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SUMMARY:Time-series Machine Learning Models for Healthcare: Advancements a
 nd Applications - Tingting Zhu\, University of Oxford
DTSTART:20231128T160000Z
DTEND:20231128T170000Z
UID:TALK203644@talks.cam.ac.uk
CONTACT:Cecilia Mascolo
DESCRIPTION:Artificial intelligence plays a crucial role in digital health
  and represents a vibrant and dynamic research field with profound implica
 tions for how we'll care for future generations. In my talk\, I will discu
 ss the advancement of time-series machine learning models tailored to addr
 ess the challenges and opportunities posed by the vast volume of modern he
 althcare data and their practical applications. Furthermore\, I will share
  insights from my journey towards realising digital twins\, with a specifi
 c emphasis on data synthesis and treatment recommendations.\n\nBiography: 
 \nProfessor Tingting Zhu graduated with the DPhil degree in information an
 d biomedical engineering at Oxford University in 2016. This followed her M
 Sc in Biomedical Engineering at University College London and BEng (Hons) 
 in Electrical Engineering from the University of Malta. \n\nAfter DPhil\, 
 Tingting was awarded a Stipendiary Junior Research Fellowship at St. Hilda
 's College\, Oxford. In 2018\, Tingting was appointed as the first Associa
 te Member of Faculty at the Department of Engineering Science\; in 2019\, 
 following the award of her Royal Academy of Engineering Research Fellowshi
 p\, she was appointed to full Member of Faculty at the Department of Engin
 eering Science. Tingting is a Non-Tutorial Fellow at Kellogg College and a
  Stipendiary College Lecturer at Mansfield College.
LOCATION:Computer Lab\, FW11 and Online (zoom link on this page)
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