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DTSTAMP:20231204T170753
DTSTART;TZID=America/Detroit:20231213T160000
DTEND;TZID=America/Detroit:20231213T170000
SUMMARY:Workshop / Seminar:Bayesian sequential testing and estimation in discrete time
DESCRIPTION:In this talk\, I will present two concrete problems related to sequentially testing and estimating an unknown parameter within the exponential family in discrete time\, incorporating observation costs within the Bayesian setting. Specifically\, we will examine the entire one-parameter exponential family with an arbitrary prior distribution\, and\, therefore\, we will not rely on conjugate priors. These problems can be embedded in Markovian frameworks. In the absence of explicit solutions\, we will discuss the properties of the value functions and their implications for the structure of continuation regions. Beyond the obvious statistical applications\, I will briefly discuss their relevance in stochastic control problems with learning features. Part of this talk is based on joint work with Erik Ekström.
UID:115769-21835489@events.umich.edu
URL:https://events.umich.edu/event/115769
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:Off Campus Location
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20231117T145250
DTSTART;TZID=America/Detroit:20231213T160000
DTEND;TZID=America/Detroit:20231213T170000
SUMMARY:Lecture / Discussion:DCMB / CCMB  Weekly Seminar featuring X. Shirley Liu\, PhD (Co-founder & CEO of GV20 Therapeutics)
DESCRIPTION:Abstract:\nDespite the exciting clinical benefits of immune checkpoint inhibitors\, only a minority of cancer patients respond to treatment. Addressing resistance to immune checkpoint inhibitors is an urgent unmet need and requires novel approaches for target identification and drug discovery. \n\nGV20 Therapeutics adopts an interdisciplinary approach integrating functional genomics\, big data AI\, and cancer immunology for cancer target identification and drug discovery. Our platform computationally extracts antibodies from large cohorts of patient tumor RNA-seq profiles and uses AI to pair targets and corresponding antibodies in silico\, de novo with speed and scale. We then leverage in-house and public functional genomics and proteomics data to de-risk the AI-identified targets from patient tumors and provide insights on target function before we conduct systematic in vitro and in vivo validation experiments. \n\nWe used this approach to discover our lead program\, GV20-0251\, which is a first-in-class monoclonal antibody against a novel immune checkpoint IGSF8. In multiple syngeneic tumor models\, anti-IGSF8 antibody has single-agent efficacy and is synergistic with anti-PD1 in controlling tumor growth\, and the safety of GV20-0251 is currently being tested in the clinic. Our efforts represent the beginning of rationally combining genomics and AI to unlock the hidden information from patient tumors to develop cancer therapeutics.\n\nShort Bio:\nDr. X. Shirley Liu is the co-founder and CEO of GV20 Therapeutics\, a clinical stage biopharmaceutical company with pioneering technologies in novel target identification and antibody drug discovery in Oncology. Dr. Liu received PhD in Biomedical Informatics and PhD minor in Computer Science from Stanford University in 2002. She has been a Professor of Biostatistics and Computational Biology at the Department of Data Science at Dana-Farber Cancer Institute (DFCI) and Harvard University\, until she joined GV20 full-time in 2022. Her research work focused on algorithm development and data integration modeling for translational cancer research. She has published over 270 papers and has an H-index of 117. Dr. Liu is a fellow of the International Society of Computational Biology (ISCB)\, American Institute for Medical and Biological Engineering (AIMBE) and was a Breast Cancer Research Foundation Investigator (2017-2021). She is a recipient of the Sloan Research Fellowship (2008)\, Weitzman Outstanding Early Career Investigator Award from the Endocrine Society (2016)\, ISCB Innovator Award (2020)\, and the Benjamin Franklin Award for Open Access in the Life Sciences (2020). Her lab has mentored 27 PhD and postdoctoral trainees to independent academic careers.\n\nhttps://umich-health.zoom.us/j/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09
UID:115352-21834562@events.umich.edu
URL:https://events.umich.edu/event/115352
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Life Science,Talk,Structural Biology,seminar,Science,Research,Public Health,Precision Health,Physics,Pediatrics,Michigan Engineering,Medicine,Mathematics,Applications,Discussion,Basic Science,Biology,Biomedical Engineering,Biosciences,Cardiovascular,Chemistry,Lecture,Education,Electrical Engineering and Computer Science,Engineering,Free,Graduate Students,Human Genetics,Information and Technology,Learning Health Systems
LOCATION:Palmer Commons - Forum Hall
CONTACT:
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BEGIN:VEVENT
DTSTAMP:20231203T140517
DTSTART;TZID=America/Detroit:20231213T160000
DTEND;TZID=America/Detroit:20231213T180000
SUMMARY:Workshop / Seminar:GeomTopDyn Seminar: Images of algebraic groups and mixing properties.
DESCRIPTION:Let G be an algebraic group over a local field.\nWe will show that generally the image of G under an arbitrary continuous homomorphism into a (Hausdorff) topological group is closed. We will show how mixing properties of unitary representations follow from this topological property.
UID:115724-21835432@events.umich.edu
URL:https://events.umich.edu/event/115724
CLASS:PUBLIC
STATUS:CONFIRMED
CATEGORIES:Mathematics
LOCATION:Off Campus Location - 3866
CONTACT:
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