Nadia Kanwal

Biography

Biography

Dr Kanwal received her master's and Ph.D. degrees in Computer Sciences from the University of Essex, UK in 2013. She has also received a prestigious Marie Skłodowska-Curie Research fellowship (for 3-years) to do an industry led project related to secure and privacy protected CCTV video storage and retrieval as a principal investigator. Her research interests are in the field of Computer Vision and Machine Learning. She is actively working on applying machine learning to develop cutting-edge solutions for health, security, and vision applications. Her publications on multimedia data security, visual privacy, low-level image features, virtual reality, EEG/ECG signal analysis, and pupillometry have been very well supported by the research community. She is an active reviewer of good-standing journals and conferences. She is a Senior Member of IEEE since 2019. She has also been awarded a senior fellow status of Advance HE, UK in 2022.

Research and scholarship

Research and scholarship

Research grants

• Co-Investigator: MDUK entitled “Pilot study: Using deep neural networks to establish a novel non-invasive and sensitive motor skill assessment tool for pre-clinical mouse models of muscle-wasting conditions.” November 2022 (Grant ref 22GRO-PG12-0560) (Funding: £29,548)
• Principal Investigator: Commercialisation Fund Programme 2020, Commercial Case Feasibility Support Grant by Enterprise Ireland, Title: “Market Feasibility Study for A Secured Video Storage System with Privacy Protection Feature” (Funding: €15000)
• Principal Investigator: Research grant from the President Doctoral Scholarship (PDS) program, Technological University of the Shannon Athlone, Ireland to supervise a PhD research project (2020-2024) Project title: Federated AI Learning to Understand Human Emotions Via Smart Clothing and Edge Analytics under my supervision. (Funding: €77,000)
• Principal Investigator: Research grant from the President Doctoral Scholarship (PDS) program, Technological University of the Shannon Athlone, Ireland to supervise a PhD research student (2020- 2024) Project title: Activity Recognition in Encrypted Videos using Federated Learning: A framework for Privacy Protected Big Data Analysis (Funding: €77,000)
• Principal Investigator: Marie Curie Career-Fit (International fellowship- 2018) to work on a research project with the funding support by Enterprise Ireland and H2020 European Project (2019-2022). Project title: Distributed Deep Learning System for Privacy Preserving Video Retrieval in Large Scale Video Sensing (Funding: €256,200)

Research themes

• Data privacy and security in
  • surveillance systems
  • healthcare data
  • sensors for health-related data collection
• Human-Computer Interaction
• Bioinformatics and computational biology

Research interests

• Federated Learning
• Distributed Machine/Deep Learning
• Computer Vision
• Visual Data Security
• Visual Data Authentication
• Emotions classification from physiological signals
• Encryption and Steganography
• Ethical AI

Teaching

Teaching

• CSC-10050 Requirements, Evaluation, and Professionalism for Data Scientists
• CSC-20055 Data Structures and Algorithms
• CSC-30051 Artificial Intelligence for Data Scientists

Publications

Publications

Selected publications

• Zaidi, S. S. A., Ansari, M. S., Aslam, A., Kanwal, N., Asghar, M., & Lee, B. (2022). A survey of modern deep learning based object detection models. Digital Signal Processing, 126 (1) pages 103514.
• Mitchell, J., Kanwal, N., Quincey, E., (2022, July) Using physiological signals to measure the Quality-of-Experience of Health Care Professionals when interacting with a clinical guideline mobile app, In 2022 35th International BCS Human Computer Interaction Conference, UK
• Kanwal, N., Asghar, M. N., Ansari, M. S., Fleury, M., Lee, B., Herbst, M., & Qiao, Y. (2020). Preserving chain-of-evidence in surveillance videos for authentication and trust-enabled sharing. IEEE Access, 8, 153413-153424
• Rafique, S., Kanwal, N., Karamat, I., Asghar, M. N., & Fleury, M. (2020). Towards estimation of emotions from eye pupillometry with low-cost devices. IEEE Access, 9, 5354-5370.
• Zahra, A., Kanwal, N., ur Rehman, N., Ehsan, S., & McDonald-Maier, K. D. (2017). Seizure detection from EEG signals using multivariate empirical mode decomposition. Computers in biology and medicine, 88, 132-141.

