Cristina Heghedus

1

Cristina Heghedus

Ph.D. started in: 2016
Year of graduation: 2020
COINS consortium member: University of Stavanger
Supervised by: Chunming Rong, Antorweep Chakravorty
Links: Cristin
Research area: Models and Protocols
Project title: Dara driven energy informatics
Project description: The background for my PhD lies in the constantly growing amount of data. The Internet of Things and Big Data requires permanent evolvement of the methods/models being used in order to analyze and improve behavior of the objects. During my PhD I will explore these methods and datasets. I am interested in making a contribution in peoples life. They must feel safe and secure about their lifestyle and personal information.

Publications:

  1. Cristina Viorica Heghedus, Antorweep Chakravorty, Rong Chunming (2020). Deep Learning for Short-Term Energy Load Forecasting Using Influential Factors
  2. Cristina Viorica Heghedus, Rong Chunming (2020). Artificial Intelligence Models Used for Prediction in the Energy Internet
  3. Cristina Viorica Heghedus, Antorweep Chakravorty, Chunming Rong (2019). Neural Network Frameworks. Comparison on Public Transportation Prediction
  4. Cristina Viorica Heghedus, Santiago Segarra, Antorweep Chakravorty, Chunming Rong (2019). Neural Network Architectures for Electricity Consumption Forecasting
  5. Cristina Viorica Heghedus, Anton Shchipanov, Rong Chunming (2019). Advancing Deep Learning to Improve Upstream Petroleum Monitoring
  6. Cristina Viorica Heghedus, Anton Shchipanov, Chunming Rong (2019). Pattern Recognition and Flow Rate Reconstruction: PDG Data Analysis Using Machine Learning
  7. Cristina Viorica Heghedus, Antorweep Chakravorty, Rong Chunming (2018). Deep Learning For Short-Term Energy Load Forecasting Using Influential Factors
  8. Cristina Viorica Heghedus, Antorweep Chakravorty, Rong Chunming (2018). Energy Informatics Applicability; Machine Learning and Deep Learning
  9. Cristina Viorica Heghedus, Antorweep Chakravorty, Rong Chunming (2018). Energy Load Forecasting Using Deep Learning
  10. Anton Shchipanov, Roman Berenblyum, Alexey A. Khrulenko, Lars Kollbotn, Rong Chunming, Cristina Viorica Heghedus, Fredrik Haugsand (2018). Well Data Analytics: from Case Studies to Solutions
  11. Cristina Viorica Heghedus (2017). Ph.D. Forum: Forecasting Public Transit Using Neural Network Models
Courses attended:
  1. IMT6002 COINS Winter School (NTNU), 3 ECTS, 2017
Events attended with COINS funding:
  1. COINS Ph.D student seminar, Longyearbyen, Svalbard, Norway, 2018
  2. NISK 2018, Longyearbyen, Svalbard, Norway, 2018
  3. COINS Finse winter school, Finse, Norway, 2017
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