Amir Hussain

amir hussain

Prof Amir Hussain



Amir Hussain received his B.Eng (highest 1st Class Honours with distinction) and Ph.D degrees, from the University of Strathclyde, Glasgow, U.K., in 1992 and 1997, respectively.

Following postdoctoral and academic positions at the Universities of West of Scotland (EPSRC postdoctoral fellow: 1996-98), Dundee (Research Lecturer: 1998-2000) and Stirling (Lecturer: 2000-4; Senior Lecturer: 2004-8; Reader: 2008-12; Professor: 2012-18) respectively, he joined Edinburgh Napier University (in Scotland, UK) in 2018 as Professor and founding Head of the Data Science and Cyber Analytics (DSCA) Research Group (over 20 academics and research staff). He is also founding Head of the Cognitive Big Data and Cybersecurity (CogBiD) Research Lab.

He currently holds a number of Visiting Professorships, including at Xi’an Jiaotong-Liverpool University, Shanghai University and Anhui University, China, and Taibah University, Saudi Arabia.
He has previously held Visiting Professorships at Synthetic Intelligence Lab, Massachusetts Institute of Technology (MIT), USA and Oxford Computational Neuroscience, University of Oxford, UK.

He has been invited Advisor/Consultant for various international Governments and organisations, including (currently) at: Kuwait Institute for Scientific Research (KISR), Kuwait Government; and the National Centre of Big Data & Cloud Computing (NCBC), Higher Education Commission, Pakistan Government.


Prof Hussain's research and innovation interests are cross-
disciplinary and industry-led, aimed at developing and commercializing cognitive data science and AI technologies
to engineer the smart and secure healthcare and industrial systems of tomorrow.

He has (co)authored three international patents and over 400 publications, including 150+ international journal papers, 20 Books/monographs and 100+ Book chapters with (current Google h-index of 49, i10-index of 153, and 40+ Research Gate score).

He has led major cross-disciplinary research projects (including current grants totalling over GBP 5 Million), as Principal Investigator, funded by national and European research councils, local and international charities and industry, and supervised over 30 PhD students and 30+ postdoctoral researchers to-date. His high-profile PhD graduates include (amongst numerous others): Prof Erik Cambria (NTU, Singapore - the world’s most highly-cited AI researcher in sentiment analysis); Dr Soujanya Poria (2018 Presidential Young Investigator Award Winner, Singapore) and Prof Muaz Niazi (CIIT, Pakistan, & Chief-Editor: Springer journal of Complex Adaptive Systems Modeling)


• He is founding Editor-in-Chief of two leading international journals: Cognitive Computation (Springer Nature: SCI Impact Factor (IF): 4.29), and BMC Big Data Analytics (BioMed Central), and of the Springer Book Series on Socio-Affective Computing, and Cognitive Computation Trends.

• He has been appointed invited Associate Editor/Editorial Board member for a number of prestigious journals, including: the IEEE Transactions on Neural Networks and Learning Systems (IF: 11.7), IEEE Transactions on Systems, Man, and Cybernetics: Systems (IF: 7.35), Information Fusion (Elsevier, IF: 10.7), AI Review (Springer, IF: 5.1), IEEE Computational Intelligence Magazine (IF: 6.6), and the IEEE Transactions on Emerging Topics in Computational Intelligence.

• In 2017-18, he was ranked in independent surveys, published in leading international journals (including in Elsevier’s Information Processing & Management Journal), as one of the world’s top two most productive. AI researchers in sentiment analysis (since 2000). His works on biologically-inspired natural language processing (for sentiment & opinion mining) are ISI highly-cited papers.

• He was co-Leader of the Winning Team (jointly with Tsinghua University) at the 2nd World Intelligent Driving Challenge (WIDC), held in Tianjin, China, 15-17 May 2018. His team secured second-position in the 2019 WIDC Challenge. WIDC is an annual, internationally leading competition comprising contests in autonomous driving, intelligent assistance, information security and virtual testing. The Challenge attracts 90-100 teams from industry, universities and research institutes across the world, and is broadcast by over 100 international media outlets. His team won second

• His pioneering research on Sentic Computing for Big Data sentiment analytics and Natural Language Processing, was awarded the top “4* (Outstanding)” (industrial) Impact evaluation by UK Government’s Research Enhancement Framework (REF2014) exercise, and also the Best Performing Approach Award for 'Semantic Parsing' Task at the joint-industry & academic-led 'Concept-Level Sentiment Analysis Challenge’, organized as part of the 11th Extended Semantic Web Conference.

