The MIT-Takeda Program, a collaboration between the MIT School of Engineering and Takeda Pharmaceuticals Company, advances the development and application of artificial intelligence capabilities to benefit human health and drug development. As part of the Abdul Latif Jameel Clinic for Machine Learning in Health, the program fuses disparate disciplines, melds theory and practical implementation, combines hardware and algorithm innovations, and creates multidimensional collaborations between academia and industry.
With the goal of building a community dedicated to the next generation of AI and system-level advancements, the MIT-Takeda Program is also creating educational opportunities. Each year Takeda funds scholarships to support graduate students conducting research related to health and AI. This year’s Takeda fellows, described below, are working on projects ranging from electronic medical record systems and robotic control to pandemic preparedness and traumatic brain injury.
Camille C. Farruggio
Farruggio is a PhD candidate in the Department of Materials Science and Engineering whose research leverages artificial intelligence and machine learning, including regression modelling, to help realize the promise of cell-as-medicine applications. As a Takeda Fellow, she seeks to develop a holistic understanding of culture conditions and cellular attributes that modulate and predict cell efficacy as therapeutic treatments and resolve existing technological bottlenecks in the production of cell therapies.
wenhao gao
Gao is a PhD candidate in the Department of Chemical Engineering, whose goal is to accelerate the processes of biological and chemical discovery. His work focuses specifically on AI for the health sciences and cutting-edge applications of machine learning for molecular discovery and drug development. Gao’s research, supported by a Takeda grant, seeks to create a more efficient process, using AI algorithms to advance de novo design methods and organic synthesis for accelerated drug development.
samuel goldman
Goldman is a doctoral candidate in the Computational and Systems Biology Program, whose research interests lie at the intersection of biology, analytical chemistry, and machine learning. Specifically, Goldman uses data from mass spectrometry and generative deep learning to elucidate the structures of unknown molecules in biological samples, with important implications for drug discovery. As a Takeda fellow, he will create new computational tools to characterize and measure unknown small molecule metabolites in a cellular mixture.
Sara Gurev
Gurev is a PhD candidate in the Department of Electrical Engineering and Computer Science. His research seeks to address the challenges of pandemic preparedness and the prediction of viral immune evasion. As a Takeda fellow, Gurev will advance her work at the intersection of computational approaches and experimental detection to develop new models of antibody escape.
R’mani Haulcy
Haulcy is a PhD candidate in the Department of Electrical Engineering and Computer Science, whose work bridges the fields of AI and healthcare to create cutting-edge AI-based assessments of cognitive decline in speech and language disorders. With the support of a Takeda grant, Haulcy will develop new tools for speech processing focused on the measurement of health-related biomarkers of speech, specifically examining the speech of subjects with frontotemporal dementia and primary progressive aphasia.
velina kozareva
Kozareva is a PhD candidate in the Computational and Systems Biology Program whose research focuses on the development of machine learning methods to integrate multi-omics data in heterogeneous diseases. As a Takeda fellow, Kozareva aims to develop computational methods to simultaneously identify heterogeneous disease subtypes and the causal mechanisms driving each subtype, with an initial focus on amyotrophic lateral sclerosis.
yang liu
Liu is a PhD candidate in the Department of Electrical Engineering and Computer Science whose current work focuses on AI for health records and computational imaging/photography, which is at the confluence of informatics, optics, biomedical / neuroscience, hardware design and software design. . Liu’s Takeda Fellowship will support her ongoing research, a collaborative project that aims to address the related challenges of delivering healthcare and maintaining healthcare records in resource-constrained settings.
luke murray
Murray is a PhD candidate in the Department of Electrical Engineering and Computer Science whose work focuses on electronic medical record (EHR) systems, which have revolutionized healthcare and have tremendous potential for clinical diagnostics, operations and research, but they also suffer from serious problems. shortcomings Through his Takeda Fellowship, Murray will address a major limitation of EHR: disparate interfaces that fragment clinical workflow into slow, error-prone processes that require clinicians to spend more time interacting with EHRs than with patients.
brand olchanyi
Olchanyi is a doctoral candidate in the Harvard-MIT Program in Health Sciences and Technology whose research seeks to advance our knowledge of traumatic brain injury (TBI). Olchanyi’s research, supported by a Takeda grant, will apply deep learning to study TBI biomarkers based on in vivo imaging, with a particular focus on subcortical white matter lesions in acute TBIs that result in impaired consciousness. .
Krista Pullen
Pullen is a PhD candidate in the Department of Biological Engineering whose research sits at the intersection of vaccine immunology and machine learning. With the support of a Takeda grant, Pullen will develop and validate the application of cross-species models in the context of vaccine immunology to enable the prediction of human efficacy from preclinical data.
georgia thomas
Thomas is a doctoral candidate in the Harvard-MIT Program in Health Sciences and Technology, whose research explores the underlying physics of optical imaging, with the goal of expanding its ability to address important medical challenges. As a Takeda Fellow, Thomas will advance her work to create innovative tools to better understand and treat coronary atherosclerosis, a disease that affects more than 18 million people in the United States alone.
A. Michael West Jr.
West is a PhD candidate in the Department of Mechanical Engineering whose research integrates robotics, AI, and healthcare to improve robotic rehabilitation and promote human-robot interactions. Specifically, his work explores human neuromotor control of movement, with the goal of improving robot control and performance. As a Takeda intern, West will study the functionality of the human hand and its ability to manipulate objects and tools.
