Current Research Project/Collaboration

·      Associate Professor, ECE Discipline, Khulna University, Khulna, Bangladesh, August 22, 2021 - Present.

·      Assistant Professor, ECE Discipline, Khulna University, Khulna, Bangladesh, June  12, 2016 - August 21, 2021.

·      Lecturer, ECE Discipline, Khulna University, Khulna, Bangladesh, September 05, 2013 - June 11, 2016.

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Supervision

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• 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

8. Rafia 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

7. Rafia Nishat Toma, Cheol-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

6. Rafia 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 Toma, Abdullah 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

1. Rafia 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

7. Md. Nazmul Hasan, Rafia Nishat Toma, Sana Ullah Jan, and Insoo Koo, “Transfer Learning with Domain Adaptation for Unlabelled Sensor Faulty Data Classification” in 15th International Conference on Information and Communication Technology Convergence (ICTC), 16-18 October 2024, Jeju Island, Republic of Korea, DOI: 10.1109/ICTC62082.2024.10826888

6. Rafia Nishat Toma, Farzana 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

5. Md. Abdur Rahman, S. M. Shoaib, Md. Al Amin, Rafia Nishat Toma, Mohammad 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. 2019, DOI: 10.1109/ICAEE48663.2019.8975480

4. Rafia 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

3. Md 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, Bangladesh, DOI: 10.1109/ICCITECHN.2016.7860181

2. Md. 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

1. Md. Maniruzzaman, Shakil Ahmed, Galib Md. Fattah and Rafia Nishat Toma, “Estimation 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

• Digital Electronics

• Digital Electronics Sessional

• Mobile Communication Engineering

• Electrical Engineering Materials

• Electrical Circuits II

• Electrical Circuits II Sessional