The surface-associated growth of microbial populations / communities has been revealed as the most ubiquitous lifestyle of microorganisms, which is usually referred to as biofilm. In biofilms, cells are encased within a self-produced matrix of extracellular polymeric substances (EPS). Biofilm matrix is highly structurally and physicochemically heterogeneous. The EPS matrix enhances bacterial tolerance to environmental stresses and mechanical and metabolic stability, rendering biofilms a promising workhorse in industrial applications. However, the heterogeneity of biofilm structures and metabolic activities together with uncontrollable biofilm dispersal poses a great challenge to the industrial application of biofilm-based bioprocesses. To enable the control of biofilm-based processes, this project is designed and organized to develop a platform towards controllable and reproducible biofilm development and biofilm-based bioprocesses. In this work, we demonstrated the concept of biofilm mimics supported by hydrogel matrix and evaluated the effects on cells by the artificial matrix in protein level. And we explored the potential of matrix functionalization by introducing signaling or functional molecules in the hydrogel matrix. Further, we designed a new device which was able to generate controllable and reproducible chemical gradients for biofilm development. Taken together, we successfully established the platform towards the reproducible and controllable biofilms and biofilm-based bioprocesses. First, by using hydrogel as artificial matrix, we developed biofilm mimics and elucidated the responses of bacterial cultures to the artificial entrapment. Using calcium-alginate as a model hydrogel matrix and Shewanella oneidensis as a model organism, bacterial colonies were developed within the artificial matrix. The growth, surface properties and protein expression of the biofilm mimics were evaluated, in comparison with the flow cell biofilms developed by the same strain. Briefly, there were no significant differences regarding both growth and surface properties. The proteomic analysis provided basic information on bacterial activities, such as ion uptake, energy metabolism and eDNA synthesis, advancing the understanding on bacterial responses to the artificial matrix and to the microenvironments provided by the matrix. This study showed the great potential to utilize the bacterial populations / communities developed within the artificial matrix as an alternative to flow cell biofilms. To better regulate the performance of hydrogel matrix supported biofilm mimics, we explored two approaches: (1) regulation through cell communication systems and (2) mediation through environmental chemical cues. And to better understand biofilm mimics-based responses to the regulation approaches, we explored and optimized the method of high quality RNA extraction from biofilm mimics for downstream transcriptomic analysis. Further, we investigated the responses of biofilm mimics to synthesized quorum sensing molecules using Pseudomonas aeruginosa and its mutated strain as model organism through transcriptomic analysis. We compared the quorum sensing regulated genes in biofilm mimics to those reported in biofilms, facilitating the understanding of QS regulation in the artificial matrix. To study biofilm mimics responses to highly dynamic environmental cues, we developed a high throughput platform of fluidic chamber which can generate defined and reproducible chemical gradients. We explored the application of this device in the biofilm development study using S. oneidensis as model organism, showing the biofilm formation trend along chemical gradients in the chamber. Meanwhile, we showed the great potential to study biofilm communities by using this gradient-generator flow cell system with two strains of Commamonas testosteroni as model organisms. Furthermore, this chamber can be integrated with the artificial matrix to generate reproducible external signals for biofilm mimics regulation, which will be explored in future work. Doctor of Philosophy (IGS)