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Dr .Atifc Rizwan |Machine Learning Award | Best Researcher Award

Dr .Atif Rizwan ,Kyunghee University,South Korea

Dr. Atif Rizwan is a distinguished academician and researcher currently affiliated with Kyunghee University in South Korea. With expertise in [mention specific field or area of research], Dr. Rizwan has contributed significantly to the academic community through his innovative research and publications. His dedication to excellence in teaching and research has earned him recognition and respect both nationally and internationally. Dr. Rizwan’s commitment to advancing knowledge and fostering collaboration makes him a valuable asset to the academic community at Kyunghee University and beyond.

Professional Profiles:

Scopus

Education:

  • PhD in Computer Engineering
    Jeju National University, Jeju-si, Republic of Korea
    CGPA: 4.39/4.5
    Thesis Title: Joint NAS and Topology Optimization for Decentralized Federated Learning in AIoT Digital Twin Networks
  • Master of Science in Computer Science (MSCS)
    COMSATS University Islamabad, Attock, Punjab, Pakistan
    CGPA: 3.63/4.0
    Thesis Title: WR-SVM model based on the margin radius approach for solving the minimum enclosing ball problem in support vector machine classification
  • Master of Computer Science (MCS)
    COMSATS University Islamabad, Attock, Punjab, Pakistan
    CGPA: 3.83/4.0
  • Bachelor of Science (BSC)
    University of the Punjab, Lahore, Punjab, Pakistan
    Marks: 519/800

 

Professional Experience :

  • Visiting Lecturer
    COMSATS University Islamabad, Attock Campus
    Spring 2018 – Spring 2020
    Responsibilities: Leading programming labs in Java, Python, and C#, guiding students in industry projects.

Technical Skills:

  • Programming: Python, Java, C++, C#
  • Frameworks & CMS: Django, Flask, Codeignitor, MVC
  • Web Development: HTML, CSS, Bootstrap, JavaScript, jQuery, PhP
  • Databases: SQL, MySQL, SQLite
  • Software: Spyder, Jupyter, MATLAB, Sublime Text, PyCharm, Visual Studio, Anaconda, Dreamweaver, Eclipse, NetBeans
  • Protocols: IEEE 802.11, HTTP, CoAP, MQTT, TCP/IP
  • Operating Systems: Ubuntu, Raspbian, Windows

Research Object:

  • Neural Architecture Search for Resource Constraint Devices in DFL
  • Optimization of Topology in DFL
  • Digital Twin for Decentralized Federated Learning
  • Personalized Hierarchical Heterogeneous FL
  • Digital Twin for Centralized Federated Learning
  • Sampling-Based Model Consolidation for Attack Prevention in Federated Learning
  • Indoor Environment Optimization Techniques using Deep Learning in Edge Computing Environments
  • Optimal location for Water Drilling
  • Self Optimal Environment Control with minimum energy consumption for Greenhouse environment
  • Realtime Situation Reporting using YOLO

Development Projects:

  • Developed more than ten android applications using Java, XML, SQL, Firebase.
  • Developed more than 5 web applications using HTML, CSS, Bootstrap, jQuery, PhP, Python, SQL.

Publications:

  1. Khan, A. N., Rizwan, A., Ahmad, R., Jin, W., Khan, Q. W., Lim, S., & Kim, D. H. (2023). Hetero-FedIoT: A Rule-Based Interworking Architecture for Heterogeneous Federated IoT Networks. IEEE Internet of Things Journal.
  2. Rizwan, A., Ahmad, R., Khan, A. N., Xu, R., & Kim, D. H. (2023). Intelligent digital twin for federated learning in AIoT networks. Internet of Things, 100698.
  3. Khan, A. N., Rizwan, A., Ahmad, R., Khan, Q. W., Lim, S., & Kim, D. H. (2023). A precision-centric approach to overcoming data imbalance and non-IIDness in federated learning. Internet of Things, 100890.
  4. Khan, Q. W., Kim, B. W., Ahmed, R., Rizwan, A., Khan, A. N., Kim, K., & Kim, D. H. (2023). Predictive Modeling of Water Table Depth, Drilling Duration, and Soil Layer Classification using Adaptive Ensemble Learning for Cost-Effective Percussion Water Borehole Drilling. IEEE Access.
  5. Shah, S. M. A. H., Shah, S. F. H., Ullah, A., Rizwan, A., Atteia, G., & Alabdulhafith, M. (2023). Arabic Sentiment Analysis and Sarcasm Detection using Probabilistic Projections Based Variational Switch Transformer. IEEE Access.
  6. Khan, A. N., Rizwan, A., Ahmad, R., & Kim, D. H. (2023). An OCF-IoTivity enabled smart-home optimal indoor environment control system for energy and comfort optimization. Internet of Things, 22, 100712.
  7. Khan, A. N., Kim, B. W., Rizwan, A., Ahmad, R., Iqbal, N., Kim, K., & Kim, D. H. (2023). A New Method for Determination of Optimal Borehole Drilling Location Considering Drilling Cost Minimization and Sustainable Groundwater Management. ACS Omega.
  8. Rizwan, A., Khan, A. N., Ahmad, R., & Kim, D. H. (2022). Optimal environment control mechanism based on OCF connectivity for efficient energy consumption in greenhouse. IEEE Internet of Things Journal, 10(6), 5035-5049.
Atifc Rizwan | Machine Learning Award |Best Researcher Award

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