Professor Ashiq Anjum

I am a professor of Distributed Systems at the University of Leicester and the director of enterprise and impact for the School of Computing and Mathematical Sciences at Leicester.  Previously I have been the director of the data science research centre. My areas of research include data intensive distributed systems, distributed machine learning models, self-adapting federated digital twins and physics informed machine learning models for digital twins. I have been investigating digital twins to emulate the real time behaviour of (bio)mechanical and cyber-physical systems.

My research work has been funded through a number of research grants including the current EPSRC projects in AI driven digital twins for net zero (EP/Y00597X/1) and clinical care (EP/Y018281/1)  and the EU funded projects on distributed clinical intelligence, modelling and iterative genome analytics. I am also the AI lead for METEOR that is the £60 Million flagship project at the Space Park Leicester. I have been investigating distributed analytics platforms for the LHC data in collaboration with CERN Geneva Switzerland for the last twenty years. I also closely work with telecom, aerospace, rail and automobile companies to investigate self-learning digital twins and distributed machine learning platforms for intelligently analyzing IoT data streams for accuracy, reliability, safety and capacity. I am also actively collaborating with leading VR providers to commoditise AI driven digital twins and enable real time physics informed and distributed machine learning algorithms for augmented and virtual reality environments with applications in health, aerospace and telecom.

I have secured grants from EPSRC, RCUK, STFC, UKRI, Innovate UK, European Commission and other funding agencies for investigating distributed learning systems for producing intelligence and evidence for medical, security, object tracking, manufacturing, telecom and space science applications. Examples of funded projects include: self-learning digital twins for cyber-physical systems, distributed video streams analytics for real time object tracking and classification,  distributed clinical integration and intelligence, distributed and delay sensitive immersive visualizations and high performance iterative genome analytics for personalized medicine.  

Industrial Collaborations: As a director of data science as well as the director of enterprise and impact, I have been actively involved in both academic and industrial research for over a decade with leading companies in the world such as BT, CGI, Roche, Siemens, Microsoft, SAP, Google, Rolls Royce and Bombardier. I have led projects of extreme importance to these companies, leading to impact and intellectual property of significant value.  I also developed around 15 knowledge transfer partnerships with regional SMEs. During the process, we have exploited the knowledge in systems, artificial intelligence and digital twins for the benefit of these companies and also produced new knowledge and insights by solving real-world problems that helped us in producing new research ideas and impact. My work with industry has so far produced two impact case studies, generated over £5 Million in research income, produced numerous opportunities for undergrad and postgraduate students and developed industrial research opportunities for the research students.

More precisely, I have been undertaking research and development in distributed digital twins for cyber-physical systems with applications in telecoms, aerospace, earth observation and digital manufacturing. I have been closely working with leading industrial partners including Rolls Royce, Bloc Digital and BT in realizing the aim of self-learning digital twins. I have been investigating AI driven digital twins that can transform engineering data into VR based 3D models. I secured four KTPs through a local SME (Bloc Digital) in the areas of data driven and performance aware digital twins. Using CAD/CAM models, we have been able to produce digital twins of complete machines such as gas turbines and aircraft engines in a fraction of time that otherwise used to take months. I have been working with BT to produce a digital twin of data centres where all aspects of the data centre will be digitally twinned including routers, switches, servers and network traffic. The output digital twin will be used to deliver energy efficiencies, safety critical maintenance and critical 5G deployments. I have been working with Space Park Leicester (SPL) to investigate digital twins for twinning the earth for floods, Net Zero,  droughts, environmental degradation and landscape modelling. I am also collaborating with SPL’s partners such as Airbus and CGI to investigate thermal digital twins as well as building digital twins to forward plan potential scenarios that may be encountered in space missions.  

Health and Scientific Collaborations: I am also closely working with healthcare providers, hospitals and pharma companies in investigating self adapting digital twins for distributed clinical intelligence and integration, iterative genome analytics and precision medicine. 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 in large scale distributed systems and provided platforms for high performance medical data analytics. 

I have been investigating large-scale distributed data analytics systems that deal with hundreds of petabytes of LHC data in collaboration with CERN Geneva for the last 15 years. I closely work with world leading companies in cloud computing, telecommunication, space, earth observation, aerospace, rail and automobile to investigate digital twins and distributed learning systems for optimizing infrastructures and operations for accuracy, reliability, safety, and capacity. I am also actively collaborating with leading virtual reality (VR) providers to commoditise AI driven self-learning digital twins and enable real time rendering of data and models for high performance immersive visualizations. 

