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Personal profile

Research profile

Elena Mocanu is a researcher in Machine Learning and Autonomous Systems within the Control System Technology group, Department of Mechanical Engineering, Eindhoven University of Technology (TU/e) since February 2018.

Academic background

Elena Mocanu received her B.Sc. degree in Mathematics and Physics from Transilvania University of Brasov, Romania, in 2004. After four years as mathematics and physics teacher at high-school level, Elena moved to the university. She has been an Assistant Lecturer within the Department of Information Technology, University of Bucharest, Romania from September 2008 to January 2011. In parallel, in 2009 she started a master program in Theoretical Physics. In 2011 she obtained the M.Sc. degree with specialization in Quantum Transport from University of Bucharest, Romania.

In January 2011, Elena moved from Romania to Netherlands. She obtained the M.Sc. degree in Operations Research from Maastricht University, The Netherlands, in 2013. In the last year of her master program, she did a six months Internship at Mastricht University on bioinformatics data analytics research and a six months graduation project at NXP Semiconductors, Eindhoven. In her master thesis she has investigated deep learning methods for "People detection for building automation".

In October 2013, Elena started her PhD research in Machine Learning and Smart Grids at TU/e. In January 2015 she performed a short research visit at the Technical University of Denmark and, from January to April 2016 she was a visiting researcher at University of Texas at Austin, USA. In 2017, Elena received her Doctor of Philosophy degree in Machine learning and Smart Grids from TU/e.

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.

Learning systems Engineering & Materials Science
Energy utilization Engineering & Materials Science
Intelligent buildings Engineering & Materials Science
Advanced metering infrastructures Engineering & Materials Science
Agglomeration Engineering & Materials Science
Smart meters Engineering & Materials Science
Reinforcement learning Engineering & Materials Science
Bayesian networks Engineering & Materials Science

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Research Output 2014 2018

5 Citations (Scopus)

Deep learning versus traditional machine learning methods for aggregated energy demand prediction

Paterakis, N. G., Mocanu, E., Gibescu, M., Stappers, B. & van Alst, W., 16 Jan 2018, 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2017 - Proceedings. Piscataway: Institute of Electrical and Electronics Engineers (IEEE), p. 1-6 6 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Learning systems
Multilayer neural networks
Linear regression
Artificial intelligence
Support vector machines

Deep reinforcement learning for scheduling

Mocanu, E., Nguyen, H. P. & Gibescu, M., 2018, (Accepted/In press) Proceedings of 2018 IEEE Power and Energy Society General Meeting (PESGM), 5-10 August 2018, Portland, Oregon. Piscataway: Institute of Electrical and Electronics Engineers (IEEE)

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)

Enabling cooperative behavior for building demand response based on extended joint action learning

Hurtado Munoz, L. A., Mocanu, E., Nguyen, H. P., Gibescu, M. & Kamphuis, I. G., 1 Jan 2018, In : IEEE Transactions on Industrial Informatics. 14, 1, p. 127-136

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
Reinforcement learning
Decision making

One-shot learning using Mixture of Variational Autoencoders: A generalization learning approach

Mocanu, D. C. & Mocanu, E., 11 Jul 2018, 17th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2018. Dastani, M., Sukthankar, G., André, E. & Koenig, S. (eds.). International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), Vol. 3, p. 2016-2018 3 p.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
Learning algorithms
Deep learning
8 Citations (Scopus)

On-line building energy optimization using deep reinforcement learning

Mocanu, E., Mocanu, D. C., Nguyen, H. P., Liotta, A., Webber, M. E., Gibescu, M. & Slootweg, J. G., 8 May 2018, In : IEEE Transactions on Smart Grid.

Research output: Contribution to journalArticleAcademicpeer-review

Reinforcement learning
Advanced metering infrastructures
Energy management systems
Electric vehicles
Power generation


3E-Royal SMIT- De Kuyper Award

Elena Mocanu (Recipient), 2016

Recognition: OtherDiscipline relatedProfessional

WISE-Network Travel Grant for the IEEE PES General Meeting 2015 conference

Elena Mocanu (Recipient), 2015

Recognition: OtherScholarshipsScientific

Activities 2015 2018

  • 3 Invited talk
  • 1 Visiting an external academic institution

Adaptive and Sparse Neural Networks

Elena Mocanu (Speaker)
24 May 2018

Activity: Talk or presentation typesInvited talkScientific

University of Texas at Austin

Elena Mocanu (Visiting researcher)
16 Jan 201616 Apr 2016

Activity: Visiting an external institution typesVisiting an external academic institutionScientific

High-order RBM for electrical patterns estimations

Elena Mocanu (Speaker)
Apr 2016

Activity: Talk or presentation typesInvited talkScientific

Deep Learning to estimate building energy demands in the smart grid context at Technical University of Denmark

Elena Mocanu (Member)
16 Jan 2015

Activity: Talk or presentation typesInvited talkScientific