[July-22   till   Now]   Assistant Professor, Air University Islamabad, Pakistan.

[Oct-21 to May 22]   Research Fellow (Post-Doctorate), East Anglia University, England, UK.

[Aug-21 to Sep-21]   Assistant Professor, Air University Islamabad, Pakistan.

[Jan-17 to Dec-20]    PhD Electrical Engineering, Newcastle University, Australia. 

[Aug-13 to Dec-16]   Research Associate, COMSATS University Islamabad, Pakistan. 

[Aug-13 to Sep-15]   MS Electrical Engineering, COMSATS University Islamabad, Pakistan. 

[Aug-09 to Sep-13]   BS Electrical Engineering, COMSATS University Islamabad, Pakistan. 


Ashfaq Ahmad is currently working as Assistant Professor in electrical and computer engineering department at Air University Islamabad, Pakistan. Previously, he served as Research Fellow in Artificial Intelligence Laboratory within the School of Computing Sciences at the University of East Anglia, United Kingdom.  Where, he carried investigations towards project 'REMeDY—Spearheading a revolution in energy market design', funded by Innovate UK [details on: REMeDY, UEA, UKRI]. Project REMeDY involved collaborations with local authorities, commercial organisations and academic institutions including Imperial College London, SMS Energy Services Limited, Vital Energi Utilities Limited, Places for People Group Limited (FutureGov. Ltd), University of East Anglia, and Southend on Sea Borough Council.

Dr. Ahmad also worked in ComSens Research Lab at COMSATS University Islamabad as Research Associate. He did PhD in electrical engineering from the University of Newcastle, Australia, and the BS and MS degrees in electrical engineering from COMSATS University Islamabad, Pakistan. He has (co-)authored 40+ research publications in technical international journals and peer-reviewed international conferences. He has served and is actively serving as Associate Editor, Guest Editor, Invited Reviewer and  Technical Program Committee (TPC) member of several prestigious international journals and conferences/workshops. He is currently investigating the applications of machine learning and optimization techniques for the future energy internet, not limited to, but in the following potential areas.


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