Radical Rakhman Wahid

🎓 Education

🖥️ Working Experience

🎤 Talks & Presentations

• Introduction to FastAPI for Machine Learning Application

  Python Conference Indonesia
  🇮🇩 Nov 2023
• Fooling Your Deep Neural Networks with Torchattacks

  Python Conference Indonesia
  🇮🇩 Dec 2021
• Grasping Adversarial Attacks on Deep CNN for Cholangiocarcinoma Classification

  IEEE International Conference on e-Health and Bioengineering
  🇷🇴 Nov 2021
• Hands-on Practice on Machine Learning and Model Deployment

  Data Science Academy on IT Convention
  🇮🇩 Octr 2021
• Optimize Your Database Operations with Asynchronous Processing

  Python Conference Zuid Afrika
  🇿🇦 Oct 2021
• Alzheimer's Disease Stage Classification using Deep CNN on Oversampled Data

  6th International Conference on Science and Technology
  🇮🇩 Sep 2020
• Combining Flask and PyTorch to Build a Computer Aided Diagnotic System

  Python Conference Asia Pacific
  🇲🇾 Sep 2020
• Start Your Web Development Journey with Flask Micro Framework

  Konferensi Pekerja Teknologi Informasi
  🇮🇩 Apr 2020
• Pandas: Python for Data Science

  Python Conference Indonesia
  🇮🇩 Nov 2019
• Deep Learning in Linux Distros

  GNOME.Asia Summit
  🇮🇩 Oct 2019

📑 Research Publications

• F. Azzedin, R. R. Wahid^†, Mufti Mahmud, J. Hassine, "Mitigating Gradient Leakage in Federated Learning for Medical Imaging: Homomorphic Encryption Approach", IEEE Journal of Biomedical and Health Informatics. Submitted on January 2026.
• R. R. Wahid, F. Azzedin, J. Hassine, S. Mahmood, "A Federated Learning Framework with Privacy Protection and Adversarial Robustness: Secure Aggregation and Evasion Detection", Springer Link Evolving Systems Journal. Submitted on December 2025.
• M. Syukron, R. R. Wahid^†, "Vehicles Detection from Overhead Satellite Images in Saudi Arabia with YOLOv12", ITB Journal of Engineering and Technological Sciences. Submitted the second revision on December 2025.
• R. R. Wahid, F. Azzedin, "Applications for Federated Learning: From 6G Communications to Sustainable Smart Societies", In: Buyya R., Mukherjee, A., Das, S.K., Federated Learning: Foundations and Applications. Elsevier. Accepted, will be published on June 2026.
• R. R. Wahid, F. Azzedin, J. Hassine, M. Hammoudeh, "Evaluating the Robustness of Deep Learning Systems on Adversarial Attacks in Medical Images", ACM International Conference on Future Networks and Distributed Systems. Accepted on January 2026.
• R. R. Wahid^‡, F. T. Anggraeny and B. Nugroho, "Brain Tumor Classification with Hybrid Algorithm Convolutional Neural Network-Extreme Learning Machine", International Journal of Computer, Network Security and Information System, vol. 3, no. 01, 2021, pp. 29-33, doi: 10.33005/ijconsist.v3i1.53.
• R. R. Wahid^‡*, C. Nisa', R. P. Amaliyah and E. Y. Puspaningrum, "Lung and Colon Cancer Detection with Convolutional Neural Networks on Histopathological Images", AIP Conference Proceedings, vol. 2654, no. 1, 2023, p. 020020, doi: 10.1063/5.0114327.
• I. G. S. M. Diyasa, R. R. Wahid^‡* and B. P. Amiruddin^†, "Grasping Adversarial Attacks on Deep Convolutional Neural Networks for Cholangiocarcinoma Classification", 2021 International Conference on e-Health and Bioengineering, 2021, pp. 1-4, doi: 10.1109/EHB52898.2021.9657589.
• I. G. S. M. Diyasa, A. Fauzi, A. Setiawan, M. Idhom, R. R. Wahid^* and A. D. Alhajir, "Pre-trained Deep CNN for Detecting Malaria on the Human Blood Smear Images", 2021 International Conference on Artificial Intelligence in Information and Communication, 2021, pp. 235-240, doi: 10.1109/ICAIIC51459.2021.9415183.
• R. R. Wahid^‡*, F. T. Anggraeny and B. Nugroho, "Implementasi Metode Extreme Learning Machine Untuk Klasifikasi Tumor Otak Pada Citra Magnetic Resonance Imaging", Prosiding Seminar Nasional Informatika Bela Negara, vol. 1, 2020, pp. 16-20, doi: 10.33005/santika.v1i0.45.
• E. Y. Puspaningrum, R. R. Wahid^†, R. P. Amaliyah and C. Nisa', "Alzheimer's Disease Stage Classification using Deep Convolutional Neural Networks on Oversampled Imbalance Data", 2020 6th Information Technology International Seminar, 2020, pp. 57-62, doi: 10.1109/ITIS50118.2020.9321061.
• F. T. Anggraeny, I. Y. Purbasari, and R. R. Wahid, "Analysis of Supervised Learning Methods on ANN", Nusantara Science and Technology Proceedings, 2020, pp. 125-134, doi: 10.11594/nstp.2019.0418.

^†contributed equally   ^‡corresponding author   ^*presenter

🏆 Honors & Awards

⚙️ Technical Skills

🤝 Volunteer Experience