My primary research interests lie in the applications of probabilistic and statistical methods in biology and physical science, particularly in Uncertainty Quantification, Bayesian Methods, and Sampling Methods.
During my undergraduate, I tried to use stochastic models to give insight into biochemical networks and corresponding phenomena, for example, HIV latency.
Now I’m focusing on developing efficient statistical algorithms for inferences, emulations, and model calibration.
Publication:
[1] Xiaolu Guo, Tao Tang, Minxuan Duan, Lei Zhang, Hao Ge. The nonequilibrium mechanism of noise-enhanced drug synergy in HIV latency reactivation. Iscience, 2022 – Elsevier arXiv link [link]
[2] Bayesian spectrum inference and low-rank approximation of continuous-time Markov chain (CTMC). in preparation
[3] Adaptive Bayesian Regression on Data with Low Intrinsic Dimension. in preparation
[4] Tao Tang, Simon Mak, and David Dunson. Hierarchical shrinkage Gaussian processes for emulation and dynamical recovery. submitted [link]
[5] Chih-li Song, Irene Ji Yi, Tao Tang, and Simon Mak. Stacking designs: designing multi-fidelity computer experiments with confidence. submitted arXiv:2211.00268 [link]
[6] Omar Melikechi, Alex Young, Tao Tang, Trevor Bowman, James Johndrow, and David Dunson. Limits of epidemic prediction using SIR models. Journal of Mathematical Biology 85 (4), 36; 2022; arXiv link [link]