I have research & development interests in the following areas:

• Data Intensive Distributed Systems for High Performance Analytics
  
  
• Distributed, Scalable and Parallel Machine Learning Models 
  
  
• System Models for Self-Adapting and federated networks of Digital Twins
  
  
• Physics Informed Neural Networks for Trustworthy Digital Twins to emulate the behaviour of Cyber-Physical Systems 

The following is a list of selected research grants that have been supported by various funding agencies:

• Self-Learning Digital Twins for Sustainable Land Management (2023-2025, EPSRC)
• SLAIDER: Self-Learning AI-Based Digital Twins for Accelerating Clinical Care in Respiratory Emergency Admissions (2023-2025, EPSRC)
• Cardiograph Model of Human Heart for Personalized Treatments (2023-2024, BHF)
• Edge Deployed Self Adapting Network of Digital Twinning (2022/2027, EPSRC iCase and BT)
• Data Centre Digital Twins (2023-2024, CGI)
• METEOR: Manufacturing, Engineering, Technology and Earth Observation Research Centre (UKRPIF, 2020-2025) 
• COG-MHEAR: Towards cognitively-inspired, 5G-IoT enabled multi-modal hearing aids (2020-2025, EPSRC)
• Real time predictive maintenance of rolling stock using edge enhanced Machine Learning ((2020-23, Innovate UK)
• Leveraging satellite data for automated compliance checking, validation and risk assessment of large infrastructure projects as well as digital twins (2020-2022, Leicester Space Park/SPRINT)
• A Data Lake Blueprint for Space Data Integration and Access (2022, Sprint)

• AI Models for Vehicle Navigation, Recognition and In-service Intelligence (2020-2023 PI, Innovate UK)

• IoT Stream Analytics for rail efficiencies and intelligence in operations (2018-2020, Co-PI, D2N2)

• VR enabled Real Time Visualizations of Engineering Data (2018- 2021, PI, Innovate UK)

• Genome Analytics for Personalized Healthcare (2015-2020, PI, Hoffmann-La Roche Switzerland and Genentech USA
• Smart Logistics & Intelligent Warehousing for future supply chains (SLIMS) (2018-2020, PI, Innovate UK)

• Iterative Graph Analytics for Transport Network Incident and Impact Minimization (2018-2021, PI, Resonate)

• Blockchain Consistency and Scalability for Healthcare Traceability and compliance (2017-2019, PI, Roche)

• LHC Big Data Analytics for Particle Identification and Trajectory Analysis with CERN Geneva (2016-2020)

• Video Stream Analytics System for real time Surveillance and Object Classification (2015-2018, PI, RCUK/TSB)

• Transform Health (2010-2011, Task Leader, EC Framework 7 Programme)
• NeuGrid - Grid based knowledge discovery platform to enable neuroscientists for Alzheimer’s disease analysis (2008-2013, WP leader, EC FP7)

• Health-e-Child- Medical data integration platform and computational infrastructure for decision support system for European pediatricians (2006-2010, Task Leader, EC FP6)

• Data Intensive and Network Aware (DIANA) Grid Scheduler (2004-2007, EC FP5)

• JClarens- The Clarens Grid-Enabled Services Framework (2002-2004, Team Lead, DOE)

• MAGGIE - Measurement and Analysis of the Global Grid and Internet End-to-End Performance (2004-2005, Co-PI, NSF, USAID)

• Grid Enabled Analysis Environment (GAE) (2003-2005, Team Lead and Co-Principal Investigator, NSF and USAID)

Selected Papers

"Edge-Enhanced QoS Aware Compression Learning for Sustainable Data Stream Analytics", Maryleen Amaizu, Muhammad Ali, Ashiq Anjum, Lu Liu, Antonio Liotta, Omer Rana, IEEE Transactions on Sustainable Computing, 2023, doi: 10.1109/TSUSC.2023.3252039

"Cloud based scalable object recognition from video streams using orientation fusion and convolutional neural networks", Muhammad Usman Yaseen, Ashiq Anjum, Giancarlo Fortino, Antonio Liotta, Amir Hussain, Pattern Recognition, Volume 121, 2022, 108207, doi: 10.1016/j.patcog.2021.108207

"A Deep Learning based Explainable Control System for Reconfigurable Networks of Edge Devices," Priyanthi Dassanayake, Ashiq Anjum, Ali K. Bashir, Joe Bacon, Rabia Saleem and Warren Manning,  IEEE Transactions on Network Science and Engineering, Volume: 9, Issue: 1, 01  2022, doi: 10.1109/TNSE.2021.3083990.

