Dr. Nadeem Anjum

PROFILE SUMMARY

Dr Nadeem Anjum has been involved in research and development for more than 18 years. Dr Anjum completed his Masters in Computer Science in 2001 from International Islamic University, Islamabad (with distinction). He joined Advanced Engineering Research Organization and served the organization for five years as an Assistant Manager. To further his studies, he went at Queen Mary University of London (QMUL, UK) for MS in computer science. He achieved distinction in MS and got QMUL scholarship for PhD. He earned his PhD in 2010 and then joined Riphah International University, Islamabad in 2010 as an Assistant Professor. In 2013, he joined the University of Engineering and Technology Taxila as an Assistant Professor and served the organization for three years. In 2016, Dr Anjum joined Stemma International (pvt) limited as founding director. Dr Anjum received the best paper award at IEEE AVSS 2009. His current research interests include deep learning for human activity recognition, computer vision, and machine learning.

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
BSc	Double Math, Statistic	Punjab University	1998

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
Teaching Assistant	Multimedia and Vision Group (MMV) at Queen Mary University (QMUL), London	2001 – 2005

INDUSTRIAL EXPERIENCE
Founder Director	Stémma International (PVT) Limited	2016 – 2019
Assistant Manager	Advanced Engineering Research Organization-Pakistan	2001 – 2005

MANAGEMENT EXPERIENCE
HoD Software Engineering	Capital University of Science and Technology, Islamabad	Since – 2021

HONORS & AWARDS
1.	PhD scholarship from Queen Mary University of London
2.	Distinction certificate from Queen Mary University of London in MS
3.	Best paper award, IEEE AVSS 2009, Italy
4.	Distinction certificate from IIUI in MCS

RESEARCH AREAS / INTERESTS

Computer Vision;
Deep Learning for Human activity recognition;
Machine Learning and 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
1.	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.
2.	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.
3.	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, (IF= 3.847).
4.	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, (IF= 3.847).
5.	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).
6.	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
7.	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.
8.	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.
9.	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.
10.	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.
11.	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.
12.	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).
13.	W. Sultan; N. Anjum; M. Stansfield; N. Ramzan, Hybrid Local and Global Deep-Learning Architecture for Salient-Object Detection. Appl. Sci. 2020, 10, 8754.
14.	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.
15.	A. Khattak, G. Raja, N. Anjum. Adaptive Framework for Multi-Feature Hybrid Object Tracking. Applied Sciences, 8(11), p.2294. 2018
16.	S. Bibi, N. Anjum, M. Sher, Automated Multi- Feature Human Interaction Recognition in Complex Outdoor Environments, Elsevier, Computers in Industry (Accepted,2018)
17.	M J. Mirza, and N. Anjum. “Association of moving objects across visual sensor networks.” Journal of Multimedia 7.1 2012
18.	N. Anjum and A. Cavallaro. Automated localization of a camera network. IEEE Intelligent Systems, 2012
19.	N. Anjum. Camera localization in distributed networks using trajectory estimation, Journal of Electrical and Computer Engineering, 2011
20.	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
21.	N. Anjum and A. Cavallaro. Trajectory clustering for scene context learning and outlier detection. Springer-Verlag series on Studies in Computational Intelligence, 2010
22.	N. Anjum and A. Cavallaro. Multi-camera calibration and global trajectory fusion. Intelligent Video Surveillance Systems and Technology, 2010

CONFERENCE PUBLICATIONS
1.	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.
2.	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.
3.	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
4.	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
5.	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
6.	N. Anjum ; M J. Mirza ; A. Cavallaro Camera network localization using trajectory estimation, Emerging Technologies (ICET), 2011
7.	N. Anjum and A. Cavallaro. Localization of distributed wireless cameras. In Proc. of IEEE Intl. Conf. on Distributed Smart Cameras, Como (Italy), Aug., 2009
8.	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
9.	8. 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
10.	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
11.	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
12.	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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