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DTSTART;TZID=America/Toronto:20221026T120000
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UID:10000143-1666785600-1666787400@bme.utoronto.ca
SUMMARY:Graduate Seminar Series: Clinical Stream - saba sadatamin
DESCRIPTION:Graduate Seminar Series: Clinical Stream\nGraduate Seminar Series for the Institute of Biomedical Engineering (BME). This day is for clinical stream presenters.\nIf you would like to invite your Principal Investigator\, please add their email via the ‘Add Guest’ button and they will also be notified of your presentation.\nPresentation Title: Thermometry Prediction Using Artificial Intelligence on MR-guided Laser Interstitial Thermal Therapy Planning Images\nAbstract:\nMagnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive thermal therapy for drug-resistant focal epilepsy and brain tumors. In this approach\, the surgeon needs to insert the laser fiber into the target along a fixed trajectory. Thermometry prediction using artificial intelligence (AI) modeling may help the surgeon determine whether the selected laser position is the ideal location to treat the tumor before starting the surgery\, as both repositioning and predicting thermal spread close to heat sinks are difficult. I hypothesize that this data-driven approach will reduce planning time\, minimize injury to other brain regions and maximize tumor treatment probability. Specifically\, I will train artificial intelligence algorithms to model the nonlinear mapping from three-dimensional\nanatomical MRI planning images to multi-slide thermometry time series (three-dimensional). By having the patients’ anatomical MRI\, the surgeon will access the AI-based heat propagation distribution in predicted thermometry images to better choose the ideal laser position.\nSupervisor Name: Dr. James Drake\, Dr. Lueder Kahrs\nYear of Study: 2\nProgram of Study: PhD\nZoom link: https://us02web.zoom.us/j/89610372821?pwd=azd4SCtYVWtreVovaGNPV1c2NGY2Zz09\nMeeting ID: 896 1037 2821\nPassword: 483329\nPowered by Calendly.com
URL:https://bme.utoronto.ca/event/graduate-seminar-series-clinical-stream-saba-sadatamin/
CATEGORIES:Graduate Seminar Series
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DTSTART;TZID=America/Toronto:20221028T120000
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UID:10000141-1666958400-1666962000@bme.utoronto.ca
SUMMARY:Active Learning for Optimizing RNA Based Vaccines and Therapeutics
DESCRIPTION:CARTE Industry Speaker Seminar Series welcome Michael Bailey\, Computational Scientist at Sanofi Data and AI Center of Excellence in Toronto\, for the first in-person seminar of 2022-23 academic year. \nTopic: Active Learning for Optimizing RNA Based Vaccines and Therapeutics \nDate and Time: Friday October 28\, 2022 (12:00 – 1:00 PM EST) \nRegistration: To register\, please see here. Capacity is limited. Please register early to secure your spot. \n  \n \nAbstract: RNA vaccines saved the world from COVID. But vaccines are just one of several potential uses for this breakthrough technology. As the world leading vaccine manufacturer and one of the largest pharma companies\, Sanofi has recently launched its RNA Center of Excellence to lead the way in the development and use of RNAs for vaccines and therapeutics. While promising\, the use of mRNA raises several new computational challenges. These involve issues related to representation and search in the exponential space of mRNA molecules\, the design and optimization of their lipid vehicles and the ability to predict human response from non-human models. I will discuss these challenges and will also present methods we developed to address these issues. Our methods use deep language models and graph neural networks for representation and couple them with active learning approaches for optimization. By developing an experimental-computational strategy we were able to obtain more accurate RNA and lipid combinations while still reducing the time and cost to optimize vaccines for new variants. \nSpeaker Bio: Michael Bailey is a Computational Scientist at Sanofi. With a background in Mathematics (doing a Ph.D. at the University of Toronto)\, he transitioned into Machine Learning later in his career\, looking to work on real-world problems. In his current role at the new Sanofi Data and AI Center of Excellence in Toronto\, he works on Machine Learning problems to support the discovery of new therapies. \nLocation: Myhal Centre for Engineering Innovation & Entrepreneurship\, 55 St George St.\, Toronto\, Ontario\, M5S 0C9\, Room 380 \nRegistration: To register\, please see here. Capacity is limited. Please register early to secure your spot.
URL:https://bme.utoronto.ca/event/active-learning-for-optimizing-rna-based-vaccines-and-therapeutics/
LOCATION:Myhal Centre for Engineering Innovation & Entrepreneurship\, 55 St George St.\, Toronto\, Ontario\, M5S 0C9\, Room 380
CATEGORIES:Events & Workshops
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