Research Output per year
Personal profile
Personal information
Bernd Heidergott is professor of Stochastic Optimization at the department of Econometrics and Operations Research of the Vrije Universiteit Amsterdam. He is working at the VU since 2002. Before that he worked at the TU Eindhoven, at EURANDOM, at DIAM, and at the Erasmus University Rotterdam. He obtained his PhD in 1996 at the University of Hamburg, Germany.
From 2013 to 2018 be served as Program Director Econometrics and Operations Research.
Currently, he is Board Member of Amsterdam Business Research Institute.
Research
His research interests are:
- Simulation based stochastic optimization
- Model and parameter inscecurity
- Risk analysis and financial engineering
-Differentiation theory of stochastic models
- Max-plus algebra
Ancillary activities
No ancillary activities
Ancillary activities are updated daily
Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
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Markov processes
Engineering & Materials Science
Markov chain
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Derivatives
Engineering & Materials Science
Queue
Mathematics
Taylor series
Engineering & Materials Science
Gradient Estimation
Mathematics
Estimator
Mathematics
Perturbation Analysis
Mathematics
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 1995 2019
Naïve learning in social networks with random communication
Huang, J. P., Heidergott, B. & Lindner, I., 1 Jul 2019, In : Social Networks. 58, p. 1-11 11 p.Research output: Contribution to Journal › Article › Academic › peer-review
Social Support
social network
Communication
Learning
communication
The Jump Start Power Method: A New Approach for Computing the Ergodic Projector of a Finite Markov Chain
Berkhout, J. & Heidergott, B. F., 2019, (Accepted/In press) In : Journal of Scientific Computing.Research output: Contribution to Journal › Article › Academic › peer-review
Power Method
Projector
Markov processes
Markov chain
Numerical methods
A new unbiased stochastic derivative estimator for discontinuous sample performances with structural parameters
Peng, Y., Fu, M. C., Hu, J. Q. & Heidergott, B., Mar 2018, In : Operations Research. 66, 2, p. 487-499 13 p.Research output: Contribution to Journal › Article › Academic › peer-review
Derivatives
Estimator
Structural parameters
Experiments
Perturbation
Efficient Updating of Node Importance in Dynamic Real-Life Networks
Berkhout, J. & Heidergott, B. F., Jul 2018, In : IFAC-PapersOnLine. 51, 7, p. 64-69 6 p.Research output: Contribution to Journal › Article › Academic › peer-review
Internet
Naive Learning in Social Networks with Random Communication
Heidergott, B. F., Huang, J. & Lindner, I., 2018, 018/II ed., Amsterdam: Tinbergen Institute, 33 p. (TI Discussion Paper Series; vol. 2018, no. 018/II).Research output: Working paper › Academic
Activities 2005 2005
- 1 Conference
1st International Seminar on Railway Operations Modeling and Analysis
B.F. Heidergott (Organiser)8 Jun 2005
Activity: Participating in or organising an event › Conference › Academic
Prizes
honors and awards
Habilitation in Wiskunde aan de Universiteit Hamburg, Duitsland
B.F. Heidergott (Recipient), 2005
Prize › Academic