Eleni Daskalaki

Honorary Senior Lecturer

Picture of Eleni Daskalaki


+61 2 6125 6188

Data Science


Google Scholar



Areas of expertise

  • Artificial Intelligence And Image Processing 0801
  • Control Systems, Robotics And Automation 090602
  • Pattern Recognition And Data Mining 080109
  • Electrical And Electronic Engineering 0906
  • Signal Processing 090609
  • Biomedical Engineering Not Elsewhere Classified 090399
  • Simulation And Modelling 080110
  • Performing Arts And Creative Writing


Research Interests
Machine/deep learning, reinforcement learning, control systems, signal processing, time-series analysis, unsupervised learning, sensing applications


Dr Eleni Daskalaki received her 5-year Dipl-Ing in Electrical and Computer Engineering from the National Technical University of Athens, Greece in 2009 and her PhD in Biomedical Engineering from the University of Bern, Switzerland in 2013. Her doctoral research was on the design and development of reinforcement learning-based control algorithms and adaptive prediction models for glucose regulation in type 1 diabetes. Her main contribution on personalisation of insulin treatment resulted in a patent application. After her PhD, Dr. Daskalaki was engaged for two years as project associate at the European Organization for Nuclear Research (CERN), Geneva, where she worked in different engineering areas, among which, the design of control algorithms for the phase regulation of the Compact Linear Collider klystrons. Subsequently she was engaged at the Swiss Center for Electronics and Microtechnology (CSEM), Neuchatel, a private research company, first as a post-doctoral researcher and then as a R&D engineer. Her work focused on the development of signal processing algorithms for radiofrequency-based sensing applications and radar-based remote sensing of human vital signs. She led a research project on the development of machine/deep learning (ML/DL) algorithms for anomalies and events detection in multivariate time-series. Currently, she is a research fellow in Computer Science, mainly working for the OHIOH grand challenge. Her work focuses on the development of ML/DL strategies for the improvement of diagnosis and management of diabetes and multiple sclerosis, but also expands in the broader field of data processing in medical applications.

Activities & Awards

Journal Publications

You are on Aboriginal land.

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

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