Dr Ashraf Mahmud

Areas of interest
His research interest includes the
Smart grid, Smart Cities, Data Science, Machine Learning, Big Data analytics, Internet
of Things, Computer Networks and Wireless Communications.
Teaching
He is currently teaching Computer Network, Programming C++ and Big Data Analytics.Background
Ashraf is an associate lecturer at University of Reading. He worked as a lecturer at York St Johns University. He was module leader of Internet of Things. He was a Research Associate for the ReFLEX project, funded by the UKRI. He is a multidisciplinary approach aided by his Master degrees in Computer Science as well as Statistics. Diverse experience including 15 years industry/professional experience to support Higher Education teaching and research. Current research focuses on Smart Grid, Smart Cities, Computer Networking, Data Science, Internet of Things. Skilled in supporting learning in different contexts. Management experience.
Ashraf obtained his PhD in Computer
Science in 2019 from the University of Bedfordshire, UK, where he worked
on the Smart Grid. He has a number of publications. His research was on
designing the demand response pricing model by using simultaneous perturbation
stochastic approximation in the Smart Grid.
From 2015 to 2021, he worked as a Lecturer at the University of Bedfordshire. Prior to that, between 2004 and 2014, he worked as a Head of Student Services and IT Manager at ICON College of Technology and Management. Over the period of time, he also served as an IT Consultant at IT Anywhere which provides smart hardware and software solutions.
Academic qualifications
2019 PhD in Computer Science, University of Bedfordshire2006 MSc in Computer Science, University of East London
2003 Master of Information Technology, Charles Stuart University
1999 Master of Statistics, University of Dhaka
Professional bodies/affiliations
2017 Fellow of Higher Education Academy
2012 Member of IEEE
Selected publications
https://scholar.google.co.uk/citations?user=YU724DEAAAAJ&hl=enhttps://dblp.org/pid/204/8689.html
Mahmud,
AA, Sant, P, Flynn, D (in review) (2021): The Novel Real-Time Price Suggestions
(RTPS) model for the Smart Grid via Stochastic Approximation, IEEE Open Access.
Mahmud, AA., Sant, P., Tariq, F.,
Jazani, D. (2017) A Real-Time monthly DR Price system for the Smart Energy
Grid. EAI Endorsed Transactions on Energy Web 17(13): e3. Available at http://eudl.eu/doi/10.4108/eai.3-8-2017.152981
Mahmud,
A, Flynn, D (2021), (Review)Smart Energy Management for Prosumers in Local
Energy Communities
Mahmud,
A, Flynn, D (2021), (Review), Artificial
Intelligence (AI)-based identification of appliances in households through NILM
Mahmud,
AA., Sant, P., Jazani, D. (2016) Empirical analysis of real-time pricing mechanisms
for demand-side management: Contemporary Review. International Conference
on Future Generation Communication Technologies. Available at https://ieeexplore.ieee.org/abstract/document/7605071/
Mahmud,
AA., Sant, P., (2017) Real-Time price savings through price suggestions for the
Smart Grid demand Response Model. International Conference on Smart Grid
and Smart Cities. Available at https://ieeexplore.ieee.org/abstract/document/7947603/
Mahmud AA., Sant, P., (2018) Real-Time
Price Suggestion through Stochastic approximation in the Smart Grid, 6th
IEEE International Conference on Smart Energy Grid Engineering (SEGE)
Mahmud,
AA. (2006) An investigation into the factors that contribute to improvement in
the performance of a network, (University of East London, UK)