The use of algae in biofuel production is more sustainable as compared to crop-based resources as it doesn't compromise food security, rainforests, or arable land. Furthermore, the utilization of molecular biology methods such as CRISPR/Cas9 with guided RNA for genetic modification in algae has opened up new avenues to meet the future energy demand. Recently, a progressive shift in the paradigm of algal growth from an open system (raceways) to a closed system (e.g.; PBRs) has been observed because the latter is more efficient in biofuel production as it provides optimized growth conditions. Several algal species have been genetically engineered and characterized for different parameters, especially their ability to grow in a closed system. Since the advent of the closed system viz. fermenters for industrial applications, several advancements have been made in its design and functions to optimize the growth of industrially used microbial strains and the yield of their bio-products. Genetically engineered algae have diverse growth condition requirements varying even at strain levels, consequently, an enormous amount of significant information or data is available on the optimization of algal growth conditions in PBRs. In conjunction with different computational biological approaches, the high throughput analysis of data becomes fast, enabling to predict the scale-up production process and capital cost and investment requirements. Systematic and planned, altogether applications of genetic engineering, PBRs, and computational approaches should not only help to make the production of fourth-generation biofuels more convenient but also pave the way of different interdisciplinary approaches to be used in algal biofuel production processes in near future.