The MIT School of Engineering has selected 13 new Takeda Fellows for the 2023-24 academic year. These graduate students will conduct groundbreaking research in the field of artificial intelligence (AI) and its applications in human health and drug development. The MIT-Takeda Program, a collaboration between MIT and Takeda, aims to advance AI capabilities to benefit human health. The program brings together different disciplines, merges theory and practical implementation, combines algorithm and hardware innovations, and fosters collaborations between academia and industry.
The 2023-24 Takeda Fellows consist of several PhD candidates from different departments in MIT’s School of Engineering. Adam Gierlach is researching ingestible devices for advanced diagnostics and therapeutics delivery. He aims to develop smart, energy-efficient devices for at-home, long-term diagnostics that can identify and correct gastrointestinal diseases. Vivek Gopalakrishnan focuses on biomedical machine learning methods for minimally invasive neurosurgery. He aims to develop real-time computer vision algorithms for high-quality, 3D intraoperative image guidance. Hao He’s work revolves around passive, continuous, remote health monitoring for virtual clinical trials. He aims to develop trustworthy AI models that promote equitable access and equal performance across different demographic groups. Chengyi Long is studying the temporal dynamics of ecological systems and aims to develop AI-assisted platforms to anticipate changes in microbial systems, which can help differentiate between healthy and unhealthy hosts and design probiotics for disease prevention. Omar Mohd investigates spatial profiling of microRNAs within tissue samples to gain insights into drug resistance in cancer. He develops AI programs for image analysis and pattern recognition in tissues. Sanghyun Park focuses on the integration of AI and biomedical engineering for the development of in-situ forming implants (ISFIs) for drug delivery. He aims to understand the compaction mechanism of drug particles in ISFI formulations for optimal drug delivery. Huaiyao Peng is working on AI techniques for the development of pre-cancer organoid models of high-grade serous ovarian cancer. She aims to identify biomarkers and therapeutic targets for this lethal cancer through cellular and molecular analyses.
The research conducted by these Takeda Fellows holds great promise for advancing AI in healthcare. Their innovative contributions can revolutionize diagnostics, treatment, and drug delivery, ultimately benefiting patients and improving clinical outcomes.