Twinning-induced plasticity (TWIP) and transformation-induced plasticity (TRIP) alloys can encourage uniform plastic deformation and avoid early necking in metal systems. Being able to control these phenomena allows achieving a high stiffness and/or a targeted balance between strength and ductility. Such high stiffness and strength materials can be utilized for energy saving, energy absorption, and biomedical applications. These alloys generally are capable of high stress and strain rate absorption thanks to the evolution of twins and dislocations during deformation as well as phase transformation that may occur when loading is applied. High entropy alloys (HEAs) and stainless steels (SS) are among high demand alloys in such applications. The focus of this thesis is an investigation of the TWIP/TRIP mechanisms at the nano-scale using molecular dynamics (MD) simulation to provide in-situ microstructural characterization during deformation. For this purpose, two well-known HEAs (AlCrCoFeCuNi and CoNiCrFeMn) with both TWIP and TRIP mechanisms and FeCrNi SS dominated with the TWIP mechanism were selected. AlCrCoFeCuNi HEA with a dual phase BCC/FCC microstructure resulting from defined solidification conditions was examined. The tensile/compression results and the corresponding plastic deformation mechanisms were discussed in detail. The solidified Fe-Cr-Ni FCC single phase system with a chemical composition close to SS 316L was characterized with regard to understanding the plastic deformation mechanisms. The last part of this study focused on the assessment of a well-known single phase FCC TWIP/TRIP HEA (equiatomic CoNiCrFeMn) using a combined MD and machine learning assisted high throughput simulation for optimal alloy design. The focus of this alloy design work was tuning the alloy chemical composition with a view to having a more optimal combination of higher sustainability and mechanical properties compared with the equiatomic system. From this work, two new alloys were proposed and their deformation mechanisms during loading were investigated via MD simulation.