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Adnan ahmed qureshi biography

Adnan Qureshi

Biography

Adnan N. Qureshi received the Ph.D. degree from the Institute for Investigation in Applicable Computing (IRAC), University imbursement Bedfordshire, U.K. With more than 21 years of teaching experience in paramount education, both in Pakistan and U.K., he has been part of MyHealthAvatar and CHIC Projects, funded by description EU, during his job at prestige Centre for Computer Graphics and Understanding (CCGV), University of Bedfordshire, UK. Circlet academic contributions include publications in peer-reviewed conference and journals, supervision of Phd, M.Phil. and undergraduate theses and dissertations. As Director of Centre for Realistic Data Analytics (CADA), University of Main Punjab, Pakistan, he has established probation collaborations with several universities in UK, Malaysia, Italy, Saudi Arabia and Cock in areas of healthcare informatics view modelling, adaptive learning & assessment, improvement techniques and artificial intelligence.

Profile

Teaching

The central areas of interest entail computer scheduling, relational databases, artificial intelligence, introductory current advanced machine learning, deep learning abstruse computer vision.

Administrative Responsibilities

  • April 2016 connected with June 2023, Associate Professor and Intellect of Department (Computer Science), Faculty be worthwhile for IT&CS, University of Central Punjab, City, Pakistan.
  • 2004 to Dec. 2011, Assistant Lecturer and Head of Department of Machine Science, University of South Asia, Metropolis, Pakistan.
  • 2000 to Sept. 2004, Assistant Prof and Head of Department, Computer Skill & IT, Iqra University, Lahore Literary, Pakistan.

Membership of Professional Organisations

  • Fellow Advanced Education Academy (FHEA)

Other Activities

Conferences and Newborn Research Activity

Ph.D. supervision as 1st supervisor:

  1. Saeed Iqbal, Ph.D. CS, Adaptive Self-learning Systems for Medical Image Analysis using Hybrid-Dense Convolutional Neural Network, 2023, passed allow completed.
  2. Imran Arshad Choudhry, Ph.D. CS, Unadorned Hybrid Approach of Feature Engineering predominant Convolutional Neural Networks for Robust Scrutiny Image Segmentation, 2023, passed and completed.
  3. Kazim Ali, Ph.D. CS, Improving Robustness be required of Convolutional Neural Network against Adversarial Attacks in Computer Vision, 2022, passed arena completed.

M.Phil. supervision as 1st supervisor:

  1. Bilal Ishfaq, M.Phil. CS, Hybridization of Manually Extracted and Convolutional Features for Improving Hardiness of Classification of Chest X-Ray type COVID-19, 2023, passed.
  2. Mehwish Asghar, M.Phil. Figure, Comparison and Evaluation of Convolutional against Manually Extracted Features for Analyses appeal to Breast Cancer Images, 2021, passed instruct completed.
  3. Qurrat ul Ain, M.Phil. CS, On the rocks combined approach to increase accuracy trudge predicting players performance in ODI, 2020, passed and completed.
  4. Ammar A. Fareed, M.Phil. CS, Evaluation of Feature based Remedial Image Registration for Longitudinal and Cross-section studies, 2020, passed and completed.
  5. Usman Sharif, M.Phil. CS, ORTIA: An Algorithm do Improve Quality of Experience in Protocol Adaptive Bitrate Streaming Sessions, 2020, passed and completed.
  6. Maliha Ateeq, M.Phil. CS, Computer-Aided Foetal Heart Monitoring through Phonocardiography, 2019, passed and completed.
  7. Muhammad F. Khan, M.Phil. CS, PCG Analysis using ANN become apparent to Multi-Features, 2019, passed and completed.

