dr-nadeem-anjum

Dr. Nadeem Anjum

Professor/HoD Software Engineering
PROFILE SUMMARY

Dr. Nadeem Anjum has over 20 years of combined industrial and academic experience. He holds a PhD and an MS degree from Queen Mary University of London, UK, having received a fully funded scholarship for his doctoral studies. Currently serving as the Professor and Head of the Department of Software Engineering at Capital University of Science and Technology (C.U.S.T) in Islamabad, Pakistan, he is a Senior Member of the IEEE. Dr. Anjum actively contributes as a technical reviewer for esteemed research journals and engages in nationally and internationally funded projects. He received the Best Paper Award at the IEEE Intl. Conf. on Advanced Video and Signal-Based Surveillance (AVSS) in 2009. His research interests encompass artificial intelligence, eHealth, behavior analysis, and big data analytics.

QUALIFICATION
PhD Computer Science Queen Mary University of London, London 2010
MS Computer Science Queen Mary University of London, London 2006
MSc Computer Science International Islamic University, Islamabad-PK 2001
TEACHING EXPERIENCE
Associate Professor Capital University of Science and Technology (CUST), Islamabad Since – 2021
Assistant Professor Capital University of Science and Technology (CUST), Islamabad 2019 – 2021
Assistant Professor University of Engineering and Technology, Taxila-Pakistan 2013 – 2016
Assistant Professor Riphah International University, Islamabad-Pakistan 2010 – 2013
INDUSTRIAL EXPERIENCE
Founder Director Stémma International (PVT) Limited 2016 – 2019
Assistant Manager Advanced Engineering Research Organization-Pakistan 2001 – 2005
MANAGEMENT EXPERIENCE
HoD Capital University of Science and Technology, Islamabad Since – 2021
RESEARCH AREAS / INTERESTS
1. Computer Vision
2. Deep Learning for Human Activity Recognition
3. Machine Learning
4. Pattern Recognition
RESEARCH SUPERVISION
1. PhD Robust Human Behaviour Anticipation in Multiple Camera Environments
2. PhD A Multi-Feature Hybrid Object Tracking Algorithm
3. PhD Placement of drones for efficient communication in disaster regions
4. PhD FLAG-PDFe: Geometric and Layout Aware Methods to Extract Metadata from Digital Scientific Research Publications
5. MS Detection of Malicious Consumer Interest Packet While Mitigating Content Poisoning Attack with Name-Key Based Forwarding and Multipath Forwarding Based Inband Probe
6. MS Salient Object Detection with Deep learning
7. MS Multi-feature Trajectory Analysis for abnormal activity recognition
8. MS ECG signal analysis to identify sudden cardiac arrest
9. MS Trajectory clustering for video analysis
10. MS Anticipation of human interaction using machine learning techniques
11. MS Performance analysis of machine learning algorithms
12. MS Moving object tracking using robust Kalman filter
JOURNAL PUBLICATIONS
S. Ahmed, S. Irfan, N. Kiran, N. Masood, N. Anjum, N. Ramzan. Remote health monitoring systems for elderly people: A survey. Physical Sensors, 2023.
W. Raja and N. Anjum, Generic Features Selection for Structure Classification of Diverse Styled Scholarly Articles”, Springer Multimedia Tools and Applications (Accepted).
Waqas Raja and Nadeem Anjum. A Hybrid Strategy to Extract Metadata from Scholarly Articles by Utilising Support Vector Machines and Heuristics. Springer Scientrometrics (Accepted)
S. Zaheer, N. Anjum, S. Hussain, A. D. Algarni, J. Iqbal, S. Bourouis, and S. S. Ullah. 2023. “A Multi-Parameter Forecasting for Stock Time Series Data Using LSTM and Deep Learning Model” Mathematics 11, no. 3: 590. https://doi.org/10.3390/math11030590.
AS Khattak, N. Anjum, N. Khan, MR Mufti, N. Ramzan. “AMF-MSPF: A Retrospective Analysis with Online Object Tracking Algorithms”. Displays. 2022 Dec 7:102354.