Journal articles:

• Gillani, S. M., Asghar, M. N., Shifa, A., Abdullah, S., Kanwal, N., & Fleury, M. (2022). VQProtect: Lightweight Visual Quality Protection for Error-Prone Selectively Encrypted Video Streaming. Entropy, 24(6), 755.
• Xiao, S., Ye, Y., Kanwal, N., Newe, T., & Lee, B. (2022). SoK: context and risk aware access control for zero trust systems. Security and Communication Networks, vol (2022), pages 20.
• Shah, R. A., Asghar, M. N., Abdullah, S., Kanwal, N., & Fleury, M. (2020). SLEPX: An efficient lightweight cipher for visual protection of scalable HEVC extension. IEEE Access, 8, 187784-187807.
• Shifa, A., Asghar, M. N., Fleury, M., Kanwal, N., Ansari, M. S., Lee, B., Herbst, M., & Qiao, Y. (2020). MuLViS: Multi-level encryption based security system for surveillance videos. IEEE Access, 8, 177131-177155.
• Tanseer, I., Kanwal, N., Asghar, M. N., Iqbal, A., Tanseer, F., & Fleury, M. (2020). Real-time, content-based communication load reduction in the internet of multimedia things. Applied Sciences, 10 (3), 1152.
• Asghar, M. N., Kanwal, N., Lee, B., Fleury, M., Herbst, M., & Qiao, Y. (2019). Visual surveillance within the EU general data protection regulation: A technology perspective. IEEE Access, 7, 111709-111726.
• Malik, S., Kanwal, N., Asghar, M. N., Sadiq, M. A. A., Karamat, I., & Fleury, M. (2019). Data driven approach for eye disease classification with machine learning. Applied Sciences, 9(14), 2789.
• Anjum, F., Kanwal, N., Clark, A. F., & Bostanci, E. (2018). Statistical evaluation of corner detectors: does the statistical test have an effect?. IET Computer Vision, 12(7), 1018-1030.
• Bostanci, E., Bostanci, B., Kanwal, N., & Clark, A. F. (2018). Sensor fusion of camera, GPS and IMU using fuzzy adaptive multiple motion models. Soft Computing, 22(8), 2619-2632.
• Kanwal, N., Bostanci, E., & Clark, A. F. (2016). Evaluation method, dataset size or dataset content: how to evaluate algorithms for image matching?. Journal of Mathematical Imaging and Vision, 55(3), 378-400.
• Tahir, M., Kanwal, N., & Anjum, F. (2016). FAB: fast angular binary descriptor for matching corner points in video imagery. Journal of Robotics, vol (2016), pp 1-11.
• Kanwal, N., Bostanci, E., Currie, K., & Clark, A. F. (2015). A navigation system for the visually impaired: a fusion of vision and depth sensor. Applied bionics and biomechanics, vol (2015), pp 1-16.
• Bostanci, E., Kanwal, N., & Clark, A. F. (2015). Augmented reality applications for cultural heritage using Kinect. Human-centric Computing and Information Sciences, 5(1), pp 1-18.
• Kanwal, N., Bostanci, E., & Clark, A. F. (2014). Matching corners using the informative arc. IET Computer Vision, 8(3), 245-253.
• Bostanci, E., Kanwal, N., & Clark, A. F. (2013). Spatial statistics of image features for performance comparison. IEEE Transactions on Image Processing, 23(1), 153-162.
• Bostanci, E., Kanwal, N., Ehsan, S., & Clark, A. F. (2013). User tracking methods for augmented reality. International Journal of Computer Theory and Engineering, 5(1), pp 93-98.
• McAusland, L., Davey, P. A., Kanwal, N., Baker, N. R., & Lawson, T. (2013). A novel system for spatial and temporal imaging of intrinsic plant water use efficiency. Journal of experimental botany, 64(16), 4993-5007.
• Kanwal, N., Bostanci, E., & Clark, A. F. (2012). Describing corners using angle, mean intensity and entropy of informative arcs. Electronics letters, 48(4), 209-210.
• Ehsan, S., Kanwal, N., Clark, A. F., & McDonald-Maier, K. D. (2011). An algorithm for the contextual adaption of surf octave selection with good matching performance: Best octaves. IEEE transactions on image processing, 21(1), 297-304.
• Ehsan, S., Kanwal, N., Clark, A. F., & McDonald-Maier, K. D. (2010). Improved repeatability measures for evaluating performance of feature detectors. Electronics letters, 46(14), pp 998-1000

