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HomeTechnologyArtificial intelligence2022-23 Takeda Fellows: Leveraging AI to positively impact human health

2022-23 Takeda Fellows: Leveraging AI to positively impact human health

The MIT-Takeda Program, a collaboration between MIT’s School of Engineering and Takeda Pharmaceuticals Company, fuels the event and utility of synthetic intelligence capabilities to learn human well being and drug growth. Part of the Abdul Latif Jameel Clinic for Machine Learning in Health, this system coalesces disparate disciplines, merges principle and sensible implementation, combines algorithm and {hardware} improvements, and creates multidimensional collaborations between academia and business.

With the goal of constructing a neighborhood devoted to the subsequent era of AI and system-level breakthroughs, the MIT-Takeda Program can also be creating instructional alternatives. Every 12 months Takeda funds fellowships to help graduate college students pursuing analysis associated to well being and AI. This 12 months’s Takeda Fellows, described beneath, are engaged on initiatives starting from digital well being file techniques and robotic management to pandemic preparedness and traumatic mind accidents.

Camille C. Farruggio

Farruggio is a PhD candidate within the Department of Materials Science and Engineering whose analysis leverages AI and machine studying, together with regression modeling, to assist notice the promise of cells-as-medicine functions. As a Takeda Fellow, she seeks to develop a holistic understanding of the tradition situations and cell attributes that modulate and predict cell efficacy as therapeutic therapies and resolve current expertise bottlenecks within the manufacturing of cell therapies.

Wenhao Gao

Gao is a PhD candidate within the Department of Chemical Engineering who goals to speed up organic and chemical discovery processes. His work particularly focuses on AI for well being sciences and cutting-edge functions of machine studying for molecular discovery and drug growth. Gao’s analysis, supported by a Takeda Fellowship, seeks to create a extra environment friendly course of, utilizing AI algorithms to advance de novo design strategies and natural synthesis for accelerated drug growth.

Samuel Goldman

Goldman is a PhD candidate within the Computational and Systems Biology Program whose analysis pursuits lie on the intersection of biology, analytical chemistry, and machine studying. Specifically, Goldman makes use of mass spectrometry knowledge and generative deep studying to elucidate the buildings of unknown molecules in organic samples, with essential implications for drug discovery. As a Takeda Fellow, he’ll construct new computational instruments to characterize and measure unknown small molecule metabolites in a mobile combination.

Sarah Gurev

Gurev is a PhD candidate within the Department of Electrical Engineering and Computer Science. Her analysis seeks to deal with the challenges of pandemic preparedness and the prediction of viral immune evasion. As a Takeda Fellow, Gurev will advance her work on the intersection of computational approaches and experimental screening to develop new fashions of antibody escape.

R’mani Haulcy

Haulcy is a PhD candidate within the Department of Electrical Engineering and Computer Science whose work bridges the fields of AI and well being to create cutting-edge AI-based assessments of cognitive impairment in speech and language problems. Supported by a Takeda Fellowship, Haulcy will develop new instruments for speech processing targeted on the measurement of health-related speech biomarkers, particularly analyzing the speech of topics with frontotemporal dementia and first progressive aphasia.

Velina Kozareva

Kozareva is a PhD candidate within the Computational and Systems Biology Program whose analysis focuses on growing machine studying strategies to combine multi-omic knowledge in heterogeneous ailments. As a Takeda Fellow, Kozareva goals to develop computational strategies to concurrently establish subtypes of heterogeneous ailments and the causal mechanisms that drive every subtype, with an preliminary concentrate on amyotrophic lateral sclerosis.

Yang Liu

Liu is a PhD candidate within the Department of Electrical Engineering and Computer Science whose present work focuses on AI for well being information and computational imaging/pictures, which lies on the confluence of pc science, optics, biomedical/neuroscience, {hardware} design, and software program design. Liu’s Takeda Fellowship will help his present analysis, a collaborative mission that goals to deal with the related challenges of delivering well being care and sustaining health-care information in resource-constrained settings.

Luke Murray

Murray is a PhD candidate within the Department of Electrical Engineering and Computer Science whose work is concentrated on digital well being file (EHR) techniques, which have revolutionized well being care and maintain great potential for medical analysis, operations, and analysis, but in addition endure from severe shortcomings. Through his Takeda Fellowship, Murray will sort out a main EHR limitation: disparate interfaces that fragment the medical workflow into time-consuming, error-prone processes that require clinicians to spend extra time interacting with EHRs than with sufferers.

Mark Olchanyi

Olchanyi is a PhD candidate within the Harvard-MIT Program in Health Sciences and Technology whose analysis seeks to advance our information of traumatic mind accidents (TBIs). Olchanyi’s analysis, supported by a Takeda Fellowship, will apply deep studying to review in vivo imaging-based TBI biomarkers, with a selected concentrate on subcortical white matter lesions in acute TBIs leading to problems of consciousness.

Krista Pullen

Pullen is a PhD candidate within the Department of Biological Engineering whose analysis is located on the intersection of vaccine immunology and machine studying. With the help of a Takeda Fellowship, Pullen will develop and validate the applying of cross-species modeling within the context of vaccine immunology to allow the prediction of human efficacy from preclinical knowledge.

Georgia Thomas

Thomas is a PhD candidate within the Harvard-MIT Program in Health Sciences and Technology whose analysis explores the underlying physics of optical imaging, with the aim of increasing its capability to deal with essential medical challenges. As a Takeda Fellow, Thomas will advance her work to create progressive instruments to higher perceive and deal with coronary atherosclerosis, a illness affecting over 18 million individuals within the United States alone.

A. Michael West Jr.

West is a PhD candidate within the Department of Mechanical Engineering whose analysis integrates robotics, AI, and well being care to enhance robotic rehabilitation and advance human-robot interactions. Specifically, his work explores the human neuromotor management of motion, with the aim of enhancing robotic management and efficiency. As a Takeda Fellow, West will research the performance of the human hand and its potential to govern objects and instruments.

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