Dr. Rafia Nishat Toma
Associate Professor

·      Ph.D. in Information Technology, Department of Electrical, Electronic and Computer Engineering, University of Ulsan, South Korea (2019-2023).

·      M.Sc. Engg., Electronics and Communication Engineering, Khulna University, Khulna, Bangladesh (2013-2016).

·      B.Sc. Engg., Electronics and Communication Engineering, Khulna University, Khulna, Bangladesh (2008-2012).

·      Research on condition monitoring of engineering systems using signal processing and ML/DL-based techniques.

·      Developing the solutions for fault feature extraction and fault detection and classification in engineering systems.

·      Antenna and Wave Propagation.

Current Research Project/Collaboration

SL Title Research Role Awarded Date Completion Date Funding Agency
1 "Jogott”: An Array of Artificial Intelligence Enabled Solutions for Diagnosis, Monitoring, and Intervention of Children with Autism Spectrum Disorder Principal Investigator 01 October, 2023 National

·      Associate Professor, ECE Discipline, Khulna University, Khulna, Bangladesh, April 12, 2023 - Present.

·      Assistant Professor, ECE Discipline, Khulna University, Khulna, Bangladesh, July 26, 2016 - April 11, 2023.

·      Lecturer, ECE Discipline, Khulna University, Khulna, Bangladesh, September 05, 2013 - July 25, 2013.

coming soon...


SL Title Degree Role Start Date End Date
No Supervision Available

coming soon...

    • Journal Articles

12. Rafia Nishat Toma, Yangde Gao, Farzin Piltan, Kichang Im, Dongkoo Shon, Tae Hyun Yoon, Dae-Seung Yoo, and Jong-Myon Kim, “Classification Framework of the Bearing Faults of an Induction Motor Using Wavelet Scattering Transform-Based Features”, Sensors 2022, 22(22), 8958; https://doi.org/10.3390/s22228958

11. Rafia Nishat Toma, Farzin Piltan, Kichang Im, Dongkoo Shon, Tae Hyun Yoon, Dae-Seung Yoo, and Jong-Myon Kim, “A Bearing Fault Classification Framework Based on Image Encoding Techniques and a Convolutional Neural Network under Different Operating Conditions”, Sensors 2022, 22(13), 4881; https://doi.org/10.3390/s22134881

10. Abdullah-Al Nahid, Niloy Sikder, Mahmudul Hasan Abid, Rafia Nishat Toma, Iffat Ara Talin, Lasker Ershad Ali, " Home Occupancy Classification Using Machine Learning Techniques along with Feature Selection ", International Journal of Engineering and Manufacturing (IJEM), Vol.12, No.3, pp. 38-50, 2022. DOI: 10.5815/ijem.2022.03.04

9. Farzin Piltan, Rafia Nishat Toma, Dongkoo Shon, Kichang Im, Hyun-Kyun Choi, Dae-Seung Yoo, Jong-Myon Kim, “Strict-Feedback Backstepping Digital Twin and Machine Learning Solution in AE Signals for Bearing Crack Identification”, Sensors 2022, 22(2), 539.  https://doi.org/10.3390/s22020539

8Rafia Nishat Toma, Farzin Piltan, and Jongmyon Kim, “A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors”, Sensors 2021, 21(4), 8453; https://doi.org/10.3390/s21248453

7Rafia Nishat TomaCheol-Hong Kim and Jong-Myon Kim, “Bearing Fault Classification Using Ensemble Empirical Mode Decomposition and Convolutional Neural Network”, Electronics 2021, 10(11), 1248; https://doi.org/10.3390/electronics10111248

6Rafia Nishat Toma and Jong-Myon Kim“Bearing Fault Classification of Induction Motors Using Discrete Wavelet Transform and Ensemble Machine Learning Algorithms”, Appl. Sci. 2020, 10(15), 5251; https://doi.org/10.3390/app10155251 

5. Rafia Nishat Toma, Alexander E. Prosvirin and Jong-Myon Kim, “Bearing Fault Diagnosis of Induction Motors Using a Genetic Algorithm and Machine Learning Classifiers”, Sensors 2020, 20(7), 1884; https://doi.org/10.3390/s20071884

4. Md Nazmul Hasan, Rafia Nishat TomaAbdullah Al Nahid, MMM Islam, Jong-Myon Kim, "Electricity Theft Detection in Smart Grid Systems: A CNN-LSTM Based Approach", Energies 2019, 12(17),3310; https://doi.org/10.3390/en12173310 

3. Rafia Nishat Toma, Imtiaj Ahmmed Shohagh, Md Nazmul Hasan, “Analysis the effect of Changing Height of the Substrate of Square Shaped Microstrip Patch Antenna on the Performance for 5G Application” in International Journal of Wireless and Microwave Technologies (IJWMT), Vol. 9, No. 3, pp. 33-45, 2019, DOI: 10.5815/ijwmt.2019.03.04

2. Rafia Nishat Toma, Md. Maniruzzaman, Om Prakash Panjiyar, Md. Mahmud Hassan, Md. Nazmul Hasan, Md. Atiqur Rahman, “Analysis of Crosstalk Noise for 2π RC Model considering Interconnect Parameters in Deep Submicron VLSI Circuit” in Journal of Telecommunication, Electronic and Computer Engineering, Vol 11, No 1, pp 49-55, 2019.  https://jtec.utem.edu.my/jtec/article/view/4646