"RES: Real-time Video Stream Analytics using Edge Enhanced Clouds", Muhammad Ali, Ashiq Anjum, Omer Rana, Ali Reza Zamani, Daniel Balouek-Thomert, Manish Parashar, IEEE Transactions on Cloud Computing PP(99):1-1, 2020, DOI:  10.1109/TCC.2020.2991748

"Deep Learning Hyper-parameter Optimisation for Video Analytics", M Usman Yaseen, Ashiq Anjum, Omer Rana, Nick Antonopoulos, IEEE Transactions on Systems, Man and Cybernetics: Systems, 2018, 10.1109/TSMC.2018.2840341

"Deadline Constrained Video Analysis via In-Transit Computational Environments", Ali Reza Zamani, Mengsong Zou, Javier Diaz-Montes, Ioan Petri, Omer Rana, Ashiq Anjum, Manish Parashar, Volume: PP, Issue: 99,, IEEE Transactions on Services Computing, 2017, DOI: 10.1109/TSC.2017.2653116

"An Inter-Cloud Meta-Scheduling (ICMS) Simulation Framework: Architecture and Evaluation", Stelios Sotiriadis, Nik Bessis, Ashiq Anjum, RajKumar Buyya,  IEEE Transactions on Services Computing, Volume: 99, ISSN: 1939-1374, February 2015,  DOI: 10.1109/TSC.2015.2399312 (Impact Factor: 1.985)

"Adapting Scientific Workflow Structures Using Multi-Objective Optimisation Strategies", Irfan Habib, Ashiq Anjum, Richard McClatchey, Omer Rana, ACM Transactions on Autonomous and Adaptive Systems (TAAS), ISSN: 1556-4665, Volume 8, Number 1, 2012, DOI=http://dx.doi.org/10.1145/2451248.2451252   (Impact Factor: 1.645)

"Video Stream Analysis in Clouds: An Object Detection and Classification Framework for High Performance Video Analytics", Ashiq Anjum, Tariq Abdullah, M Fahim Tariq, Yusuf Baltaci, Nikos Antonopoulos, IEEE Transactions on Cloud Computing, Volume: 7 , Issue: 4 , 2019, 1152 - 1167 DOI: 10.1109/TCC.2016.2517653

"Cloud based scalable object recognition from video streams using orientation fusion and convolutional neural networks", Muhammad Usman Yaseen, Ashiq Anjum, Giancarlo Fortino, Antonio Liotta, Amir Hussain, Pattern Recognition, Volume 121, 2021, 108207, doi: 10.1016/j.patcog.2021.108207

"A Deep Learning based Explainable Control System for Reconfigurable Networks of Edge Devices" Priyanthi Dassanayake, Ashiq Anjum, Ali K. Bashir, Joe Bacon, Rabia Saleem and Warren Manning,  IEEE Transactions on Network Science and Engineering, Doi: 10.1109/TNSE.2021.3083990.

Language model-based automatic prefix abbreviation expansion method for biomedical big data analysis", X Du, R Zhu, Y Li, Ashiq Anjum, Future Generation Computer Systems, Volume 98, September 2019, Pages 238-251, https://doi.org/10.1016/j.future.2019.01.016

"Blockchain Standards for Compliance and Trust", Ashiq Anjum, Manu Sporny, Alan Sill, IEEE Cloud Computing, vol. 4, no. , pp. 84-90, July/August 2017, doi:10.1109/MCC.2017.3791019

"Data Intensive and Network Aware (DIANA) Grid Scheduling", Richard McClatchey, Ashiq Anjum, Heinz Stockinger, Arshad Ali, Ian Willers, Michael Thomas, Journal of Grid Computing,  Springer Verlag, 5(1):43-64, 2007

Please get in touch with me if you're interested in a research and development project in Distributed Systems, Distributed and Edge AI , Self-Learning Digital Twins or in another area of my research interests. Broadly Speaking, I have the research and development interests in the following areas: 

