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Our team

Dr. Fahmid Al Farid

Dr Fahmid Al Farid is a Lecturer at the Berlin School of Business & Innovation (BSBI), Germany, where he leads teaching and research in computer vision and artificial intelligence, specialising in image and video analysis. With over 12 years of academic and research experience, he has developed a strong career that includes positions as a Postdoctoral Research Scientist at Multimedia University, Malaysia, and Research Assistant at both the University of Ulsan and Sungkyunkwan University in South Korea.

Overview

Dr Fahmid Al Farid is a Lecturer at the Berlin School of Business & Innovation (BSBI), Germany, where he leads teaching and research in computer vision and artificial intelligence, specialising in image and video analysis. With over 12 years of academic and research experience, he has developed a strong career that includes positions as a Postdoctoral Research Scientist at Multimedia University, Malaysia, and Research Assistant at both the University of Ulsan and Sungkyunkwan University in South Korea.

Dr Al Farid holds a PhD in Information Technology from Multimedia University, an MSc in Electrical and Computer Engineering from the University of Ulsan, and a BSc in Computer Science and Engineering from the University of Chittagong. An active IEEE member, he has authored numerous high-impact publications covering areas such as vision-based hand gesture recognition, deep learning for crowd density estimation, and tomato leaf disease detection. As of 2025, his research has accumulated over 675 citations and an h-index of 15. His interests also extend to practical AI applications, including electric vehicle smart charging systems and solar photovoltaic home systems.

Dedicated to teaching and mentorship, Dr Al Farid supervises postgraduate students and collaborates with international researchers to advance the state of the art in AI and computer vision. His primary goal is to apply advanced AI techniques to solve real-world challenges, inspiring innovation and impact through research and education at BSBI.

Areas of expertise

  • Artificial Intelligence
  • Machine Learning & Deep Learning
  • Computer Vision
  • Medical Imaging
  • Smart Farming

Awards and Honours

  • Gold Medal, iNVENTX 2025, Malaysia
  • Silver Medal, iNVENTX 2025, Malaysia
  • Keynote Speaker, ICIERI 2024, Indonesia
  • Gold Medal, iNVENTX 2024, Malaysia
  • Postdoctoral Fellowship, Faculty of Engineering, Multimedia University (2023)
  • Best Paper Award, 7th International Visual Informatics Conference, UNITEN, Malaysia (2021)
  • Bronze Medal, Innovative Research, Invention and Application Exhibition (I-RIA2021)
  • Bronze Medal, Multimedia University, Malaysia (2021)
  • Finalist, Programming League National 2020, University of Malaya (Ranked 9th of 200+ teams)
  • Director of ICT, WWO Global Malaysia (Volunteer, 2019–present)
  • Fully Funded PhD Scholarship, Multimedia University, Malaysia
  • BK21 PLUS Scholarship, Korean Government (2012–2014)
  • Bangladesh Government ICT Scholarship in MS (2014)

Research interests

  • Artificial Intelligence
  • Machine Learning & Deep Learning
  • Computer Vision
  • Medical Imaging
  • Smart Farming