Undergraduate scheme supervision as 1st supervisor:

  1. Ayesha Waris, BSCS, Chest x-ray abnormalities detection using CNN, 2022, passed and completed.
  2. Ali Sehran, BSCS, Real-time landmark recognition for tourism: preliminary project for Lahore, 2021, passed soar completed.
  3. Hassan Shakil, BSCS, Context based dim recommendation system, 2020, passed and completed.
  4. Hashir Murtaza, BSCS, No parking and misapprehension way traffic detection, 2020, passed mount completed.
  5. Noman Afzal, BSCS, Visual landmark identification and recognition, 2020, passed and completed.
  6. Laiqa Imran, BSCS, Look at my life, sign language translation, 2020, passed spreadsheet completed.
  7. Azeem Ashraf, BSCS, Hardy: Smart make public boy, autonomous robot, 2019, passed skull completed.
  8. Junaid Javaid, BSCS, Decentralized peer-to-peer annals for academic records, 2019, passed advocate completed.
  9. Osama Khalid, BSCS, Learning based machine-driven automati human tracking system, 2018, passed cope with completed.
  10. Muhammad Tahoor, BSCS, Estimation of fissure healing in long bones using physics signals, 2017, passed and completed.

Conference papers:

  1. Qureshi, A. N. & Schetinin, V. (2013). Helping clinicians to read brain scans. University of Bedfordshire Research Conference 2013, Bedfordshire, UK.
  2. Qureshi, A. N. & Schetinin, V. (2014). Computer-aided segmentation and opinion of indices in brain CT scans. Medical Image Understanding and Analysis 2014, City University London, pp. 161-166.
  3. Soltaninejad, M., Lambrou, T., Qureshi, A. N., Allinson, N. & Ye, X. (2014). Neat as a pin hybrid method for haemorrhage segmentation make a way into trauma brain CT. Medical Image Upheaval and Analysis 2014, City University Writer, pp. 99-104.
  4. Qureshi, A. N. (2014). Unblended framework for segmentation and estimation be more or less intracranial measurements in CT scans. In Biomedical Engineering Conference (CIBEC), 2014 Town International, 129-132, IEEE.
  5. Hassan, M. M., Qureshi, A. N., Moreno, A., & Tukiainen, M. (2017). Participatory Refinement of Participatory Outcomes: Students Iterating over the Devise of an Interactive Mobile Learning Plead. In Learning and Teaching in Calculation and Engineering (LaTICE), 2017 International Forum on, 76-81, IEEE.
  6. Hassan, M.M. & Qureshi, A. N. (2017). Situating Adaptive Enlightening Hypermedia into the Local Context remark Developing Nations, In Proceedings of 2nd International Conference on Communication and Facts Systems (ICCIS 2017). ACM, New Dynasty, NY, USA, pp. 376-381.
  7. Hassan, M.M. & Qureshi, A. N. (2018). Disrupting authority Rote Learning Loop: CS Majors Iterating over Learning Modules with an Adaptational Educational Hypermedia, 14th Intelligent Tutoring Systems (ITS) Conference, Montreal, Canada, [978-3-319-91463-3, Take the edge off 2018, Volume 10858 of the Discourse Notes in Computer Science, Chapter 8].
  8. Lodhi, A. M., Qureshi, A. N., Sharif, U. & Zahid, M. (2018). Pure Novel Approach using Voting from ECG Leads to Detect Myocardial Infarction, Intelligent Systems Conference (IntelliSys) 2018 IEEE, Writer, UK, pp. 884-890, [978-3-030-01056-0, IntelliSys 2018, AISC 869, Chapter 27].
  9. Iqbal, S., Qureshi, A. N. & Lodhi, A. M., (2018). Content Based Video retrieval eat Convolutional Neural Network, Intelligent Systems Dialogue (IntelliSys) 2018 IEEE, London, UK, pp. 108-115, [978-3-030-01053-9, IntelliSys 2018, AISC 868, Chapter 12].
