Machine Learning, Data Science











About me


Im currently a Data Scientist, Ml & AI at RBC, and part of Data and Analytics team. I completed my PhD in biomedical Engineering with focus in Machine Learning with Alex Mihailidis at the University of Toronto in 2016. Subsequently, I held a postdoctoral fellowship at UHN with Babak Taati.


Please contact me at elham.dolatabadi@rbc.com




Vector Institute for Artificial Intelligence.




      Jun 2018: I will be attending and presenting a poster at DLRL Summer School.

      Jun 2018: I will present a tutorial on hyperparameter optimization using Gaussian processes at our CV journal club.

      June 2018: I will be joining RBC as a machine learning Data Scientist.

      Feb 2018: I became affiliated with the Vector Institute for AI. 

      Apr 2018: I will review Scalable and accurate deep learning for electronic health records at our CV journal club

      Dec 2017: I will give a cloud computing tutorial (SciNet basics) at our CV journal club.

      Nov 2017: I will give a hands-on tutorial on training a Recurrent Neural Networks (RNN) in TensorFlow.

      Jun 2017: I will review these two papers at our CV journal club:

  Assessing gait stability: The influence of state space reconstruction on inter- and intra-day reliability of local dynamic stability during over-ground walking, by K. S. van Schooten et al.

  A practical method for calculating largest Lyapunov exponents from small data sets, by M. T. Rosenstein et al.

      Oct 2016, I will continue with GPs, reading Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data by Neil Lawrence at CV journal club.

      Sep 2016: I will provide a tutorial on Gaussian Processes, going over Chapter 2 of Rasmussen and Williams' book, at our CV journal club.