Anton V. Riabov worked on multiple projects at IBM Research involving the application of AI planning, reasoning and optimization in distributed computing systems. He lead the research resulting in MARIO, an automated semantics-based flow composer with faceted goal navigation, and SPPL, a formalism for describing flow composition tasks. Currently he is working on projects that aim to simplify the development and operation of mulit-stage analytic applications in distributed runtimes and clouds for business users and data scientists, and on applying AI planning to reason with limited domain knowledge and to create hypotheses about the present and the future in accordance with noisy observations. He received his PhD degree in Operations Research from Columbia University in New York City and a degree in Computer Science from the Lomonosov Moscow State University. He received an IBM Corporate Award for the work on stream processing systems, a Master Inventor title in recognition of the value of his patents, and has over 25 publications in conferences and journals.