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2021-22 Takeda Fellows: Leaning on AI to advance drugs for people | MIT Information



In fall 2020, MIT’s College of Engineering and Takeda Prescription drugs Firm Restricted launched the MIT-Takeda Program, a collaboration to assist members of the MIT neighborhood working on the intersection of synthetic intelligence and human well being. Housed on the Abdul Latif Jameel Clinic for Machine Studying in Well being, the collaboration goals to make use of synthetic intelligence to each profit human well being and assist in drug improvement. Combining expertise with cutting-edge well being analysis, this system’s individuals hope to enhance well being outcomes the world over.

Up to now, the partnership has supported joint analysis efforts centered on subjects resembling automated inspection in sterile pharmaceutical manufacturing and machine studying for liver phenotyping.

Yearly, this system additionally funds graduate fellowships to assist college students pursuing analysis on a broad vary of points tied to well being and AI. This yr’s Takeda fellows, described beneath, are engaged on analysis involving digital well being report algorithms, distant sensing knowledge because it pertains to environmental well being danger, and neural networks for the event of antibiotics.

Monica Agrawal

Agrawal is a PhD scholar within the Division of Electrical Engineering and Laptop Science (EECS). Her analysis focuses on the event of machine studying algorithms that would unlock the potential of digital well being data to energy personalised, real-world research of comparative effectiveness. She is tackling the problem from three interconnected angles: understanding the essential constructing blocks of medical textual content, enabling the structuring of medical timelines with solely minimal labeled knowledge, and redesigning medical documentation to incentivize high-quality structured knowledge on the time of creation. Agrawal earned each a BS and an MS in laptop science from Stanford College.

Peng Cao

A PhD scholar in EECS, Peng Cao’s analysis is targeted on growing a brand new strategy to monitoring oxygen saturation by analyzing the radio frequency indicators that bounce off an individual’s physique. To this finish, she is extracting respiration indicators from the radio indicators after which coaching a neural community to deduce oxygen ranges from it. Peng earned a BS in laptop science from Peking College in China.

Bianca Lepe

A PhD scholar in organic engineering, Bianca Lepe is working to benchmark current and defining next-generation vaccine candidates for tuberculosis. She is utilizing publicly accessible knowledge mixed with machine studying algorithms to determine the Mtb proteins which can be well-suited as subunit vaccine antigens throughout the range of the human leukocyte antigen alleles. Lepe earned a BS in organic engineering and enterprise from Caltech; an MS in methods and artificial biology from the College of Edinburgh in Scotland; and an MPhil in expertise coverage from the College of Cambridge in England.

Caroline McCue

Caroline McCue is a PhD scholar in mechanical engineering who’s growing a system that would simplify and pace up the method of cell passaging. Extra particularly, she is designing and testing a platform that triggers cell detachment in response to easy exterior stimuli, resembling a change in voltage or in mechanical properties. She plans to check the efficacy of this platform by making use of machine studying to quantify the adhesion of Chinese language hamster ovary cells to those surfaces. McCue earned a BS in mechanical engineering from the College of Maryland.

Somesh Mohapatra

A PhD scholar within the Division of Supplies Science and Engineering, Somesh Mohapatra can also be pursuing an MBA on the MIT Sloan College of Administration as a part of the Leaders for International Operations Program. His doctoral analysis, in shut collaboration with experimentalists at MIT, focuses on designing biomacromolecules utilizing interpretable machine studying and simulations. Particularly, Mohapatra leverages macromolecule graph representations to develop machine studying fashions for quantitative prediction, optimization, and attribution strategies. He then applies these instruments to elucidate design ideas and to enhance efficiency and artificial accessibility of performance macromolecules, starting from peptides and glycans to electrolytes and thermosets. Mohapatra earned his BTech in metallurgical and supplies engineering from the Indian Institute of Expertise Roorkee in India.

Luke Murray

Luke Murray is a PhD scholar in EECS. He’s growing MedKnowts, a system that mixes machine studying and human laptop interplay methods to cut back the hassle required to synthesize data for medical decision-making, and writer high-quality, structured, medical documentation. MedKnowts unifies these two presently splintered workflows by offering a seamless interface that re-imagines documentation as a pure byproduct of medical reasoning, quite than as a compliance requirement. Murray earned his BS in laptop science from Brown College.

Ufuoma Ovienmhada

Ufuoma Ovienmhada SM ’20 is a PhD scholar in aeronautics and astronautics. Her analysis employs a mixed-methods strategy (community-centered design, methods engineering, and machine studying) to satellite tv for pc distant sensing knowledge to create instruments that consider how human well being danger pertains to environmental hazards. Ovienmhada earned her BS in mechanical engineering from Stanford College and her SM in media arts and sciences from MIT.​

Lagnajit Pattanaik

Lagnajit “Fortunate” Pattanaik is a PhD scholar in chemical engineering. He seeks to shift the paradigm of predictive natural chemistry from qualitative to quantitative. Extra particularly, his analysis is targeted on the event of machine studying methods for predicting 3D buildings of molecules and reactions, together with transition state geometries and the geometrical conformations that molecules absorb answer. He earned a BS in chemical engineering from Ohio State College.

Na Solar 

A PhD scholar in EECS, Na Solar is working within the rising subject of neuro-immuno-genomics. Extra particularly, she is growing machine studying strategies to higher perceive the interactions between two extraordinarily advanced methods: the human mind and its dozens of cell sorts, and the human immune system and the handfuls of organic processes that it integrates throughout cognition, pathogen response, diet-exercise-obesity, and synaptic pruning. Solar earned her BS in life sciences from Linyi College in China and an MS in developmental biology from the College of Chinese language Academy of Sciences in China.

Jacqueline Valeri

Jacqueline Valeri is a PhD scholar in organic engineering who makes use of neural networks for antibiotics discovery. Her efforts embrace the recycling of compounds from current compound libraries and the computationally assisted design of novel therapeutics. She can also be excited by broader purposes of machine studying and synthetic intelligence within the fields of well being care and biomedicine. Valeri earned her BSE and MSE in bioengineering from the College of Pennsylvania.

Clinton Wang

A PhD scholar in EECS, Clinton Wang SM ’20 has developed a brand new kind of conditional generative adversarial community based mostly on spatial-intensity transforms. It achieves excessive picture constancy, is powerful to artifacts in coaching knowledge, and generalizes to held-out medical websites. Wang now goals to increase his mannequin to much more difficult purposes, together with visualizing transformations of focal pathologies, resembling lesions, the place it may function a strong software for characterizing biomarkers of malignancy and remedy response. Wang earned a BS in biomedical engineering from Yale College and an SM in electrical engineering and laptop science from MIT.

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