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​Rami N. Khushaba
PhD, M.Sc., B.Sc., Senior Member - IEEE

​Positions
  • Senior Planning and Modelling Scientist from Sep 2021 - till Day
           Planning and Modelling
            Sydney Trains
  • Equipment Automation Theme Lead/Senior Research Fellow from Feb 2020 - Sep 2021
            Australian Center for Field Robotics (ACFR)
          University of Sydney
  • Team Lead, Data Science from August 2019 - Feb 2020
            Data Science Team
            BuildingIQ​​
  • ​Senior Data Scientist from March 2017 - July 2019
            Data Science Team 
            BuildingIQ​​
  • ​Algorithms Development Engineer from June 2012 - till Feb 2017
           Chronic Disease Management  - Applied Research
            ResMed Ltd.
  • Postdoctoral Research Fellow from Jan 2010 - till June 2012
           School of Electrical, Mechanical, and Mechatronic Systems
           FEIT, University of Technology Sydney (UTS)
  • Lecturer and Tutor from Sep 2007 - till Nov 2009
           School of Electrical, Mechanical, and Mechatronic Systems
          FEIT, University of Technology Sydney (UTS)

Degrees:
  • PhD in Engineering - University of Technology, Sydney (UTS)                       - 2010 (Signal Processing/Machine Learning - Myoelectric Control)
  • M.Sc in Electronics Engineering - University of Technology                          - 2001 (VLSI of Artificial Neural Networks)
  • B.Sc in Computers and Control Engineering - University of Technology - 1999 (Remote Control of Robotic Arms)


​Courses:
Deep Learning and Neural Networks                                                                                                                - DeepLearning.ai
Improving Deep Neural Networks: Hyperparameters tuning, Regularization and Optimization   - DeepLearning.ai
Structuring Machine Learning Projects                                                                                                             - DeepLearning.ai
Convolutional Neural Networks                                                                                                               - DeepLearning.ai
 Sequence Models                                                                                                                                        - DeepLearning.ai
Foundations of Heart Rate Variability                                                                                                     - HRVcourse
LEAN4x4 Continuous Improvement Progress                           -P2 Capabilities Pty Ltd (Completed October 2015 - 2 days course)
Exercise Physiology: Understanding the Athlete Within        - Online Courses - The University of Melbourne-(Completed Sep 2014).
Fundamentals of Sleep Medicine                                                  - In-person training - University of Sydney -(Completed Nov 2013)
Computational Methods for Data Analysis                                - Online Courses University of Washington(Completed March 2013).
Programming a Robotic Car - UDACITY                                      - Online Courses (Completed April 2012).
Machine Learning      - Stanford University                                 - Online Courses - By Prof. Andrew Ng.(Completed Dec 2011).
Artificial Intelligence - Stanford University                                 - Online Courses. (Completed)
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Research Areas:
Signal Processing, Machine Learning, Data Analytics, Neural Engineering, Pattern Recognition, Human Factors, Myoelectric Control, Human-Robot-Interaction, Sleep Disordered Breathing, Evolutionary Algorithms, and Fuzzy Logic.


Projects Description:
- Predictive energy optimization and modelling, descriptive/diagnostic analytics, big data, & machine learning.
- Neural Control of Prosthetic Devices (Myoelectric Control + Brain Computer Interfaces)
- Driver Drowsiness/Fatigue Detection.
- Human-Machine Interaction.
- Consumer Neuroscience (Neuromarketing).
- Non-Contact Detection of Sleep and Breathing Patterns 
   (Apnea-Hypopnea Index Calculation, Sleep/Wake Analysis, Respiratory/Heart Rate      
    Detection, Cheyne-Stokes Respiration Detection, etc...).
- Data Science.

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Membership: 
- IEEE Senior member - July 2015
- IEEE Computational Intelligence Society
- IEEE Computer Society
- IEEE Engineering in Medicine and Biology Society
- IEEE Signal Processing Society
- IEEE Robotics and Automation Society
- IEEE Systems, Man, and Cybernetics Society
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