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

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

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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 application of artificial intelligence capabilities to profit human health and drug development. A part of the Abdul Latif Jameel Clinic for Machine Learning in Health, this system coalesces disparate disciplines, merges theory and practical implementation, combines algorithm and hardware innovations, and creates multidimensional collaborations between academia and industry.

With the aim of constructing a community dedicated to the following generation of AI and system-level breakthroughs, the MIT-Takeda Program can be creating educational opportunities. Every yr Takeda funds fellowships to support graduate students pursuing research related to health and AI. This yr’s Takeda Fellows, described below, are working on projects starting from electronic health record systems and robotic control to pandemic preparedness and traumatic brain injuries.

Camille C. Farruggio

Farruggio is a PhD candidate within the Department of Materials Science and Engineering whose research leverages AI and machine learning, including regression modeling, to assist realize the promise of cells-as-medicine applications. As a Takeda Fellow, she seeks to develop a holistic understanding of the culture conditions and cell attributes that modulate and predict cell efficacy as therapeutic treatments and solve existing technology bottlenecks within the production of cell therapies.

Wenhao Gao

Gao is a PhD candidate within the Department of Chemical Engineering who goals to speed up biological and chemical discovery processes. His work specifically focuses on AI for health sciences and cutting-edge applications of machine learning for molecular discovery and drug development. Gao’s research, supported by a Takeda Fellowship, 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 PhD candidate within the Computational and Systems Biology Program whose research interests lie on the intersection of biology, analytical chemistry, and machine learning. Specifically, Goldman uses mass spectrometry data and generative deep learning to elucidate the structures of unknown molecules in biological samples, with essential implications for drug discovery. As a Takeda Fellow, he’ll construct recent computational tools to characterize and measure unknown small molecule metabolites in a cellular mixture.

Sarah Gurev

Gurev is a PhD candidate within the Department of Electrical Engineering and Computer Science. Her research 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 recent models 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 health to create cutting-edge AI-based assessments of cognitive impairment in speech and language disorders. Supported by a Takeda Fellowship, Haulcy will develop recent tools for speech processing focused on the measurement of health-related speech biomarkers, specifically examining the speech of subjects with frontotemporal dementia and first progressive aphasia.

Velina Kozareva

Kozareva is a PhD candidate within the Computational and Systems Biology Program whose research focuses on developing machine learning methods to integrate multi-omic data in heterogeneous diseases. As a Takeda Fellow, Kozareva goals to develop computational methods to concurrently discover subtypes of heterogeneous diseases and the causal mechanisms that drive each subtype, with an initial give attention to amyotrophic lateral sclerosis.

Yang Liu

Liu is a PhD candidate within the Department of Electrical Engineering and Computer Science whose current work focuses on AI for health records and computational imaging/photography, which lies on the confluence of computer science, optics, biomedical/neuroscience, hardware design, and software design. Liu’s Takeda Fellowship will support his current research, a collaborative project that goals to deal with the connected challenges of delivering health care and maintaining health-care records in resource-constrained settings.

Luke Murray

Murray is a PhD candidate within the Department of Electrical Engineering and Computer Science whose work is targeted on electronic health record (EHR) systems, which have revolutionized health care and hold tremendous potential for clinical diagnosis, operations, and research, but additionally suffer from serious shortcomings. Through his Takeda Fellowship, Murray will tackle a primary EHR limitation: disparate interfaces that fragment the clinical workflow into time-consuming, error-prone processes that require clinicians to spend more time interacting with EHRs than with patients.

Mark Olchanyi

Olchanyi is a PhD candidate within the Harvard-MIT Program in Health Sciences and Technology whose research seeks to advance our knowledge of traumatic brain injuries (TBIs). Olchanyi’s research, supported by a Takeda Fellowship, will apply deep learning to review in vivo imaging-based TBI biomarkers, with a specific give attention to subcortical white matter lesions in acute TBIs leading to disorders of consciousness.

Krista Pullen

Pullen is a PhD candidate within the Department of Biological Engineering whose research is situated on the intersection of vaccine immunology and machine learning. With the support of a Takeda Fellowship, Pullen will develop and validate the applying of cross-species modeling within the context of vaccine immunology to enable the prediction of human efficacy from preclinical data.

Georgia Thomas

Thomas is a PhD candidate within the Harvard-MIT Program in Health Sciences and Technology whose research explores the underlying physics of optical imaging, with the goal of expanding its capability to deal with essential medical challenges. As a Takeda Fellow, Thomas will advance her work to create progressive tools to higher understand and treat coronary atherosclerosis, a disease affecting over 18 million people in america alone.

A. Michael West Jr.

West is a PhD candidate within the Department of Mechanical Engineering whose research integrates robotics, AI, and health care to enhance robotic rehabilitation and advance human-robot interactions. Specifically, his work explores the human neuromotor control of movement, with the goal of enhancing robot control and performance. As a Takeda Fellow, West will study the functionality of the human hand and its ability to govern objects and tools.

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