Publications

  1. Bhuiyan, M.R., Abdullah, J., Hashim, N., Farid, Fahmid A., Isa, W.N.M., Uddin, J., & others, 2025. Optical flow and deep learning-based anomaly detection for hajj pilgrimage crowd monitoring. Signal, Image and Video Processing, 19(9), pp.1–10. Available at: https://doi.org/10.1007/s11760-025-04291-5
  2. Siddika, A., Begum, M., Farid, Fahmid A., Uddin, J., & Karim, H.A., 2025. Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms. Eng, 6(7), p.161. Available at: https://doi.org/10.3390/eng6070161
  3. Pal, O.K., Farid, Fahmid A., Mridha, M.F., Kabir, R., Islam, M.R., & Karim, H.A., 2025. SkinPalNet: An Advanced Ensemble Model for Skin Cancer Diagnosis with Computer Vision Approach. In: International Conference on Industrial, Engineering and Other Applications. Available at: https://link.springer.com/chapter/10.1007/978-981-96-8892-0_35
  4. Jahin, M.A., Soudeep, S., Farid, Fahmid A., Mridha, M.F., Kabir, R., Islam, M.R., & Karim, H.A., 2025. Cagn-gat fusion: A hybrid contrastive attentive graph neural network for network intrusion detection. In: International Conference on Industrial, Engineering and Other Applications, p.5. [Link to paper]
  5. Dipo, M.H., Farid, Fahmid A., Mahmud, M.S.A., Momtaz, M., Rahman, S., Uddin, J., & others, 2025. Real-Time Waste Detection and Classification Using YOLOv12-Based Deep Learning Model. Digital, 5(2), p.19. Available at: https://doi.org/10.3390/digital5020019
  6. Farid, Fahmid A., Bari, A., Miah, A.S.M., Mansor, S., Uddin, J., & Kumaresan, S.P., 2025. A Structured and Methodological Review on Multi-View Human Activity Recognition for Ambient Assisted Living. Journal of Imaging, 11(6), p.182. Available at: https://doi.org/10.3390/jimaging11060182
  7. Alom, M.R., Farid, Fahmid A., Rahaman, M.A., Rahman, A., Debnath, T., Miah, A.S.M., & others, 2025. An explainable AI-driven deep neural network for accurate breast cancer detection from histopathological and ultrasound images. Scientific Reports, 15(1), p.17531. Available at: https://10.1038/s41598-025-97718-5
  8. Navin, N., Farid, Fahmid A., Rakin, R.Z., Tanzim, S.S., Rahman, M., Rahman, S., Uddin, J., & others, 2025. Bilingual sign language recognition: A YOLOv11-based model for Bangla and English alphabets. Journal of Imaging, 11(5), p.134. Available at: https://doi.org/10.3390/jimaging11050134
  9. Rakin, R.Z., Rahman, M., Borsa, K.F., Farid, Fahmid A., Rahman, S., Uddin, J., & Karim, H.A., 2025. Towards Safer Cities: AI-Powered Infrastructure Fault Detection Based on YOLOv11. Future Internet, 17(5), p.187. Available at: https://doi.org/10.3390/fi17050187
  10. Sharmin, S., Farid, Fahmid A., Jihad, M., Rahman, S., Uddin, J., Rafi, R.K., Hossan, R., & others, 2025. A Hybrid CNN Framework DLI-Net for Acne Detection with XAI. Journal of Imaging, 11(4), p.115. Available at: https://doi.org/10.3390/jimaging11040115
  11. Islam, M.R. & Farid, Fahmid A., 2025. Advancements in AI-Based Anomaly Detection for Smart Manufacturing. In: Artificial Intelligence for Smart Manufacturing and Industry X.0, pp.37–68. Available at: https://doi.org/10.1007/978-3-031-80154-9_3
  12. Kamal, S.T., Jabin, F., Ullah, S.E., Jahan, U.S., Hossain, M.N., Rahim, M.A., & others, 2025. Performance analysis of multiuser mmWave DCT-spread CP-Less OFDM communication system. Multidisciplinary Science Journal, 7(3), pp.2025135–2025135. Available at: https://doi.org/10.31893/multiscience.2025135
  13. Islam, M.S., Farid, Fahmid A., Shamrat, F.M.J.M., Islam, M.N., Rashid, M., Bari, B.S., & others, 2024. Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review. PeerJ Computer Science, 10, p.e2517. Available at: https://doi.org/10.7717/peerj-cs.2517
  14. Sarker, M.T., Farid, Fahmid A., Alam, M.J., Ramasamy, G., Karim, H.A., Mansor, S., & others, 2024. Analysis of the power sector in Bangladesh: Current trends, challenges, and future perspectives. Bulletin of Electrical Engineering and Informatics, 13(6), pp.3862–3879. Available at: https://doi.org/10.11591/eei.v13i6.7503
  15. Barman, S., Farid, Fahmid A., Gope, H.L., Hafiz, M.F.B., Khan, N.A., Ahmad, S., & Mansor, S., 2024. LBF-MI: Limited Boolean Functions and Mutual Information to Infer a Gene Regulatory Network from Time-Series Gene Expression Data. Genes, 15(12), p.1530. Available at: https://doi.org/10.3390/genes15121530
  16. Shern, S.J., Sarker, M.T., Haram, M.H.S.M., Ramasamy, G., Thiagarajah, S.P., Farid, Fahmid A., & others, 2024. Artificial intelligence optimization for user prediction and efficient energy distribution in electric vehicle smart charging systems. Energies, 17(22), p.5772. Available at: https://doi.org/10.3390/en17225772
  17. Muntaqim, M.Z., Smrity, T.A., Miah, A.S.M., Kafi, H.M., Tamanna, T., Farid, Fahmid A., & others, 2024. Eye disease detection enhancement using a multi-stage deep learning approach. IEEE Access, 12, pp.143824–143836. Available at: https://doi.org/10.1109/ACCESS.2024.3476412
  18. Sarker, M.T., Ramasamy, G., Farid, Fahmid A., Mansor, S., & Karim, H.A., 2024. Energy consumption forecasting: a case study on Bhashan Char island in Bangladesh. Bulletin of Electrical Engineering and Informatics, 13(5), pp.3021–3032. Available at: https://doi.org/10.11591/eei.v13i5.7561
  19. Shern, S.J., Sarker, M.T., Ramasamy, G., Thiagarajah, S.P., Farid, Fahmid A., & others, 2024. Artificial Intelligence-Based Electric Vehicle Smart Charging System in Malaysia. World Electric Vehicle Journal, 15(10), p.440. Available at: https://doi.org/10.3390/wevj15100440
  20. Ramadan, S.T., Sakib, T., Farid, Fahmid A., Islam, M.S., Abdullah, J.B., Bhuiyan, M.R., et al., 2024. Improving wheat leaf disease classification: Evaluating augmentation strategies and CNN-based models with limited dataset. IEEE Access, 12, pp.69853–69874. Available at: https://10.1109/ACCESS.2024.3397570
  21. Farid, Fahmid A., Hashim, N., Abdullah, J.B., Bhuiyan, M.R., Kairanbay, M., Yusoff, Z., et al., 2024. Single shot detector CNN and deep dilated masks for vision-based hand gesture recognition from video sequences. IEEE Access, 12, pp.28564–28574. Available at: https:10.1109/ACCESS.2024.3360857

