Fenix Huang has a mathematical background and has applied it to solving problems in RNA folding as well as related computational work. He has designed algorithms for RNA pseudoknot prediction, RNA-RNA interaction structures, and Boltzmann sequence samplers for single structure as well as for structure pairs. All of these developments were driven by mathematical ideas pertaining to combinatorics and topology. One of his recent works was on assessing mutational robustness of let-7 miRNA, and structural accessibility for alternative structures of riboswitches. Furthermore, he also has experience in extracting information from databases using Hidden Markov Models. He has designed stochastic context-free grammars for RNA pseudoknotted structures and used them to extract features of pseudoknots from existing databases. He is open to collaborating with researchers across multiple disciplines and fields.