Freelance data scientist.
I am passionate about a lot of interesting technologies, unfortunately there are only 24 hours in a day. With the constraint of time, I have chosen to focus on few things:
- Artificial intelligence (AI) and deep learning
- Blockchain, digital currencies, and their connection to AI
- Finance and its connection to AI
I work by a simple principle, “understand concepts and explain them even clearer”.
Besides AI, I like eating quality food (I hate cooking though). My bosom friend and I have created a community-driven platform that links hungry African food lovers to excellent home cooks. If you interesting in the Afro cuisine, visit us here.
What keeps me going is my precious three-year-old mini-me who challenges me in many ways. Unlike AI models that need millions of pictures to make a correct identification, my son only needs to see a picture of a family member once and recognizes them correctly in all subsequent pictures. He is bright and learns faster than any AI (I am kidding, he is incomparable)
Contact me
Tel: +32471600750 chamberlain.mbah.f@gmail.com
Selected publications
C Mbah, J De Neve, O Thas. High dimensional prediction of binary outcome in the presence of between-study heterogeneity. Statistical Methods in Medical Research (in press).
C Mbah, K De Ruyck, S De Schrijver, C De Sutter, K Schiettecatte, C Monten, L Paelinck, W De Neve, H Thierens, C West, G Amorim, O Thas & L Veldeman (2018).
A new approach for modeling patient overall radiosensitivity and predicting multiple toxicity endpoints for breast cancer patients*. Acta Oncologica, 57:5, 604-612, DOI: 10.1080/0284186X.2017.1417633
C Mbah, H Thierens, O Thas, J De Neve, J Chang-Claude, P Seibold, A Botma, C West. Pitfalls in Prediction Modeling for Normal Tissue Toxicity in Radiation Therapy: An Illustration With the Individual Radiation Sensitivity and Mammary Carcinoma Risk Factor Investigation Cohorts. Int J Radiat Oncol Biol Phys. 2016 Aug 1;95(5):1466-1476. doi: 10.1016/j.ijrobp.2016.03.034. Epub 2016 Apr 1.
C Mbah, K Peremans, S Van Aelst, DF Benoit. Robust Bayesian seemingly unrelated regression model. Computational Statistics . 2019.