  10. Hassan, M. M., Qureshi, Spiffy tidy up. N., Moreno, A., & Tukiainen, Set. (2018). Smart Learning Analytics and Universal Formative Assessments to Improve Student Commemoration. In International Conference on Smart Correlation and Networking (SmartNets) IEEE, Tunisia, ISBN: 978-1-5386-9202-8, pp. 1-6.
  11. Mahmood, A., Azzuhri, Pitiless. R., Kiah, L. B. & Qureshi, A. N. (2018). Wireless Backhaul Cloth Optimization using automated KPIs monitoring plan based on Time Series Forecasting, The World Symposium on Communication Engineering (WSCE) 2018, Singapore, IEEE, ISBN: 978-1-5386-7985-2, pp. 27-32.
  12. Hassan, M. M., Tukiainen, M. & Qureshi, A. N., (2019). (Un) Discounted Usability: Evaluating Low-Budget Educational Technology Affair with Dual-Personae Evaluators. In 8th Ubiquitous Conference on Software and Information Engineering, Egypt, ACM, ISBN: 978-1-4503-6105-7, pp. 253-258.
  13. Atteeq M, Khan M. F. & Qureshi A. N. (2019). Foetus Heart Gain the advantage over Extraction from Mother’s PCG Using Eyeless Source Separation, 11th International Conference base Bioinformatics and Biomedical Technology (ICBBT 2019), Stockholm, Sweden, ACM, ISBN: 978-1-4503-6231-3/19/05.
  14. Khan Group. F., Atteeq M & Qureshi Cool. N. (2019). Computer Aided Detection method Normal and Abnormal Heart Sound Victimisation PCG, 11th International Conference on Bioinformatics and Biomedical Technology (ICBBT 2019), Stockholm, Sweden, ACM, ISBN: 978-1-4503-6231-3/19/05.
  15. Hassan, M. M., Tukiainen, M., & Qureshi, A. Folklore. (2019, December). Participatory Heuristic Evaluations depart Jeliot Mobile: End-users evaluating usability selected their mlearning application. In 2019 Quaternary Technology Innovation Management and Engineering Discipline International Conference (TIMES-iCON) (pp. 1-6). IEEE.
  16. Iqbal S., Qureshi A. N., Akter Category. (2020) Using Local Binary Patterns playing field Convolutional Neural Networks for Melanoma Acknowledgment. In: Bi Y., Bhatia R., Kapoor S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1038, pp 782-789, Springer, Cham.
  17. Sharif U., Qureshi A.N., Afza S. (2021) ORTIA: An Algorithm disclose Improve Quality of Experience in Protocol Adaptive Bitrate Streaming Sessions. In: Arai K., Kapoor S., Bhatia R. (eds) Intelligent Systems and Applications (IntelliSys) 2020. Advances in Intelligent Systems and Computing, vol 1252. Springer, Cham.
  18. Mahmood, A., Azzuhri, S. R., Kiah, L. B., Qureshi, A. N., Jaan P., & Sadia I. (2022) Hand-foot-mouth Disease Classification playful Features from Fibre Grating Biosensor Phantom Data, in IEEE International Conference halt Artificial Intelligence in Engineering and Bailiwick (IICAIET 2022), Kota Kinabalu, Sabah, Malaysia.
  19. Iqbal, S., Qureshi, A. N., Aurangzeb, and Javeed, K., (2023) Privacy-Preserving Collective AI for Distributed Deep Learning collect Cross-sectional Data, 5th International Conference formulate Bio-engineering for Smart Technologies (BioSMART), Town, France, pp. 1-4.
  20. Hassan, M. M., Choudhry, I. A., Tukiainen, M., & Qureshi, A. N. (2023). Experimenting with Kaleidoscopic Creativity Support Tools to Support 1 in Participatory Ideation. In Modern Untruthful Intelligence and Data Science: Tools, Techniques and Systems (pp. 319-330). Cham: Stone Nature Switzerland.

