Staff profile

Professor Ashiq Anjum

Professor of Distributed Systems




College of Engineering and Technology


Electronics, Computing and Mathematics


Markeaton Street, Derby Campus



I have been part of the EC funded projects in distributed systems and large scale analytics such as Health-e-Child (IP, FP6), neuGrid (STREP, FP7) and TRANSFORM (IP, FP7) where I investigated resource management and optimization issues of large scale distributed systems and provided platforms for high performance data analytics.

I work with healthcare providers, hospitals and pharma companies to investigate high performance analytics systems for distributed clinical intelligence and integration, iterative genome analytics and precision medicine.

I am closely working with logistics companies to investigate smart logistical models using innovative IoT technologies and Machine Learning approaches for intelligent stock tracking, warehousing and distributed supply chain management optimization.

I have also been investigating large scale distributed systems and analytics platforms for the LHC data in collaboration with CERN Geneva Switzerland for the last fifteen years. Before starting an academic career, I worked for various software multinational companies for around ten years.

Teaching responsibilities

Professional interests

I am keen to build partnerships with colleagues from industry and academia. I am always looking for bright PhD students who are keen to make a difference.

Research interests

Membership of professional bodies


Undergraduate qualifications

Postgraduate qualifications

Research qualifications

Recent conferences

Conference and Reviews

Talks and Participation in International Events

Professional Development Workshops and Schools

Experience in industry

International experience

Research Grants

VR enabled adaptive visualizations for Engineering Systems

This challenging research project (2018-2020,  Innovate UK) aims to enable real time big data visualization in a VR environment.

Smart Logistics & Intelligence Management System (SLIMS)

This project (2018-2020,  Innovate UK) aims to investigate innovative IoT (Internet of Things) technologies combined with Machine Learning approaches for intelligent Logistics and supply chain management systems.

Train Network Graph Modelling for Scheduling and Management (2018, Resonate Rail)

This project aims to model the UK rail network as a Graph System and provide an adaptive scheduling and resource management System.

Blockchain System for IoT data Integration and Analytics (2017-2019) 

This project (funded by Roche Molecular USA) aims to investigate a blockchain based distributed ledger infrastructure for trusted management of data coming from IoT devices in Healthcare.  The project will develop a HyperLedger based infrastructure for an immutable and verifiable record of transactions between patients, investigators and IoT devices.

Clinical and Genomics Data Analytics for Personalized HealthCare (2015-2019)

This project (funded by Hoffmann-La Roche Switzerland) aims to integrate clinical and genomics data coming from clinical trials, real world data and sequencing machines to provide Healthcare analytics for personalized treatments.  An In-Memory cloud computing platform will analyze the integrated data for Healthcare analytics, cross study analytics and formulation of statistical evidence. 

Video Stream Analytics System for real time Object Classification (2012-2017)

The Stream Cloud project (funded by the Technology Strategy Board) aims to develop an end-to-end solution for batch and real-time analysis of video streams using cloud computing. A software library will be developed to exploit the cloud computing potential for extracting and deriving important features from recorded video streams.

Additional interests and activities

Journal Editorship and Peer Review

In the media

Recent publications

Journal Articles

Conference Articles and Book Chapters