This paper presents a method combining stochastic resetting (SR) with metadynamics (MetaD) to accelerate molecular dynamics simulations. MetaD is a powerful technique for enhancing sampling in simulations, but its efficiency depends on the quality of collective variables (CVs) used. SR is a simple method that can restart stochastic processes at random intervals, leading to faster simulations. The study shows that combining SR with MetaD can lead to greater acceleration than either method alone. It also demonstrates that SR can improve the performance of MetaD simulations with suboptimal CVs, making it a viable alternative to improving CVs. The method is tested on various systems, including a two-wells model, the modified Faradjian-Elber potential, alanine tetrapeptide, and chignolin in water. The results show that SR can significantly speed up simulations while maintaining accuracy. Additionally, the study proposes a method to infer unbiased kinetics from MetaD simulations with SR, improving the trade-off between speedup and accuracy. The findings suggest that combining SR with MetaD can be a valuable tool for accelerating a wide range of molecular simulations.This paper presents a method combining stochastic resetting (SR) with metadynamics (MetaD) to accelerate molecular dynamics simulations. MetaD is a powerful technique for enhancing sampling in simulations, but its efficiency depends on the quality of collective variables (CVs) used. SR is a simple method that can restart stochastic processes at random intervals, leading to faster simulations. The study shows that combining SR with MetaD can lead to greater acceleration than either method alone. It also demonstrates that SR can improve the performance of MetaD simulations with suboptimal CVs, making it a viable alternative to improving CVs. The method is tested on various systems, including a two-wells model, the modified Faradjian-Elber potential, alanine tetrapeptide, and chignolin in water. The results show that SR can significantly speed up simulations while maintaining accuracy. Additionally, the study proposes a method to infer unbiased kinetics from MetaD simulations with SR, improving the trade-off between speedup and accuracy. The findings suggest that combining SR with MetaD can be a valuable tool for accelerating a wide range of molecular simulations.