Principal Investigator Ian Hunter
Principal Investigator Dick Yue
Principal Investigator Philip Gschwend
Currently, medical images require a physician to extract clinically relevant information. This talk will explore current work towards making images part of the quantitative medical history and to enable large-scale image-based studies of disease. Although large databases of clinical images contain a wealth of information, medical acquisition constraints result in sparse scans that miss much of the anatomy. These characteristics often render computational analysis impractical as standard processing algorithms tend to fail when applied to such images. Our goal is to enable application of existing algorithms that were originally developed for high resolution research scans to severely undersampled images. Application of the method is illustrated in the context of neurodegeneration and white matter disease studies in stroke patients.
What are the prospects for applying AI to improve healthcare? Three types of problems that AI can address in healthcare will be outlined, the most challenging of which is the development of new therapeutics. To address this challenge, we leverage recent advances in machine learning and high-throughput experimentation to apply the engineering cycle to drug discovery. The engineering cycle is based on iteratively measuring a system, modeling it computationally, and manipulating it. Each time the cycle is completed, the results improve. This iterative approach is fundamental to all engineering design but, until now, has had limited impact on drug discovery. Progress on unpublished projects relating to these efforts will be described, including a collaborative, multi-institutional project called Answer ALS.
Principal Investigator William Oliver
Principal Investigator Isaac Chuang
Life sciences are no longer confined to the realm of biology—they have evolved into a multidisciplinary frontier. This session examines the dynamic intersection of biology, engineering, and computational science, where bold ideas give rise to transformative innovation. By integrating AI, advanced technologies, and foundational biological research, the session will highlight how cross-disciplinary collaboration accelerates the path from scientific discovery to real-world application at MIT. Emphasizing the translation of visionary research into impactful solutions, this track invites participants to reimagine what becomes possible when disciplines converge to shape the future.