Rhodes>Mathematics>People>Staff>Marcel Atemkeng

Marcellin Atemkeng

Senior Lecturer

MSc (UDS), Ph.D. (Rhodes), PGDHE (Rhodes)


Room 10 Maths Building (Drostdy Lodge)

(046) 603 7447


  • (MAT1 S, year 1): Mathematics for Science
  • (MAM 101, year 1): Algebra and analysis
  • (MAM 101, year 1): Calculus
  • (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 a fellow of the DHET Future Professors Programme (FPP). I am coordinating the Rhodes AI Research Group (RAIRG) based in the Department of mathematics. My research interests are in big data analysis, statistical 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 honour, MSc, PhD, or post-doctorate. Also include academic transcripts in the request for supervision.  Click here for more details.

Students (Graduated)

Students (Current)

    • 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)

Research interests

  • Big data analytics
  • Statistical Signal processing
  • Artificial Intelligence
  • Radio Interferometry/Astronomical Techniques

Selected publications [publications google scholar]

  • 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 Sciences10(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. Information11(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 Society495(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 Intelligence34(1), 64-79.
  • Shimwell, T. W., et al. (2019). The LOFAR Two-metre Sky Survey-II. First data release. Astronomy & Astrophysics622, A1.
  • Tasse, C., Hugo, B., Mirmont, M., Smirnov, O., Atemkeng, M., Bester, L., ... & Shimwell, T. (2018). Faceting for direction-dependent spectral deconvolution. Astronomy & Astrophysics611, 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 Society477(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 Society462(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: Sat, 18 Mar 2023 11:40:36 SAST