1. Md. Maniruzzaman , Alok Sarker, Rafia Nishat Toma, Md. Tariq Hasan, “Estimation of Crosstalk Noise for 2pi  RC and RLC Interconnects in Deep Submicron VLSI Circuits” in International Journal of Engineering Research and Development, Volume 11, Issue 10, PP.16-27, October 2015. https://www.ijerd.com/paper/vol11-issue10/Version_1/C11101627.pdf

    • Book Chapters

4. Rafia Nishat Toma, Yangde Gao, Jong-Myon Kim, “Data-Driven Fault Classification of Induction Motor Based on Recurrence Plot and Deep Convolution Neural Network”, in Frontiers in Artificial Intelligence and Applications Ebook: Volume 360: Machine Learning and Artificial Intelligence, page: 64 – 71, November 2022. https://ebooks.iospress.nl/doi/10.3233/FAIA220425

3. Yangde Gao, Farzin Piltan, Zahoor Ahmad, Rafia Nishat Toma, Jong-Myon Kim, “A Novel Fault Diagnosis Method Based on MADCNN for Rolling Bearings”, in Frontiers in Artificial Intelligence and Applications Ebook: Volume 360: Machine Learning and Artificial Intelligence, page: 56 - 63, November 2022. https://ebooks.iospress.nl/doi/10.3233/FAIA220424

2. Rafia Nishat Toma and Jong-Myon Kim(2022). "Bearing Fault Classification of Induction Motor Using Statistical Features and Machine Learning Algorithms". In: Abraham, A., Gandhi, N., Hanne, T., Hong, TP., Nogueira Rios, T., Ding, W. (eds) Intelligent Systems Design and Applications. ISDA 2021. Lecture Notes in Networks and Systems, vol 418. Springer, Cham. https://doi.org/10.1007/978-3-030-96308-8_22

1Rafia Nishat Toma and Jong-Myon Kim, Induction Motor Bearing Fault Diagnosis Using Statistical Time Domain Features and Hypertuning of Classifiers. In: Park J.J., Fong S.J., Pan Y., Sung Y. (eds) Advances in Computer Science and Ubiquitous Computing. Lecture Notes in Electrical Engineering, vol 715. Springer, Singapore, (2021).  https://doi.org/10.1007/978-981-15-9343-7_35

    • Conference Proceedings

6. Rafia Nishat TomaFarzana Haque Toma, and Jongmyon Kim“Comparative Analysis of Continuous Wavelet Transforms on Vibration signal in Bearing Fault Diagnosis of Induction Motor” in International Conference on Electronics, Communications and Information Technology (ICECIT), 14–16 September 2021, Khulna, Bangladesh, DOI: 10.1109/ICECIT54077.2021.9641199

5Md. Abdur Rahman, S. M. Shoaib, Md. Al Amin, Rafia Nishat TomaMohammad Ali Moni, Md. Abdul Awal, "A Bayesian Optimization Framework for the Prediction of Diabetes Mellitus" in 5th International Conference on Advances in Electrical Engineering (ICAEE), 26-28 Sept. 2019DOI: 10.1109/ICAEE48663.2019.8975480

4Rafia Nishat Toma, Md Nazmul Hasan, Abdullah Al-Nahid, Bo Li, “Electricity Theft Detection to Reduce Non-Technical Loss using Support Vector Machine in Smart Grid” in International Conference on Advances in Science, Engineering and Robotics Technology 2019 (ICASERT – 2019), 3-5 May 2019, East-West University, Dhaka, Bangladesh. 10.1109/ICASERT.2019.8934601

3Md Younus Ali, S.M. Jillur Rahman, Kaniz Fatema Keya, Sudipto Adhikary and Rafia Nishat Toma, “Numerical Study of Usefulness of Parabolic Index Profile for the  Design of Erbium Doped Fiber Lasers and Amplifiers” in 19th International Conference on Computer and Information Technology (ICCIT 2016), December 18-20, 2016, North South University, Dhaka, BangladeshDOI: 10.1109/ICCITECHN.2016.7860181

2Md. Nazmul Hasan, Md. Tariq Hasan, Rafia Nishat Toma, Md. Maniruzzaman, FPGA Implementation of LBlock Lightweight Block, in 3rd International Conference on Electrical Engineering and Information Technology (ICEEICT 2016), September 22-24, 2016, Military Institute of Science and Technology (MIST), Mirpur, Dhaka, Bangladesh, DOI: 10.1109/CEEICT.2016.7873062

1Md. Maniruzzaman, Shakil Ahmed, Galib Md. Fattah and Rafia Nishat TomaEstimation of Crosstalk Noise for RLC Interconnects in Deep Submicron VLSI Circuit” in 2nd International Conference on Electrical Engineering and Information & Communication Technology (ICEEICT 2015), May 21-23, 2015, Jahangirnagar University, Dhaka, Bangladesh, DOI: 10.1109/ICEEICT.2015.7307503

Mobile Communication Engineering

This course is designed to provide the fundamental knowledge and latest trend in mobile communications and their applications. It will also provide basic concept on functioning of wireless communication system and evolution of different wireless communication systems and standards.


Electrical Engineering Materials

This course is designed to provide a basic understanding of the electric and magnetic properties of materials used in electrical engineering.


Electrical Circuits II

This is the basic and essential course for students to develop the fundamental skills on resonance, filters, transients, coupled circuits, poly-phase circuits and magnetic circuits.


Electrical Circuits II Sessional

This course is designed to develop hands-on skills in transients, passive filters, coupled circuits, poly phase circuits, and magnetic circuits.

  • Mobile Communication Engineering
  • Electrical Engineering Materials
  • Electrical Circuits II
  • Electrical Circuits II Sessional