Lecturer: Applied Mathematics and Machine Learning Coordinator: Rhodes AI Research Group (RAIRG), Rhodes University, South Africa

(046) 603 7447

Research Interest

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

Supervision

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.

Students (Graduated)

• 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

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)

Awards

• 2019: ()Deep Learning Indaba) Kambule Doctoral Award
• 2013: (SKA SA) best poster award

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