Chapters within books

• Aydın, M., Bostancı, E., Güzel, M. S., & Kanwal, N. (2020). Multiagent Systems for 3D Reconstruction Applications. Multi Agent Systems: Strategies and Applications, pp. 25-44, IntechOpen
• Unal, M., Bostanci, E., Guzel, M. S., Unal, F. Z., & Kanwal, N. (2018, November). Evolutionary motion model transitions for tracking unmanned air vehicles. In International Conference on Computational Vision and Bio Inspired Computing (pp. 1193-1200). Springer, Cham.
• Bostanci, E. Kanwal, N., Clark, A. F., (2015) “Augmented Reality for Cultural Heritage Using Vision-Based User Tracking: A Fusion Approach”, Augmented Reality: Developments, Technologies and Applications, (pp. 109-158) Nova Publishers
• Kanwal, N., Ehsan, S., & Clark, A. F. (2011, August). Are performance differences of interest operators statistically significant? Computer Analysis of Images and Patterns (pp. 429-436). Springer, Berlin, Heidelberg.
• Ehsan, S., Kanwal, N., Clark, A. F., & McDonald-Maier, K. D., (2011) “Measuring the coverage of interest point detectors”, Image Analysis and Recognition (pp. 253-261). Springer Berlin Heidelberg

Refereed publications

• Hussain, B. Z., Andleeb, I., Ansari, M. S., Joshi, A. M., & Kanwal, N. (2022, July). Wasserstein GAN based Chest X-Ray Dataset Augmentation for Deep Learning Models: COVID-19 Detection Use-Case. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 2058-2061)
• Yousuf, M. J., Kanwal, N., Ansari, M. S., Asghar, M., & Lee, B. (2022, July). Deep Learning based Human Detection in Privacy-Preserved Surveillance Videos. In 2022 35th International BCS Human Computer Interaction Conference, UK
• Mitchell, J., Kanwal, N., Quincey, E., (2022, July) Using physiological signals to measure the Quality-of-Experience of Health Care Professionals when interacting with a clinical guideline mobile app, In 2022 35th International BCS Human Computer Interaction Conference, UK
• Pidgeon, M., Kanwal, N., Murray, N., Asghar, M., (2022, July) End-to-End Emotion Recognition using Peripheral Physiological Signals, In 2022 35th International BCS Human Computer Interaction Conference, UK
• Aribilola, I., Asghar, M. N., Kanwal, N., Ansari, M. S., & Lee, B. (2022, June). AFOM: Advanced flow of motion detection algorithm for dynamic camera videos. In 2022 33rd Irish Signals and Systems Conference (ISSC) (pp. 1-6). IEEE.
• Trzcinski, K., Asghar, M. N., Phelan, A., Servat, A., Kanwal, N., Ansari, M. S., & Fallon, E. (2022). Utility of Deep Learning Model to Prioritize the A&E Patients Admission Criteria. In Proceedings of International Conference on Information Technology and Applications (pp. 99-108). Springer, Singapore.
• Tahir, M., Asghar, M. N., Kanwal, N., Lee, B., & Qiao, Y. (2021, December). Joint Crypto-Blockchain Scheme for Trust-Enabled CCTV Videos Sharing. In 2021 IEEE International Conference on Blockchain (Blockchain) (pp. 1-6). IEEE.
• Hussain, B. Z., Andleeb, I., Ansari, M. S., & Kanwal, N. (2021, November). Lightweight Deep Learning Model for Automated COVID-19 Diagnosis from CXR Images. In 2021 IEEE International Conference on Computing (ICOCO) (pp. 218-223). IEEE.
• Rafique, S., Kanwal, N., Ansari, M. S., Asghar, M., & Akhtar, Z. (2021, December). Deep Learning based Emotion Classification with Temporal Pupillometry Sequences. In 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) (pp. 1-6). IEEE.
• Kannikka, E., & Kanwal, N. (2021, December). Control of Overload Safety in Wind Turbines Through Blade Pitch Control Implementing Artificial Intelligence. In 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) (pp. 1-6). IEEE.
• Mohammed, Z., Asghar, M., & Kanwal, N. (2021, December). Analyzing the impact of COVID-19 on flight cancellation using machine learning and deep learning algorithms for a highly unbalanced dataset. In 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET) (pp. 1-6). IEEE.