S. Irfan, N. Anjum, T. Althobaiti, A. A. Alotaibi, A. B. Siddiqui, and N. Ramzan, “Heartbeat Classification and Arrhythmia Detection Using a Multi-Model Deep-Learning Technique,” Sensors, vol. 22, no. 15, p. 5606, 2022,
A. Jabbar, Q. H. Abbasi, N. Anjum, T. Kalsoom, N. Ramzan, S. Ahmed, P. M. Rafiul Shan, O. P. Falade, M. A. Imran, and M. Ur Rehman, “Millimeter-Wave Smart Antenna Solutions for URLLC in Industry 4.0 and Beyond,” Sensors, vol. 22, no. 7, p. 2688, 2022
Jamshed, Muhammad Ali, Charalambos Theodorou, Tahera Kalsoom, Nadeem Anjum, Qammer H. Abbasi, and Masood Ur-Rehman. “Intelligent computing-based forecasting of deforestation using fire alerts: a deep learning approach.” Physical Communication (2022).
Saad Irfan, Nadeem Anjum, Turke Althobaiti, Abdullah Alhumaidi Alotaibi, Abdul Basit Siddiqui, and Naeem Ramzan. 2022. “Heartbeat Classification and Arrhythmia Detection Using a Multi-Model Deep-Learning Technique” Sensors 22, no. 15: 5606. https://doi.org/10.3390/s22155606
Jabbar, Abdul, Qammer H. Abbasi, Nadeem Anjum, Tahera Kalsoom, Naeem Ramzan, Shehzad Ahmed, Piyya M. Rafi-ul-Shan, Oluyemi P. Falade, Muhammad A. Imran, and Masood Ur Rehman. 2022. “Millimeter-Wave Smart Antenna Solutions for URLLC in Industry 4.0 and Beyond” Sensors 22, no. 7: 2688. https://doi.org/10.3390/s22072688.
S. Irfan, N. Anjum, N. Masood, A. S. Khattak, and N. Ramzan. 2021. “A Novel Hybrid Deep Learning Model for Human Activity Recognition Based on Transitional Activities” Sensors 21, no. 24: 8227.
A. Lakhan, Q. Mastoi , M. A. Dootio, F. Alqahtani, I.R. Alzahrani, F. Baothman, M. S. Khokar, S. Y. Shah, S. A. Shah, N. Anjum, and Q. H. Abbasi, Hybrid Workload Enabled and Secure Healthcare Monitoring Sensing System in Distributed Fog-Cloud Network, Electronics, August 2021.
U. Saeed, S.Y. Shah, A. Zahid, N. Anjum, J. Ahmad, M. A. Imran, Q. H. Abbasi and S. A. Shaha, Wireless Channel Modelling for Identifying Six Types of Respiratory Patterns with SDR Sensing and Deep Multilayer Perceptron, IEEE Sensors, 2021.
R Gulbaz, A. B. Siddiqui, N. Anjum, A. A. Alotaibi, T. Althobaiti, and N. Ramzan, Balancer Genetic Algorithm – A Novel Task Scheduling Optimization Approach in Cloud Computing, Appl. Sci. July, 2021.
A. M. Qureshi; N. Anjum; N.B.R Rao; M. Nizami; A. Qayyum, Detection of Malicious Consumer Interest Packet with Dynamic Threshold Values, PeerJ Computer Science, (2021).
W. Sultan; N. Anjum; M. Stansfield; N. Ramzan, Hybrid Local and Global Deep-Learning Architecture for Salient-Object Detection. Appl. Sci. 2020, 10, 8754.
S. Bibi, N. Anjum, T. Amjad, G. McRobbie, and N. Ramzan. Human Interaction Anticipation by Combining Deep Features and Transformed Optical Flow Components. IEEE Access, 2020.
A. Khattak, G. Raja, N. Anjum. Adaptive Framework for Multi-Feature Hybrid Object Tracking. Applied Sciences, 8(11), p.2294. 2018
S. Bibi, N. Anjum, M. Sher, Automated Multi- Feature Human Interaction Recognition in Complex Outdoor Environments, Elsevier, Computers in Industry (Accepted,2018)
M J. Mirza, and N. Anjum. “Association of moving objects across visual sensor networks.” Journal of Multimedia 7.1 2012
N. Anjum and A. Cavallaro. Automated localization of a camera network. IEEE Intelligent Systems, 2012
N. Anjum. Camera localization in distributed networks using trajectory estimation, Journal of Electrical and Computer Engineering, 2011
N. Anjum and A. Cavallaro. Multi-feature object trajectory clustering for video analysis. IEEE Trans. on Circuits and Systems for Video Technology, 18(11):1555-1564, Nov. 2008
N. Anjum and A. Cavallaro. Trajectory clustering for scene context learning and outlier detection. Springer-Verlag series on Studies in Computational Intelligence, 2010
N. Anjum and A. Cavallaro. Multi-camera calibration and global trajectory fusion. Intelligent Video Surveillance Systems and Technology, 2010