• Data Intensive Distributed Systems

• Distributed Machine Learning 

• Edge and Embedded Artificial Intelligence

• Self-Learning  and Federated Networks of Digital Twins

• Blockchains and Trustworthy Distributed Systems

UK’s AI ‘twin’ will use big data to show the way to net zero

£13 million for 22 AI for health research projects

Multi-million pound investment in UK space industry agreed in Leicester

CGI partners with top UK academia to launch Sustainability Exploration Environmental Data Science (SEEDS) programme with the United Nations

https://www.ukauthority.com/articles/uk-universities-join-initiative-on-data-science-for-sustainability/

Fishbone Solutions to speed development of Readiness Assessment tool for remote monitoring of large infrastructure project

New Bloc Digital twin technologies to reduce time and cost of satellite development lifecycle

Fishbone Solutions to speed development of Readiness Assessment tool for remote monitoring of large infrastructure project

• Associate Editor, IEEE Transactions on Parallel and Distributed Systems (TPDS)

• Guest Editor Special Issue 2021 Concurrency and Computation: Practice and Experience

• Guest Editor Special Issue 2021 IEEE Access: Edge Intelligence

• Guest Editor Special Issue 2018 Future Generation Computer Systems

• Guest Editor Special Issue 2015 IEEE Transactions on Cloud Computing

• Guest Editor Special Issue 2013/2014 Journal of Cloud Computing: Advances Systems and Applications

• Guest Editor Special Issue 2012 Journal of Network and Systems Management

• IEEE Transactions on Parallel and Distributed Systems • IEEE Transactions on Cloud Computing

• IEEE Transactions on Systems Man and Cybernetics: Systems • IEEE Transactions on Mobile Computing

• IEEE Transactions on Big Data • IEEE Transactions on System and Circuits for Video Technology

• IEEE Transactions on Pattern Analysis and Machine Intelligence

• ACM Computing Surveys

• ACM Transactions on Autonomous and Adaptive Systems (ACM TAAS)

• IEEE Transactions on Information Technology in Biomedicine

• Science Foundation, Ireland Panellist

• EPSRC Grant Panelist 2023

• Pak Austria AI Centre Research Evaluator 2021

• European Commission Project Evaluator - 2016, 2017, 2018, 2019, 2023

• The Netherland Research Council Evaluator 2019, 2021, 2022

• Swiss Funding Council Project Evaluator - 2016

• MRC and EPSRC Grant evaluator- 2018 2019

• Cyprus Funding Council Grant Evaluator- 2017

• Canadian Funding Council Project Evaluator - 2017

• European Grid Infrastructure Champion (EGI)- 2012-2015

• Austrian Funding Council Evaluator- 2012

• Best paper award Bio Techno 2019

• Best Paper Award for Biotechno 2019 Grecce

• Runner up paper award in UCC 2014 London UK

• Outstanding University Researcher of the year 2013

• Best Paper award in GCC 2006 China.