Conferences, Talks, and Speaking Engagements

  1. Farid, Fahmid A., Karim, H.A., Bhuiyan, M.R., Badie, F., Balaganesh, D., Tusher, M.M.R., 2025. Deep Learning-Based Classification of Tomato Leaf Diseases for Precision Agriculture. In: 6th Multimedia University Engineering Conference 2025 (MECON2025) in conjunction with the Digital Futures International Congress 2025 (DIFCON2025), Multimedia University, Malaysia, 21–23 July.
  2. Farid, Fahmid A., Karim, H.A., Bhuiyan, M.R., Badie, F., Balaganesh, D., Tusher, M.M.R., 2025. Traffic Sign Classification Across Borders: Evaluating DenseNet201 on Belgium and Bangladesh Signs. In: 6th Multimedia University Engineering Conference 2025 (MECON2025) in conjunction with the Digital Futures International Congress 2025 (DIFCON2025), Multimedia University, Malaysia, 21–23 July.
  3. Bhuiyan, M.R., Abdullah, J., Hashim, N., Badie, F., Farid, Fahmid A., Uddin, J., & others, 2025. Towards Intelligent Crowd Monitoring during Hajj: A Novel Dataset for Density Estimation and Anomaly Detection in the Tawaf Area (2015–2019). In: 6th Multimedia University Engineering Conference 2025 (MECON2025) in conjunction with the Digital Futures International Congress 2025 (DIFCON2025), Multimedia University, Malaysia, 21–23 July.
  4. Bhuiyan, M.R., Badie, F., Abdullah, J., Napolitano, G., Islam, M.B., Farid, Fahmid A., 2025. Massive Crowd Pose Estimation using Deep Learning-Based Techniques. In: 6th Multimedia University Engineering Conference 2025 (MECON2025) in conjunction with the Digital Futures International Congress 2025 (DIFCON2025), Multimedia University, Malaysia, 21–23 July.
  5. Sarker, Md Tanjil, Fahmid Al Farid, Gobbi Ramasamy, Sarina Mansor, and Hezerul Abdul Karim. “An Overview of System Identification Procedures and Perturbation Signal.” In 2023 IEEE 11th Conference on Systems, Process & Control (ICSPC), pp. 282-287. IEEE, 2023.
  6. Sarker, Md Tanjil, Sarina Mansor, Fahmid Al Farid, Hezerul Abdul Karim, and Gobbi Ramasamy. “Investigation of Optimal Perturbation Signals for Multivariable System under Model Predictive Control.” In 2023 IEEE 11th Conference on Systems, Process & Control (ICSPC), pp. 304-309. IEEE, 2023.
  7. Bhuiyan, Md Roman, Junaidi Abdullah, Noramiza Hashim, and Fahmid Al Farid. “Crowd Monitoring of Hajj Pilgrimage using Video Analytics and Deep Learning.” In 2022 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), pp. 1-4. IEEE, 2022.
  8. Roman Bhuiyan, Muhammad Nur Hakim Bin Zamri , Junaidi Abdullah, Noramiza Hashim, Fahmid Al Farid, (2021) ‘Comparative Analysis of Different Machine and Deep Learning Approaches for Crowd Density Analysis Based on Hajj Pilgrimage’, 7th International Visual Informatics Conference 2021. (BEST PAPER AWARD)
  9. Fahmid Al Farid, Noramiza Hashim, Junaidi Abdullah and Md Roman Bhuiyan , “Vision based Hand Gesture Recognition: A Review” International Conference on Computer, Information Technology and Intelligent Computing (CITIC – DIFCON 2021), Malaysia
  10. Fahmid Al Farid, Noramiza Hashim and Junaidi Abdullah, “Vision-based Hand Gesture Recognition from RGB Video Data Using SVM”, IWAIT-IFMIA, NTU, Singapore, 2019 (Scopus Indexed Conference)
  11. Fahmid Al Farid, Noramiza Hashim and Junaidi Abdullah, “Hand Gesture Recognition from RGB Video Data Using Morphological Process”, MECON 2019, MMU Malaysia