29 years experience in both basic research on ML/AI algorithms/theoretical frameworks and designing practical ML/AI solutions for a large number of difficult use cases across sciences and industries - in government, academia, startup, big companies ("practical theory and theory-guided practice"). Current interests include new paradigms combining the strengths of deep learning and symbolic AI, and automating all the pragmatics of data science.