Saeed Iqbal

Saeed Iqbal, Ph.D.

Research Associate Professor
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I am a Research Associate Professor in the College of Mechatronics and Control Engineering at Shenzhen University, China, where I supervise MS and Ph.D. students on projects involving deep learning, continual learning, machine unlearning, and the latest methodologies in federated learning.

Previously, I served as an Assistant Professor at the University of Central Punjab (UCP), Pakistan, where I successfully planned and implemented undergraduate programs in Data Science and AI, as well as a postgraduate program (MSDS). I also led the Healthcare Modeling and Informatics group within the Centre for Applied Data Analytics, fostering collaborations with clinicians to develop automated disease prediction solutions.

With over 20 years of combined professional experience, my research focuses on privacy-preserving, robust AI solutions that enhance diagnosis and prognosis in healthcare, bridging the gap between computational methods and clinical applications.

Research Metrics

922 Citations h-index: 17 i10-index: 23

Education

  • Ph.D. Computer Science
    University of Central Punjab, Pakistan (2023)
  • MS. Computer Science
    FAST NUCES, Pakistan (2012)
  • BSIT. (Honors)
    Punjab University College of IT, Pakistan (2007)

Research Interests

  • Federated & Continual Learning
  • Machine Unlearning
  • Medical Image Analysis
  • Adaptive Self-Learning & Anomaly Detection

Core Skills

  • PyTorch, TensorFlow, Keras, OpenCV
  • Python, Java, C++, SQL

Recent News

2026
New paper accepted in Information Fusion (IF: 15.5, Top Tier Q1)! "Responsible AI in Healthcare: Mitigating Hallucinations and Enhancing Multimodal Fusion-Based Reasoning in Medical Imaging".
2026
New paper accepted in Expert Systems with Applications (IF: 7.5, Top Tier Q1)! "Hierarchical federated learning with paillier encryption: synergistic approach for secure analytics of sensitive healthcare data".
Nov 2024
Joined Shenzhen University as a Research Associate Professor, supervising MS and Ph.D. students in Federated Learning and Deep Learning.
Jan 2024
Paper "Dynamic selectout and voting-based federated learning" accepted in Machine Learning: Science and Technology (IOP Science, Q1).

Awards & Grants

  • Level-1 Researcher (2022, 2023, 2024)
  • Best Research & Innovator Award (2022, 2023)
  • Shenzhen Natural Science Foundation Grant for "SymPhyNeuMA: Symbolic-Physics Neural Material Adaptor"
  • Samsung Innovation Campus (SIC) Grant for AI Training Programs (2021)

Intellectual Property

  • Patent: Holistic Campus Security optimized detection/tracking system using Deep Learning with commodity hardware in real-time environment.

Selected Publications

Professional Service

  • Program Development: Designed and implemented BS Data Science & AI, and MS Data Science programs at UCP.
  • Research Leadership: Led Healthcare Modeling and Informatics group, fostering clinician collaborations for automated disease prediction.
  • Administration: Over a decade of experience leading Exam, Registration, and Course Planning Committees.

Editorial & Review Services

  • Editorial Member: BMC Biomedical Engineering
  • Program Committee: IEEE INMIC 2024, ICITCS 2017, IEEE Symposium on Computer Applications & Industrial Electronics
  • Journal Reviewer: IEEE TMI, IEEE TFS, IEEE TIP, Springer Archives of Comp. Methods in Eng., Elsevier Neural Networks, Information Processing & Management, Knowledge-Based Systems, Pattern Recognition, Medical Image Analysis, and more.

Graduate Supervision

  • Currently supervising MS and Ph.D. students at Shenzhen University on deep learning and federated learning projects.
  • MS Supervisions: Diabetic Foot Ulcer Segmentation, Hybrid Feature Engineering for Image Classification, Diabetic Retinopathy Detection, Breast Cancer Classification.
  • Undergraduate: Guided 80+ Final Year Projects (FYPs) in AI, ML, and Medical Image Analysis.