 

CONFERENCE PUBLICATIONS
A. M. Qureshi and N. Anjum. Detection of Malicious Consumer Interest Packet While Mitigating Content Poisoning Attack with Name-Key Based Forwarding and Multipath Forwarding Based Inband Probe. International Conference on UK-China Emerging Technologies (UCET), 2020.
Khattak, Ahmad S., Gulistan Raja, N. Anjum, and Muhammad Qasim. “Integration of mean-shift and particle filter: a survey.” In 2014 12th International Conference on Frontiers of Information Technology, pp. 286-291. IEEE, 2014.
M J. Mirza ; M W. Tahir ; N. Anjum. Performance Evaluation of M-Estimators as Observation Noise Model in Kalman Filter.In Proc.of IEEE Intl. Conf on Multi-topic Conference (INMIC), 2017
A. S. Khattak ; G. Raja ; N. Anjum; M. Qasim. Integration of Mean-Shift and Particle Filter: A Survey, In Proc.of IEEE Intl. Conf on Frontiers of Information Technology (FIT), 2014
M J. Mirza ; M W. Tahir ; N. Anjum. On Singularities Computation and Classification of Redundant Robots, International Conference on Computing, Communication and Control Engineering (IC4E’2015), May 22-23,2015 Dubai
N. Anjum ; M J. Mirza ; A. Cavallaro Camera network localization using trajectory estimation, Emerging Technologies (ICET), 2011
N. Anjum and A. Cavallaro. Localization of distributed wireless cameras. In Proc. of IEEE Intl. Conf. on Distributed Smart Cameras, Como (Italy), Aug., 2009
N. Anjum and A. Cavallaro. Trajectory association and fusion across partially overlapping cameras. in Proc. of IEEE Intl. Conf. on Advanced Video and Signal Based Surveillance, Genoa (Italy), Sep., 2009. Best paper award
G. Kayumbi, N. Anjum and A. Cavallaro. Global trajectory reconstruction from distributed visual sensors. in Proc of IEEE Intl. Conf. on Distributed Smart Cameras, Stanford, California (USA), Sep., 2008
N. Anjum and A. Cavallaro. Unsupervised fuzzy clustering for trajectory analysis. in Proc of IEEE Intl. Conf. on Image Processing, San Antonio, Texas (USA), Sep., 2007
N. Anjum and A. Cavallaro. Single camera calibration for trajectory-based behaviour analysis. in Proc of IEEE Intl. Conf. on Advanced Video and Signal Based Surveillance, London (UK), Sep., 2007
N. Anjum and A. Cavallaro. Relative position estimation of non-overlapping cameras. in Proc of IEEE Intl. Conf. on Acoustics, Speech and Signal Processing, Honolulu (USA), Apr., 2007

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