• Amongst other distinguished, international conference chairing roles (see examples below), he is General Chair for IEEE WCCI 2020 (the world's largest and top technical event in Computational Intelligence, comprising IJCNN, IEEE CEC and FUZZ-IEEE, attended by ~2,000 delegates:

• He is Vice-Chair of the Emergent Technologies Technical Committee of the IEEE Computational Intelligence Society, IEEE Chapter Chair of the UK and Ireland IEEE Industry Applications Society, and (founding) Vice-Chair for the IEEE CIS Task Force on Intelligence Systems for e-Health.


He is Founding/General/Organizing Chair for over 50 leading international conferences, including:

General Chair: IEEE World Congress on Computational Intelligence (WCCI’2020) – world’s largest, top biennial Conference on Computational Intelligence (comprising IJCNN, FUZZ-IEEE, IEEE-CEC, attended by ~2,000 delegates), Glasgow, Scotland, 19-25 July 2020 (

Founding General Chair: Annual IEEE Symposium on Computational Intelligence in Healthcare & e-Health (IEEE CICARE) - organized as part of the flagship IEEE SSCI (since 2013) – IEEE SSCI CICARE 2020 in Canberra, Australia, 1-4 Dec 2020

Founding General Chair: International Conference on Brain Inspired Cognitive Systems (BICS – since 2004: 1st-11th), BICS 2018 co-hosted with IEEE Brain Data Bank (BDB) Challenge - BICS’2020 in Hefei , China, 18-20 Dec 2020

General co-Chair: 3rd IEEE International Conference on Smart Data, Exeter, UK, 21-23 June 2017

Program Chair: 4th IEEE International Conference on Data Science and Systems (IEEE DSS’2018), Exeter, UK, 28-20 June 2018


Current funded Projects (examples - currently managing research grants totalling >£5million):

1. Lead/Chief Principal Investigator (PI) and Programme Director for new (~GBP 4 Million) UK Government's Engineering and Physical Sciences Research Council (EPSRC) programme grant (2020-2024): “Towards cognitively-inspired 5G-IoT enabled, multi-modal Hearing Aids (COG-MHEAR)” (EP/T021063/1). The proposal was ranked second in the country, under the EPSRC Transformative Healthcare Technologies 2050 Call. The cross-disciplinary programme includes co-Investigators (CIs) from: Edinburgh, Heriot-Watt, Glasgow and Manchester; and a strong User Group comprising ten industrial and clinical collaborators, and end-user engagement organisations (such as Deaf Scotland, Action on Hearing Loss, global hearing-aid manufacturers: Phonak & Nokia Bell Labs, providing ~GBP1 million match-funding). COG-MHEAR aims to be the world’s first multi-modal hearing-aid demonstrator (including real-time software and hardware prototypes), by radically exploiting and integrating the transformative potential of privacy-assuring and explainable AI, 5G, Internet of Things (IoT) and cybersecurity, coupled with flexible (skin-based) electronics. This will enable commercialization of future personalized, multi-modal hearing aids, with reduced end-user cognitive load/listening effort, seamlessly operating in the smart social and work spaces of 2050 and beyond. The adventurous research outputs will also be exploited to develop multimodally-enhanced, speech-enabled communication aids to support e.g. autistic people with speech disorders.

2. Lead CI/co-PI for new (~GBP 0.5 Million) EPSRC grant (2020-23) on “Natural Language Generation (NLG) for Low-resource Domains” (EP/T024917/1). The proposal was ranked first (out of 19), under the EPSRC Responsible NLP for Intelligent Interfaces Call. The project funds two postdoctoral RAs (one under my principal supervision), to develop personalized, privacy-assuring and empathetic AI (NLG) approaches that account for the emotional state of the end-user. These will enable emotion-sensitive personal assistants to enhance mental health and well-being.

3. Lead PI for new Scottish Government's Chief Scientist Office (CSO) funded research project (~GBP 0.14 Million), joint with the Usher Institute, University of Edinburgh, as part of the CSO Rapid Research in Covid -19 Programme Call (2020). The project is aimed at developing a novel Artificial Intelligence (AI) powered dashboard for COVID-19 related public sentiment and opinion mining in social media platforms.

4. Lead CI and co-Director of new H2020 EIT Digital and industry funded (~GBP 0.8 Million) Centre for Doctoral Training (CDT) on IoT Trust: Privacy, Blockchain and Cryptography (2020-24). The CDT is funding the training of 18 Doctoral students with a focus on development of privacy-preserving AI and Blockchain-enabled trustworthy citizen-centric systems. Key application areas include digital health and well-being, energy supply systems, e-Commerce, Fintech and public services.

