Daniel Furman (M.Sc.)

Daniel graduated from the University of Idaho with a Master's degree in Applied Mathematics with a focus on Artificial Intelligence (AI) and Machine Learning (ML). He is an expert in AI modeling, data imputation, and Machine Learning. During his academic career, Daniel developed novel clustering algorithms that improve the denoising process in autoencoder imputation. He has built multiple advanced AI and ML solutions for public and private sector companies.