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Author Information
Mihaela van der Schaar (University of Cambridge and UCLA)
Professor van der Schaar is John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge, a Turing Faculty Fellow at The Alan Turing Institute in London, and Chancellor's Professor at UCLA. She was elected IEEE Fellow in 2009. She has received numerous awards, including the Oon Prize on Preventative Medicine from the University of Cambridge (2018), an NSF Career Award (2004), 3 IBM Faculty Awards, the IBM Exploratory Stream Analytics Innovation Award, the Philips Make a Difference Award and several best paper awards, including the IEEE Darlington Award. She holds 35 granted USA patents. In 2019, she was identified by National Endowment for Science, Technology and the Arts as the female researcher based in the UK with the most publications in the field of AI. She was also elected as a 2019 "Star in Computer Networking and Communications". Her current research focus is on machine learning, AI and operations research for healthcare and medicine. For more details, see her website: http://www.vanderschaar-lab.com/
More from the Same Authors
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2022 Poster: Data-SUITE: Data-centric identification of in-distribution incongruous examples »
Nabeel Seedat · Jonathan Crabbé · Mihaela van der Schaar -
2022 Poster: Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations »
Nabeel Seedat · Fergus Imrie · Alexis Bellot · Zhaozhi Qian · Mihaela van der Schaar -
2022 Spotlight: Data-SUITE: Data-centric identification of in-distribution incongruous examples »
Nabeel Seedat · Jonathan Crabbé · Mihaela van der Schaar -
2022 Spotlight: Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations »
Nabeel Seedat · Fergus Imrie · Alexis Bellot · Zhaozhi Qian · Mihaela van der Schaar -
2021 : Quantitative epistemology: conceiving a new human-machine partnership »
Mihaela van der Schaar -
2021 : Synthetic Healthcare Data Generation and Assessment: Challenges, Methods, and Impact on Machine Learning »
Ahmed M. Alaa · Mihaela van der Schaar -
2020 : Panel Discussion »
Neil Lawrence · Mihaela van der Schaar · Alex Smola · Valerio Perrone · Jack Parker-Holder · Zhengying Liu -
2020 : "Automated ML and its transformative impact on medicine and healthcare" by Mihaela van der Schaar »
Mihaela van der Schaar -
2020 : Invited Talk: Learning despite the unknown - missing data imputation in healthcare »
Mihaela van der Schaar -
2019 Poster: Validating Causal Inference Models via Influence Functions »
Ahmed Alaa · Mihaela van der Schaar -
2019 Oral: Validating Causal Inference Models via Influence Functions »
Ahmed Alaa · Mihaela van der Schaar -
2018 Poster: AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning »
Ahmed M. Alaa · Mihaela van der Schaar -
2018 Oral: AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning »
Ahmed M. Alaa · Mihaela van der Schaar -
2018 Poster: Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design »
Ahmed M. Alaa · Mihaela van der Schaar -
2018 Oral: Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design »
Ahmed M. Alaa · Mihaela van der Schaar -
2017 Poster: Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis »
Ahmed M. Alaa · Scott B Hu · Mihaela van der Schaar -
2017 Talk: Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis »
Ahmed M. Alaa · Scott B Hu · Mihaela van der Schaar