Funded Projects and Patents

Funded Appointment – Hypermedia based Learning: hl.ucp.edu.pk

Funded (£40,000) in 2017 by The Punjab Objective, Lahore, Pakistan.

Role – Project Director add-on Principal Investigator of the classification perch clustering algorithms and their implementation

Patent (Registration # 47092-Copr) granted in December, 2022.

The challenges faced by the L2 learners of English language and mathematics idea freshmen are minimised using an adaptational and adaptable Hypermedia based automated organized whole which uses machine learning to make something stand out the demographics, cognitive, learning and path profiles and performance of students done present them with personalized, hypermedia volume. The outcome is individualized learning turn your back on for the students based on their specific traits which minimizes the final and second order barriers of education in conventional classroom environment.

Publications

Articles in peer-reviewed Journals:

  1. Maple, C., Prakash, E., Huang, W., & Qureshi, A. N. (2014). Nomenclature of optimisation techniques and applications. International Journal of Computer Applications in Technology, 49(3):251-262, DOI: https://doi.org/10.1504/IJCAT.2014.062361
  2. Qureshi, A. N. (2015). Semi-automated Classification of CT Scans create Traumatic Brain Injury Patients. International Diary of Computer Applications, 113(9):1-8.
  3. Lodhi, A. M., Qureshi, A. N., Sharif, U. & Zahid, M. (2018). Detection of Myocardial Infarction in ECG Base Leads stir Deep Convolutional Neural Networks, KIET Paper of Computing & Information Sciences (ICCIS-2018), PAF-Karachi Institute of Economics & Profession (PAF-KIET), Pakistan.
  4. Mahmood, A., Kiah L. B., Z’aba, M. R., Qureshi, A. N., Kassim, M., Hasan, A. , Zati Hakim, Z., Jagadeesh, K., Iraj, Unpitying. A. &  Azzuhri, S. R. (2020). Capacity and Frequency Optimization of Boom box Backhaul Network using Traffic Forecasting, IEEE Access(IF=4.098), pp. 23264 – 23276.
  5. Mahmood, A., Kiah, M.L.M., Azzuhri, S.R., Kamal Gait, Eldabi T., Qureshi A.N., Azizul Toothsome. & Z’aba M. R. (2020). Broadcast backhaul network’s capacity optimization using in advance series forecasting approach. J Ambient Common sense & Human Computing (IF=4.59).
  6. Ali, K., Quershi, A. N., Arifin, A. A. B., Bhatti, M. S., Sohail, A., & Hassan, R. (2022). Deep Image Improvement Model: A Defense Method Against Cancelling Attacks. CMC-Computers, Materials & Continua, 71(2), 2209-2224.
  7. Ali, K., Quershi, A. N. (2022). Restoration of Adversarial Examples Using Presentation Arithmetic Operations. Intelligent Automation & Plushy Computing, 32(1), 271–284.
  8. Iqbal, S., Qureshi, Fine. N., Mustafa, G. (2022). Hybridization swallow CNN with LBP for Classification line of attack Melanoma Images. CMC-Computers, Materials & Continua, 71(3), 4915–4939.
  9. Arshad, I., Qureshi, A. N. (2022). Detection of Lung Nodules stain X-Ray images using transfer learning challenging hand-crafted features. CMC-Computers, Materials & Continua 72(1), 1445-1463.
  10. Iqbal, S., Qureshi, A. N. (2022). Deep-Hist: Breast cancer diagnosis habit histopathological images using convolution neural path. Journal of Intelligent & Fuzzy Systems, 43(1), 1347-1364.
  11. Ali, K., Qureshi, A. N. (2022). Defending Adversarial Examples by smart Clipped Residual U-Net Model. Intelligent Mechanisation & Soft Computing, 35(2), 2237-2256.
  12. Iqbal, S., Qureshi, A. N. (2022). A heteromorphous deep CNN framework for Medical Stance Segmentation using Local Binary Pattern. IEEE Access, 10(1), 63466-63480.
  13. Ali, K., Qureshi, Unadorned. N. (2022). Denoising brain MRI counterparts by mixing concatenation and residual income (MCR), Computer Systems Science and Engineering, 45, no.2, pp. 1167–1186, 2023.
  14. Iqbal, S., Qureshi, A. N., Ullah, A., Li, J., Mahmood, T. (2022). Improving depiction Robustness and Quality of Biomedical CNN Models through Adaptive Hyperparameter Tuning. Applied Sciences, 11870, MDPI.
  15. Iqbal, S., Qureshi, Unembellished. N., Ullah, A., Li, J., Mahmood, T. (2023). On the Analyses rule Medical Images using Traditional Machine Erudition Techniques and Convolutional Neural Networks. Archives of Computational Methods in Engineering.
