Professor Mihaela van der Schaar

Engineering
Ordinary Student; Man Professor of Quantitative Finance

Qualifications

Ph.D. Electrical and Computer Engineering, The University of Eindhoven, The Netherlands

Academic Background

2011-2016       Chancellor’s Professor, Electrical and Computer Engineering, Professor of Computer Science (by courtesy), University of California Los Angeles (UCLA)
2005-2011       Assistant to Full Professor, University of California Los Angeles (UCLA)
2003-2005       Assistant Professor, University of California Davis (UC Davis)
2003                Adjunct Assistant Professor, Columbia University
1998-2003       Senior Member Research Staff and Project Leader, Philips Research, Briarcliff Manor, USA
1996-1998       Research Scientist, Philips Research, Eindhoven, The Netherlands

Research Interests

Machine learning for medicine, education, finance.

Publications

A full list of publications are available on Professor van der Schaar's Google Scholar page.

Machine Learning for Medicine
A. Alaa, J. Yoon, S. Hu and M. van der Schaar, "Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes," IEEE Trans. on Biomedical Engineering, 2017.
A. Alaa, S. Hu, and M. van der Schaar, "Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis," International Conference on Machine Learning (ICML), 2017.
A. Alaa and M. van der Schaar, "Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition," Neural Information Processing Systems (NIPS), 2016.
W. Hoiles and M. van der Schaar, "A Non-parametric Learning Method for Confidently Estimating Patient's Clinical State and Dynamics," Neural Information Processing Systems (NIPS), 2016.
J. Yoon, A. Alaa, S. Hu, M. van der Schaar, "ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission," International Conference on Machine Learning (ICML), 2016.

Game Theory
M. van der Schaar, Y. Xiao, W. Zame, "Efficient Outcomes in Repeated Games with Limited Monitoring," Economic Theory, vol. 60, no. 1, pp. 1-34, 2015 - Lead article.
Y. Zhang and M. van der Schaar," Reputation-based Incentive Protocols in Crowdsourcing Applications," IEEE Infocom, 2012

Distributed and Multi-agent Learning
C. Tekin and M. van der Schaar, "Distributed Online Learning via Cooperative Contextual Bandits," IEEE Trans. Signal Processing (TSP), vol. 63, no. 14, pp. 3700-3714, 2015.
F. Fu and M. van der Schaar, "Learning to Compete for Resources in Wireless Stochastic Games," IEEE Trans. Vehicular Technology, vol. 58, no. 4, pp. 1904-1919, May 2009.

Wireless Networks and Multimedia Streaming
H. P. Shiang and M. van der Schaar, "Queuing-Based Dynamic Channel Selection for Heterogeneous Multimedia Applications over Cognitive Radio Networks," IEEE Trans. Multimedia (TMM), Vol. 10, no.5, pp. 896-09, Aug. 2008.