Artificial Intelligence in Bioengineering: Innovations, Challenges, and Future Directions

Dear Colleagues,

Artificial Intelligence (AI) is rapidly becoming a defining force in modern bioengineering. The convergence of computational intelligence with the life sciences is enabling levels of biological modeling, prediction, and system design that were unthinkable only a decade ago. As bioengineering evolves at the intersection of engineering, biology, and medicine, AI and machine learning are increasingly central to research, innovation, and translation.

AI now permeates the entire bioengineering pipeline: from the analysis of complex biological and clinical data to predictive modeling of physiological processes, and from advanced biomedical imaging to the design of smart devices capable of interacting dynamically with human tissues. Deep learning, hybrid neural architectures, generative models, and multimodal approaches are reshaping biomaterials research, organ-on-chip technologies, and personalized therapies.

This technological shift is further amplified by the integration of AI with emerging platforms such as digital twins, intelligent biosensors, soft robotics, 3D bioprinting, and tissue engineering—opening new opportunities for early diagnosis, continuous health monitoring, surgical assistance, and precision medicine.

Yet these advances also bring significant challenges: the need for reliable and interoperable data, model transparency, bias mitigation, rigorous validation, and attention to the ethical and regulatory implications of deploying AI in sensitive biomedical contexts. Addressing these issues is essential to ensuring responsible and trustworthy innovation.

This Special Issue aims to highlight both the transformative potential of AI in bioengineering and the critical questions that must accompany its development.

Topics of Interest

We invite submissions covering, but not limited to, the following areas:

• AI for biomedical signal and image processing (MRI, CT, ultrasound, wearable sensors, etc.);
• Machine learning and deep learning for biomaterials design and analysis;
• Digital twins in medicine and biology;
• AI-driven drug discovery and computational modeling of biological systems;
• AI-enabled biomedical devices, implants, and prosthetics;
• Bioinformatics and multi-omics data integration through AI;
• Robotics, rehabilitation technologies, and human–machine interfaces;
• AI for precision medicine and personalized therapeutic strategies;
• Explainable, trustworthy, and ethical AI for bioengineering applications;
• Real-time AI deployment in healthcare, IoT, and biomedical monitoring systems;
• AI for biomanufacturing and synthetic biology.

Prof. Dr. Daniele Giansanti
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• artificial intelligence
• bioengineering
• machine learning
• biomedical imaging
• precision medicine
• digital twins
• biomedical devices
• explainable AI
• drug discovery
• multi-omics integration