• Recipient of the European Commission Scholarship in 2004

• Recipient of the CERN Fellowship Award in 2003

• Gold Medal in BSc 

• Programme Chair (AI and Machine Learning Track), The 22nd IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2022), Messina, Italy
• Organizing Chair, 15th International Conference on Utility and Cloud Computing (UCC) 2021, Leicester, UK
• Programme Chair, 14^th IEEE/ACM International conference on Utility and Cloud Computing (UCC 2019), Auckland, New Zealand
• General Chair, IEEE/ACM International conference on Fog and Edge Computing (FEC 2017), Madrid
• General Chair, 10^th IEEE/ACM International conference on Utility and Cloud Computing (UCC 2017), Austin, Texas, USA
• Programme Chair, 3^rd International Symposium on Big Data Computing, Applications and Technologies (BDCAT 2016), Shanghai, China
• General Chair, 8th International Conference on Utility and Cloud Computing (UCC) 2015, Cyprus
• Organizing Chair, 7th International Conference on Utility and Cloud Computing (UCC) 2014, London, UK
• Track Chair, 3^rd International Conference on Future Internet of Things and Cloud (FiCloud-2015) Vienna, Austria
• Track Chair, 12^th IEEE International Conference on Advanced and Trusted Computing, 2014, Beijing, China
• Organizing Chair, 19th annual International Conference on Conceptual Structures (ICCS 2011), UK
• Workshop Chair, Autonomic Clouds workshop (ITAAC 2013)
• Workshop Chair, Autonomic Clouds workshop (ITAAC 2012) (ITAAC 2012)
• Workshop Chair, Autonomic Clouds workshop (ITAAC 2011)
• Track Chair, The 2013 IEEE International Conference on Cyber, Physical and Social Computing
• Track Chair, The 16th International Conference on Network-Based Information Systems (NBiS 2013)
• Track Chair, The 11th IEEE/IFIP International Conferences on Embedded and Ubiquitous Computing (EUC 2013),
• Track Chair and Invited Speaker, FIT 2005,2006,2007, 2013, 2014, 205, 2016
• Track Chair and Invited Speaker, ICOSST 2006, 2007, 2022, 2012, 2013, 2014, 2015,2016
• Track Chair, 2012 3rd International Conference on Emerging Intelligent Data and Web Technologies (EIDWT-2012)
• Track Chair, 2015 7th International Conference on Intelligent Networking and Collaborative Systems (INCoS-2015)
• PC Member, Globecom 2018, 2019
• PC Member, IEEE ICIOT 2018
• PC Member, ScalCom 2018, 2019
• PC Member, BDCAT2017, 2018, 2019
• PC Member, Blockchain 2018, 2019
• PC Member, IEEE COMNETSAT 2018
• PC Member, ICCSE2018
• PC Member, CCGrid 2018, 2019
• PC Member, ICFEC 2018, 2019
• PC Member, CCUpdate2016
• PC Member, UCIOT 2017
• PC Member, FiUSE 2018
• PC Member, SCCTSA2017
• PC Member, SOSE 2016, 2017, 2018
• PC Member, Cloudcom 2017, 2018, 2019
• PC Member, FiCloud-2014,2015, 2016
• PC Member, IEEE Grid 2005, 2006, 2007, 2008
• PC Member, HealthGrid 2004,2005,2006, 2008, 2009, 2010
• PC Member, IEEE e-Science 2005,2006, 2007, 2012
• PC Member, 5th Conference on Intelligent Networking and Collaborative Systems (INCoS-2013)
• PC Member, 3rd International Conference on Cloud Computing and Services Science (CLOSER 2013), Germany
• PC Member, 4th Conference on Intelligent Networking and Collaborative Systems (INCoS-2012)
• PC Member, IEEE International Symposium on Cluster, Cloud, and Grid (CCGrid), 2008,2009, 2010, 2011,2012,2013,2014, 2016,2017
• PC Member, UK e-Science All Hands Meeting 2005, 2006, 2007, 2008
• PC Member, Sixth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC 2011)
• PC Member, Seventh International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (2012)
• PC Member, The 9th International Conferences on Embedded and Ubiquitous Computing (EUC 2011), Australia
• PC Member, The 2nd International Conference on Cloud Computing and Services Science, CLOSER 2012, Portugal
• PC Member, The 2nd International Conference on Emerging Intelligent Data and Web Technologies, 2012
• PC Member, 14th IEEE International Conference on High Performance Computing and Communication (2012), UK
• PC Member, The Fifth International Conference on Open-Source Systems and Technologies (ICOSST), 2011
• PC Member, DCABES 2004, China
• PC Member, ACM Middleware 2007
• PC Member, International Joint Conference on Autonomous Agents & Multi-Agent Systems (AAMAS 2009)
• PC Member, 9th International Workshop on State-of-the-Art in Scientific and Parallel Computing (PARA 2008)
• PC Member, Third IEEE International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2009)
• PC Member, The 12th IEEE International Conference on Computational Science and Engineering (CSE-09)
• PC Member, Software Engineering Research, Management & Applications (SERA 2010), Montreal, Canada
• PC Member, Euro-Par 2010, Naples, Italy
• PC Member, C* Conference on Computer Science & Software Engineering (C3S2E10), Montreal, CANADA, 2010
• PC Member, Medical Imaging on Grids: (MICCAI-Grid Workshop), 2008 (New York), 2009 (London)
• PC Member, International European Conference on Parallel and Distributed Computing (EURO-PAR 2012)
• PC Member, 5th Workshop on Workflows in Support of Large-Scale Science (WORKS 2010), New Orleans, USA
• PC Member, The 10th International Conferences on Embedded and Ubiquitous Computing (EUC 2012), Cyprus
• PC Member, Intelligent Cloud Computing, Theoretical Foundations and Applications (ICC 2014), Oman
• PC Member, Workshop on Cloud Computing Systems, Networks, and Applications (IEEE Globecom 2013)
• PC Member, International Workshop on Internet-based Virtual Computing Environment, OXFORD, UK iVCE 2O14
• PC Member, 4th International Conference on Cloud Computing and Services Science (CLOSER 2014), Barcelona