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2021-22 Takeda Fellows: Leaning on AI to progress medication for individuals | MIT News

In drop 2020, MIT’s College of Engineering and Takeda Prescribed drugs Enterprise Constrained introduced the MIT-Takeda Program, a collaboration to help customers of the MIT community doing work at the intersection of synthetic intelligence and human health. Housed at the Abdul Latif Jameel Clinic for Equipment Mastering in Health, the collaboration aims to use synthetic intelligence to both equally benefit human well being and aid in drug development. Combining engineering with cutting-edge wellness analysis, the program’s participants hope to make improvements to wellness outcomes across the environment.

As a result far, the partnership has supported joint investigation endeavours focused on subject areas these kinds of as automatic inspection in sterile pharmaceutical production and machine learning for liver phenotyping.

Each and every year, the application also money graduate fellowships to support college students pursuing research on a broad vary of concerns tied to wellbeing and AI. This year’s Takeda fellows, described underneath, are working on exploration involving electronic wellbeing document algorithms, remote sensing details as it relates to environmental wellness risk, and neural networks for the improvement of antibiotics.

Monica Agrawal

Agrawal is a PhD scholar in the Section of Electrical Engineering and Personal computer Science (EECS). Her research focuses on the advancement of equipment studying algorithms that could unlock the potential of digital wellness documents to electric power individualized, serious-globe studies of comparative usefulness. She is tackling the difficulty from a few interconnected angles: being familiar with the primary making blocks of scientific text, enabling the structuring of medical timelines with only nominal labeled information, and redesigning clinical documentation to incentivize substantial-good quality structured details at the time of development. Agrawal acquired both a BS and an MS in laptop science from Stanford University.

Peng Cao

A PhD university student in EECS, Peng Cao’s research is targeted on developing a new technique to checking oxygen saturation by examining the radio frequency signals that bounce off a person’s physique. To this stop, she is extracting respiration signals from the radio alerts and then schooling a neural network to infer oxygen stages from it. Peng attained a BS in laptop science from Peking University in China.

Bianca Lepe

A PhD college student in organic engineering, Bianca Lepe is functioning to benchmark current and defining following-technology vaccine candidates for tuberculosis. She is working with publicly out there data mixed with equipment understanding algorithms to detect the Mtb proteins that are well-suited as subunit vaccine antigens across the diversity of the human leukocyte antigen alleles. Lepe gained a BS in organic engineering and business enterprise from Caltech an MS in devices and artificial biology from the University of Edinburgh in Scotland and an MPhil in know-how coverage from the University of Cambridge in England.

Caroline McCue

Caroline McCue is a PhD student in mechanical engineering who is building a technique that could simplify and velocity up the course of action of cell passaging. More especially, she is designing and tests a platform that triggers cell detachment in reaction to straightforward exterior stimuli, these types of as a improve in voltage or in mechanical homes. She programs to test the efficacy of this platform by applying machine studying to quantify the adhesion of Chinese hamster ovary cells to these surfaces. McCue acquired a BS in mechanical engineering from the College of Maryland.

Somesh Mohapatra

A PhD student in the Division of Materials Science and Engineering, Somesh Mohapatra is also pursuing an MBA at the MIT Sloan School of Administration as aspect of the Leaders for World-wide Operations System. His doctoral research, in shut collaboration with experimentalists at MIT, focuses on planning biomacromolecules employing interpretable device learning and simulations. Specially, Mohapatra leverages macromolecule graph representations to acquire equipment mastering versions for quantitative prediction, optimization, and attribution strategies. He then applies these instruments to elucidate style rules and to improve overall performance and artificial accessibility of performance macromolecules, ranging from peptides and glycans to electrolytes and thermosets. Mohapatra earned his BTech in metallurgical and components engineering from the Indian Institute of Technological know-how Roorkee in India.

Luke Murray

Luke Murray is a PhD student in EECS. He is creating MedKnowts, a procedure that combines equipment learning and human laptop or computer interaction strategies to cut down the exertion expected to synthesize expertise for clinical selection-generating, and creator significant-excellent, structured, medical documentation. MedKnowts unifies these two at present splintered workflows by giving a seamless interface that re-imagines documentation as a natural byproduct of clinical reasoning, rather than as a compliance requirement. Murray gained his BS in laptop science from Brown University.

Ufuoma Ovienmhada

Ufuoma Ovienmhada SM ’20 is a PhD scholar in aeronautics and astronautics. Her exploration employs a combined-approaches solution (neighborhood-centered design, systems engineering, and device discovering) to satellite remote sensing info to produce resources that consider how human health possibility relates to environmental dangers. Ovienmhada attained her BS in mechanical engineering from Stanford College and her SM in media arts and sciences from MIT.​

Lagnajit Pattanaik

Lagnajit “Lucky” Pattanaik is a PhD student in chemical engineering. He seeks to shift the paradigm of predictive organic and natural chemistry from qualitative to quantitative. Additional precisely, his investigate is concentrated on the development of device finding out methods for predicting 3D buildings of molecules and reactions, which include changeover point out geometries and the geometrical conformations that molecules just take in resolution. He gained a BS in chemical engineering from Ohio Condition University.

Na Sunshine 

A PhD pupil in EECS, Na Solar is doing the job in the rising field of neuro-immuno-genomics. More especially, she is producing machine finding out approaches to greater comprehend the interactions involving two extremely complicated units: the human brain and its dozens of mobile types, and the human immune method and the dozens of biological processes that it integrates throughout cognition, pathogen reaction, food plan-physical exercise-being overweight, and synaptic pruning. Sun earned her BS in everyday living sciences from Linyi College in China and an MS in developmental biology from the College of Chinese Academy of Sciences in China.

Jacqueline Valeri

Jacqueline Valeri is a PhD student in biological engineering who makes use of neural networks for antibiotics discovery. Her initiatives incorporate the recycling of compounds from current compound libraries and the computationally assisted structure of novel therapeutics. She is also excited by broader purposes of machine mastering and artificial intelligence in the fields of health and fitness treatment and biomedicine. Valeri attained her BSE and MSE in bioengineering from the University of Pennsylvania.

Clinton Wang

A PhD university student in EECS, Clinton Wang SM ’20 has developed a new type of conditional generative adversarial network based on spatial-intensity transforms. It achieves higher impression fidelity, is robust to artifacts in education information, and generalizes to held-out medical web sites. Wang now aims to increase his design to even much more challenging programs, which includes visualizing transformations of focal pathologies, these kinds of as lesions, in which it could serve as a potent software for characterizing biomarkers of malignancy and treatment method reaction. Wang gained a BS in biomedical engineering from Yale College and an SM in electrical engineering and pc science from MIT.