertation Titles

6. Improving Micro-Gap Measurement Precision in Aerospace: Overcoming Environmental Challenges

Focus: Investigate common strategies to enhance accuracy in micro-gap measurements in the dynamic and potentially uncontrollable aerospace sector

7. Developing Resilient Micro-Gap Measurement Systems for Extreme Aerospace Environments

Focus: Investigate principal mechanisms involved to create micro-gap measurement devices usable in extraordinarily harsh aerospace environments.

8. AI-Driven Micro-Gap Measurement Systems in Aerospace: Real-Time Integration with Digital Twins

Focus: Investigate benefits of AI and digital twins to enhance micro-gap measurements and use of real-time data.

9. Standardising Micro-Gap Measurement Systems: Ensuring Scalability in Aerospace Production

Focus: Develop micro-gap measurement standards that facilitate standardisation and enhance integration across aerospace platforms of various companies.

10. Integrating Micro-Gap Measurement in Smart Aerospace Manufacturing: Real-Time Control and Precision

Focus: Investigate integrating micro-gap measurement tools into smart aerospace manufacturing systems to enhance on-the-spot, real-time decision quality in production.

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References:

1. Tripathi, D., Hajra, K., Mulukutla, A., Shreshtha, R., & Maity, D. (2025). Artificial Intelligence in Biomedical Engineering and Its Influence on Healthcare Structure: Current and Future Prospects. Bioengineering, 12(2), 163. https://doi.org/10.3390/bioengineering12020163

2. Weiner, E. B., Dankwa-Mullan, I., Nelson, W. A., & Hassanpour, S. (2025). Ethical challenges and evolving strategies in the integration of artificial intelligence into clinical practice. PLOS digital health, 4(4), e0000810.

3. Luz, A., & Gimah, M. (2025). AI-Driven Early Detection Systems for Chronic Diseases.

4. Zhao, X., Zhang, C., Xu, L., Wang, T., Li, P., Zhang, H., & Yang, J. (2025). Gap Measurements in Aerospace Engineering. Sensors (Basel, Switzerland), 25(10), 3059. https://doi.org/10.3390/s25103059

5. Xi, C., Liu, S., Chang, S., Dong, Y., Zhong, W., Jiang, X., & Lu, W. (2025). Enhancing accuracy of line-structured light sensor for narrow weld gap measurement. IEEE Transactions on Instrumentation and Measurement.

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