• Abbas, M. N., Ansari, M. S., Asghar, M. N., Kanwal, N., O'Neill, T., & Lee, B. (2021, January). Lightweight deep learning model for detection of copy-move image forgery with post-processed attacks. In 2021 IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI) (pp. 000125-000130). IEEE.
• Kanwal, N., Asghar, M. N., Ansari, M. S., Lee, B., Fleury, M., Herbst, M., & Qiao, Y. (2020, August). Chain-of-Evidence in Secured Surveillance Videos using Steganography and Hashing. In 2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (pp. 257-264). IEEE.
• Cetinkaya, O. T., Sandal, S., Bostancı, E., Güzel, M. S., Osmanoğlu, M., & Kanwal, N. (2019, September). A Fuzzy Rule Based Visual Human Tracking System for Drones. In 2019 4th International Conference on Computer Science and Engineering (UBMK) (pp. 1-6). IEEE. Contribution 30%
• Unal, M., Bostanci, E., Guzel, M. S., Unal, F. Z., & Kanwal, N. (2018, November). Evolutionary motion model transitions for tracking unmanned air vehicles. In International Conference On Computational Vision and Bio Inspired Computing (pp. 1193-1200). Springer, Cham.
• Ar, Y., Ünal, M., Sert, S. Y., Bostanci, E., Kanwal, N., & Güzel, M. S. (2018, October). Evolutionary fuzzy adaptive motion models for user tracking in augmented reality applications. In 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-6). IEEE.
• Unal, M., Bostanci, E., Sertalp, E., Guzel, M. S., & Kanwal, N. (2018, October). Geo-location based augmented reality application for cultural heritage using drones. In 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) (pp. 1-4). IEEE.
• Bostanci, E., Kanwal, N., & Clark, A. F. (2013, April). Kinect-derived augmentation of the real world for cultural heritage. In 2013 UKSim 15th International Conference on Computer Modelling and Simulation (pp. 117-122). IEEE.
• Kanwal, N., Bostanci, E., and Clark, A. F, (2013) “Kinect Aided Navigation System for Visually Impaired People,” In 2013 Proceedings of the Workshop on Recognition and Action for Scene Understanding (REACTS 2013), York, UK, (pp. 201-211)
• Bostanci, E., Kanwal, N., & Clark, A. F. (2012, September). Extracting planar features from Kinect sensor. In 2012 4th Computer Science and Electronic Engineering Conference (CEEC) (pp. 111-116). IEEE.
• Bostanci, E., Clark, A. F., & Kanwal, N. (2012, July). Vision-based user tracking for outdoor augmented reality. In 2012 IEEE symposium on computers and communications (ISCC) (pp. 566-568). IEEE.
• Bostanci, E., Kanwal, N., & Clark, A. F. (2012, April). Feature coverage for better homography estimation: an application to image stitching. In 2012 19th International Conference on Systems, Signals and Image Processing (IWSSIP) (pp. 448-451). IEEE.
• Kanwal, N., Ehsan, S., Bostanci, E., & Clark, A. F. (2011, September). Evaluating the angular sensitivity of corner detectors. In 2011 IEEE International Conference on Virtual Environments, Human-Computer Interfaces and Measurement Systems Proceedings (pp. 1-4). IEEE.
• Ehsan, S., Clark, A. F., Cheung, W. M., Bais, A. M., Menzat, B. I., Kanwal, N., & McDonald-Maier, K. D. (2011, September). Memory-Efficient Design Strategy for a Parallel Embedded Integral Image Computation Engine. In 2011 Irish Machine Vision and Image Processing Conference (pp. 107-108). IEEE.
• Contribution 30%
• Kanwal, N., Ehsan, S., Bostanci, E., & Clark, A. F. (2011, August). A statistical approach for comparing the performances of corner detectors In Proceedings of 2011 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (pp. 321-326). IEEE.
• Ehsan, S., Kanwal, N., Bostanci, E., Clark, A., & McDonald-Maier, K. (2010). Analysis of interest point distribution in SURF octaves. In 3rd International Conference on Machine Vision, (pp 411-415)
• Bostanci, E., Kanwal, N., Ehsan, S., & Clark, A. F. (2010). Tracking methods for augmented reality. In The 3rd international Conference on Machine Vision (pp. 425-429).
• Fahiem, M. A., & Kanwal, N. (2007, November). A novel CSG Approach for 3D Reconstruction of Helix Using Spiral Sweeps. In 7th WSEAS International Conference on applied computer science, Venice, Italy, (pp. 168-172)