Previous funded Projects (examples):

1. Lead PI for EPSRC grant (~GBP 0.5million), 2015-2019 (EP/M026981/1: Towards visually-driven speech enhancement for cognitively-inspired multi-modal hearing-aid devices: AV-COGHEAR). This pioneering project has been extensively covered in media, including the BBC ( and developed novel deep learning based speech enhancement algorithms for next-generation multi-modal hearing aids, listening devices and assistive technology. Project partners included: Psychology (CI: Prof. R. Watt, Stirling University), Speech & Hearing Research Group (CI: Prof J. Barker, Sheffield University), major hearing-aid manufacturers: Phonak AG/ Sonova (Dr P. Derleth) & UK MRC Institute of Hearing Research (Dr W. Whitmer).

2. Lead PI for UK EPSRC grant (~GBP 0.5million), 2011-2014 (EP/I009310/1: Dual Process Control Models in the Brain and Machines with Application to Autonomous Vehicle Control). This interdisciplinary project funded a post-doctoral RA to develop cognitive, multi-modal AI algorithms and decision support systems for complex autonomous systems, in the context of regular road driving and planetary rovers - in collaboration with CI: Prof K. Gurney (Psychology, Sheffield), SciSys Ltd & Industrial Systems Control Ltd.

3. Project CI for Chief Scientist Office (CSO) & industry co-funded (~GBP 0.5million) grant, 2015-18 (led by Dr C. Lees, Lead PI, Edinburgh) on “Prognostic Modeling of multi-level Big Data genetic & environmental factors in Crohn’s and Colitis”. The consortium comprised 12 UK Universities and Hospitals.

4. Lead PI for two UK EPSRC & industry co-funded grants (~GBP 200k, 2009-14), in partnership with Harvard Medical School (Prof. C. Macrae, Prof. W. Slack) and MIT Media Lab (Prof. N. Howard), USA. These projects funded development of novel AI predictive models and real-time decision support systems to enhance cardiovascular care and pre-operative risk assessment; and integrating machine learning and natural language processing (NLP) for patient opinion mining and semantic web applications

5. Lead PI for EPSRC funded Research Network: Novel Computation - Towards multiple-model based learning & optimized control paradigms for complex systems. This Network project funded a postdoctoral RA, and involved multiple academic and industrial partners. It was awarded an (Overall) Assessment of “Tending to Outstanding” by the EPSRC post-Grant Review Panel.


Prof. Hussain regularly publishes in prestigious top-ranked journals - examples include the IEEE Transactions on Neural Networks and Learning Systems; IEEE Transactions on Cybernetics; Information Fusion; Neural Networks and others.

(Up-to-date publications list is available on Google Scholar)

1. Adeel A, Gogate M, Hussain A: Contextual Deep Learning-based Audio-Visual Switching For Speech Enhancement in Real-World Environments, (Elsevier) Information Fusion, Vol.59:163-170 (2020) (SCI Impact Factor (IF): 10.7)

2. Ieracitano C, Adeel A, Morabito F.C, Hussain A, A novel statistical analysis and autoencoder driven intelligent intrusion detection approach, (Elsevier) Neurocomputing, 387:51-62 (2020) (IF: 4.1)

3. Xiong F, Sun B, Yang X, Qiao H, Huang K, Hussain A, Liu Z, "Guided Policy Search for Sequential Multitask Learning," in IEEE Transactions on Systems, Man, and Cybernetics: Systems, 49(1): 216-226 (2019) (IF: 7.35)

4. Alsarhan A.A, Kilani Y, Al-Dubai A.Y, Zomaya A.Y., Hussain A: Novel Fuzzy and Game Theory Based Clustering and Decision Making for VANETs. IEEE Transactions on Vehicular Technology 69(2): 1568-1581 (2020) (IF: 5.3)

5. Zhang L, Liu Z, Zhang S, Yang X, Qiao H, Huang K, Hussain A: Cross-modality interactive attention network for multispectral pedestrian detection, (Elsevier) Information Fusion, 50: 20-29 (2019) (IF: 10.7)

6. Ieracitano C, Mammone N, Hussain A, Morabito F.C, A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia, (Elsevier) Neural Networks, Vol. 123:176-190 (2020) (IF: 7.2)

7. Mahmud, M; Kaiser, M. S; Hussain, A: Vassanelli, S, Applications of Deep Learning and Reinforcement Learning to Biological Data, IEEE Transactions in Neural Networks and Learning Systems, 29(6):2063-2079 (2018) (IF: 11.6)

8. Yang X, Huang K, Zhang R, Hussain A: Learning Latent Features with Infinite Non-negative Binary Matrix Tri-factorization, IEEE Transactions on Emerging Topics in Computational Intelligence, 2(5): 450-463, (2018)

9. Hussain A, Cambria C: Semi-Supervised Learning for Big Social Data Analysis, (Elsevier) Neurocomputing, 275: 1662-1673 (2018) (IF: 4.1)