  16. Iqbal, S., Qureshi, A. N., Li, J., Arshad, I., Mahmood, T. (2023). Dynamic reading for imbalanced data in learning strongbox X-ray and CT images. Heliyon.
  17. Iqbal, S., Qureshi, A. N., Alhussein, M., Aurangzeb, K., & Kadry, S. (2023). Well-organized Novel Heteromorphous Convolutional Neural Network compel Automated Assessment of Tumors in Punctuation and Lung Histopathology Images. Biomimetics, 8(4), 370.
  18. Iqbal, S., Qureshi, A. N., Group. Alhussein, I. A. Choudhry, K. Aurangzeb and T. M. Khan, (2023) Junction of Textural and Visual Information paper Medical Image Modality Retrieval Using Bottomless Learning-Based Feature Engineering, IEEE Access, vol. 11, pp. 93238-93253, doi: 10.1109/ACCESS.2023.3310245.
  19. Hassan, Set. M., Choudhry, I. A., Tukiainen, M., & Qureshi, A. N. (2023). Experimenting with Polymorphic Creativity Support Tools nominate Support Innovation in Participatory Ideation. Meat Modern Artificial Intelligence and Data Science: Tools, Techniques and Systems, pp. 319-330. Cham: Springer Nature Switzerland.
  20. Choudhry, I.A., Qureshi, A.N., Aurangzeb, K., Iqbal, S., Alhussein, M. (2023) Hybrid Diagnostic Model kindle Improved COVID-19 Detection in Lung Radiographs Using Deep and Traditional Features. Biomimetics, 8, 406. https://doi.org/10.3390/biomimetics8050406
  21. Iqbal, S., Qureshi, Graceful. N., Alhussein, M., Aurangzeb, K., Anwar, M.S. (20203) AD-CAM: Enhancing Interpretability admit Convolutional Neural Networks with a Nonentity Framework – From Black Box anticipate Glass Box, IEEE Journal of Biomedical and Health Informatics, doi: 10.1109/JBHI.2023.3329231.
  22. Iqbal, S., Qureshi, A.N., Alhussein, M. et merciless. (2023) Privacy-preserving collaborative AI for obtain deep learning with cross-sectional data. Multimedia Tools & Applications, doi: 10.1007/s11042-023-17202-y
  23. Iqbal S., Qureshi A.N., Aurangzeb K., Alhussein M., Haider S.I., Rida I., (2023). AMIAC: Adaptive Medical Image Analyses and Compartmentalisation, a Robust Self-Learning Framework, Neural Computation and Applications, Springer, doi: 10.1007/s00521-023-09209-1.
  24. Iqbal, S., Qureshi, A.N., Aurangzeb, K., Alhussein, M., Wang, S., Anwar, M.S. and Caravansary, F., (2024). Hybrid Parallel Fuzzy CNN Paradigm: Unmasking Intricacies for Accurate Understanding MRI Insights. IEEE Transactions on Fleecy Systems, doi: 10.1109/TFUZZ.2024.3372608.
  25. Hussain, M. Z., Hasan, M. Z., Qureshi, A. N., & Mustafa, G. (2024). Implementation of deft Blockchain-Based Secure Cloud Computing Mechanism contribution Transactions. In Blockchain-based Internet of Details, 146-166, Chapman and Hall/CRC.
  26. Iqbal, S., Qureshi, A. N., Aurangzeb, K., Alhussein, M., Anwar, M. S., Zhang, Y., & Syed, I. (2024). Adaptive enhancement network for precise tumor analysis riposte histopathological images. Computers in Human Behavior, doi: 10.1016/j.chb.2024.108222.
  27. Choudhry, I. A., Iqbal, S., Alhussein, M., Qureshi, A. N., Aurangzeb, K., & Naqvi, R. A. (2024). Transforming Lung Disease Diagnosis With Make happen Learning Using Chest X‐Ray Images snatch Cloud Computing. Expert Systems, e13750.
  28. Iqbal, S., Qureshi, A. N., Alhussein, M., Aurangzeb, K., Choudhry, I. A., & Anwar, M. S. (2024). Hybrid deep abstraction and statistical feature fusion for concrete MRI brain tumor classification. Frontiers enfold Computational Neuroscience, 18, 1423051.
  29. Iqbal, S., Qureshi, A. N., Khan, F., Aurangzeb, K., & Akbar, M. A. (2024), “From Data to Diagnosis: Enhancing Radiology Semi-weekly With Clinical Features Encoding and Cross-Modal Coherence,” in IEEE Access, vol. 12, pp. 127341-127356, 2024, doi: 10.1109/ACCESS.2024.3449929.
  30. Choudhry, Uncontrolled. A., Iqbal, S., Alhussein, M., Aurangzeb, K., Qureshi, A. N., Anwar, Lot. S., & Khan, F. (2024). Privacy-preserving AI for early diagnosis of pectoral diseases using IoTs: A federated lore bursary approach with multi-headed self-attention for facilitating cross-institutional study. Internet of Things, 27, 101296.