MSc (Cameroon), PhD (Rhodes)
Room 19 Maths Building (Drostdy Lodge)
(046) 603 7447
- (MAT1 S, year 1): Mathematics for Science
- (MAM 101, year 1): Algebra
- (MAM 2, year 2): Mathematical Programming with Python
- (MAP 311, year 3): Numerical Analysis
- (Applied Mathematics Honours, year 4): Machine learning & deep learning
I work closely with the South African Radio Astronomy Observatory (SARAO or SKA SA) based in Cape Town and I am part of Rhodes Centre for Radio Astronomy Techniques & Technologies based in the Department of Physics and Electronics, Rhodes University. I am coordinating the Rhodes AI Research Group (RAIRG) based in the Department of mathematics. My research interests are in big data analysis, signal processing, artificial intelligence, radio interferometry / astronomical techniques. Send me a cover letter in which you explain why you would like to work with me for your honors, masters, doctorate, or post-doctorate. Also include academic transcripts in the request for supervision. Click here for more details.
- 2018: Radio Interferometry: from the measurements to the image, AMI BAKHIT, AIMS MSc in Mathematical Sciences
- 2019: Using dimensionality reduction techniques for radio interferometric big data compression, EM SECK, AIMS MSc in Data Science, with Distinction.
- 2019: Prediction of Fuel Consumption using Machine Learning, GM Nguegnang, AIMS MSc in Data Science.
- 2019: Anomaly Detection in Power Generation Plants Using Machine Learning and Neural Networks, J Mulongo, AIMS MSc in Data Science.
- 2020: Hybrid Architecture for Long Short-Term Memory and Autoregressive, ST Sari, AIMS MSc in Data Science.
- 2020: A Comparison of Conventional and Deep Learning Methods for Detecting Pneumonia on Chest X-rays with Transfer Learning, JE Mossoun, AIMS MSc in Data Science.
- 2020: Deep Learning in the Morphological Classification of Radio Galaxies, B. Strelitz, RU Honours project, with Distinction
- BDA/BDWF & Distributed Gridding Pilot (2019-current), S Masoka, RU MSc (co-supervising with Prof Oleg Smirnov)
- Segregating Radio Sources Automatically (2019-current), R Kupa, RU MSc (co-supervising with Prof Oleg Smirnov)
- Deep Compression Models with Application in Medicinal Plants (2020-current), A Deyi, RU MSc
- A Transfer Learning approach for credit card fraud detection (2020-current), S Hamlomo, RU MSc (co-supervising with Mr Jeremy Baxter)
- Animal Detection and Warning Systems in South African Highway (2020-current), I Nandutu, RU PhD
- Mathematical Methods for Supervised Learning Process with Application in Face Recognition (2020-2023), G M Gouaya, UNISA PhD (co-supervising with Prof EF Doungmo Goufo)
- Big data analytics
- Signal processing
- Artificial Intelligence
- Radio Interferometry/Astronomical Techniques
- Atemkeng, M., Perkins, S., Kenyon, J., Hugo, B. and Oleg Smirnov (2021). Xova: Baseline-Dependent Time and Channel Averaging for Radio Interferometry, Proceedings of the Astronomical Data Analysis Software and Systems (ADASS) conference
- Atemkeng, M., Smirnov, O., Tasse, C., Foster, G., & Makhathini, S. (2020). Fast algorithms to approximate the position-dependent point spread function responses in radio interferometric wide-field imaging. Monthly Notices of the Royal Astronomical Society.
- Fountsop, A. N., Ebongue Kedieng Fendji, J. L., & Atemkeng, M. (2020). Deep Learning Models Compression for Agricultural Plants. Applied Sciences, 10(19), 6866.
- Tchakounté, F., Faissal, A., Atemkeng, M., & Ntyam, A. (2020). A Reliable Weighting Scheme for the Aggregation of Crowd Intelligence to Detect Fake News. Information, 11(6), 319.
- Cotton, W.D., Thorat, K., Condon, J.J., Frank, B.S., Józsa, G.I.G., White, S.V., Deane, R., Oozeer, N., Atemkeng, M., Bester, L. and Fanaroff, B. (2020). Hydrodynamical backflow in X-shaped radio galaxy PKS 2014− 55. Monthly Notices of the Royal Astronomical Society, 495(1), pp.1271-1283.
- Mulongo, J., Atemkeng, M., Ansah-Narh, T., Rockefeller, R., Nguegnang, G. M., & Garuti, M. A. (2020). Anomaly Detection in Power Generation Plants Using Machine Learning and Neural Networks. Applied Artificial Intelligence, 34(1), 64-79.
- Shimwell, T. W., et al. (2019). The LOFAR Two-metre Sky Survey-II. First data release. Astronomy & Astrophysics, 622, A1.
- Tasse, C., Hugo, B., Mirmont, M., Smirnov, O., Atemkeng, M., Bester, L., ... & Shimwell, T. (2018). Faceting for direction-dependent spectral deconvolution. Astronomy & Astrophysics, 611, A87.
- Atemkeng, M., Smirnov, O., Tasse, C., Foster, G., Keimpema, A., Paragi, Z., & Jonas, J. (2018). Baseline-dependent sampling and windowing for radio interferometry: data compression, field-of-interest shaping, and outer field suppression. Monthly Notices of the Royal Astronomical Society, 477(4), 4511-4523.
- Atemkeng, M. T., Smirnov, O. M., Tasse, C., Foster, G., & Jonas, J. (2016). Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry. Monthly Notices of the Royal Astronomical Society, 462(3), 2542-2558.
- Zarka, P., Tagger, M., Denis, L., Girard, J. N., Konovalenko, A., Atemkeng, M., ... & Boone, F. (2015, April). NenUFAR: Instrument description and science case. In 2015 IEEE International Conference on Antenna Theory and Techniques (ICATT), pp. 1-6.
Others (refereeing, community engagements, etc.)
- I served as a reviewer for the NRF grants (Chairs), journals, and conferences including SAICSIT, International Conference on Learning Representations, AI for Social Good, Black in AI, International Conference on Artificial Intelligence and Statistics
- I have served as an external examiner for five MSc theses and 1 PhD
- I have been invited as a keynote speaker in several national and international conferences and workshops
Last Modified: Wed, 03 Mar 2021 09:26:03 SAST