10. Malik Z.K., Hussain A, Wu J: Multi-Layered Echo State Machine: A novel Architecture and Algorithm, IEEE Transactions on Cybernetics, 47(4):946 - 959 (2017) (IF: 10.4)


296 results

Cross-modality interactive attention network for multispectral pedestrian detection

Journal Article
Zhang, L., Liu, Z., Zhang, S., Yang, X., Qiao, H., Huang, K., & Hussain, A. (2019)
Cross-modality interactive attention network for multispectral pedestrian detection. Information Fusion, 50, 20-29.
Multispectral pedestrian detection is an emerging solution with great promise in many around-the-clock applications, such as automotive driving and security surveillance. To e...

Weakly Supervised Segmentation of SAR Imagery Using Superpixel and Hierarchically Adversarial CRF

Journal Article
Ma, F., Gao, F., Sun, J., Zhou, H., & Hussain, A. (2019)
Weakly Supervised Segmentation of SAR Imagery Using Superpixel and Hierarchically Adversarial CRF. Remote Sensing,
Synthetic aperture radar (SAR) image segmentation aims at generating homogeneous regions from a pixel-based image and is the basis of image interpretation. However, most of th...

A comparative study of Persian sentiment analysis based on different feature combinations

Conference Proceeding
Dashtipour, K., Gogate, M., Adeel, A., Hussain, A., Alqarafi, A., & Durrani, T. (2019)
A comparative study of Persian sentiment analysis based on different feature combinations.
In recent years, the use of internet and correspondingly the number of online reviews, comments and opinions have increased significantly. It is indeed very difficult for huma...

Guided Policy Search for Sequential Multitask Learning

Journal Article
Xiong, F., Sun, B., Yang, X., Qiao, H., Huang, K., Hussain, A., & Liu, Z. (2019)
Guided Policy Search for Sequential Multitask Learning. IEEE Transactions on Systems Man and Cybernetics: Systems, 49(1), 216-226.
Policy search in reinforcement learning (RL) is a practical approach to interact directly with environments in parameter spaces, that often deal with dilemmas of local optima ...

Toward's Arabic multi-modal sentiment analysis

Conference Proceeding
Alqarafi, A., Adeel, A., Gogate, M., Dashitpour, K., Hussain, A., & Durrani, T. (2019)
Toward's Arabic multi-modal sentiment analysis.
In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook...

A Novel Multi-Input Bidirectional LSTM and HMM Based Approach for Target Recognition from Multi-Domain Radar Range Profiles

Journal Article
Gao, F., Huang, T., Wang, J., Sun, J., Hussain, A., & Zhou, H. (2019)
A Novel Multi-Input Bidirectional LSTM and HMM Based Approach for Target Recognition from Multi-Domain Radar Range Profiles. Electronics, 8(5),
Radars, as active detection sensors, are known to play an important role in various intelligent devices. Target recognition based on high-resolution range profile (HRRP) is an...

A comparison of two methods of using a serious game for teaching marine ecology in a university setting

Journal Article
Ameerbakhsh, O., Maharaj, S., Hussain, A., & McAdam, B. (2019)
A comparison of two methods of using a serious game for teaching marine ecology in a university setting. International Journal of Human-Computer Studies, 127, 181-189.
There is increasing interest in the use of serious games in STEM education. Interactive simulations and serious games can be used by students to explore systems where it would...

Speech Enhancement Based on Adaptive Noise Cancellation and Particle Swarm Optimization

Journal Article
Taha, T. M., Wajid, S. K., & Hussain, A. (2019)
Speech Enhancement Based on Adaptive Noise Cancellation and Particle Swarm Optimization. Journal of Computer Science, 15(5), 691-701.
Speech enhancement is used in almost all modern communication systems. This is due to the quality of speech being degraded by environmental interference factors, such as: Acou...

Clinical Decision Support Systems: A Visual Survey

Journal Article
Farooq, K., Khan, B. S., Niazi, M. A., Leslie, S. J., & Hussain, A. (2018)
Clinical Decision Support Systems: A Visual Survey. Informatica, 42(4), 485–505.
Clinical Decision Support Systems (CDSS) form an important area of research. In spite of its importance, it is difficult for researchers to evaluate the domain primarily becau...

Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach

Journal Article
Ullah, A., Li, J., & Hussain, A. (2018)
Towards workload-aware cloud resource provisioning using a multi-controller fuzzy switching approach. International Journal of High Performance Computing and Networking, 12(1), 13-25.
Elasticity enables cloud customers to enrich their applications to dynamically adjust underlying cloud resources. Over the past, a plethora of techniques have been introduced ...

Current Post Grad projects