Globally, there is a rise in technological advancement exponentially where the main focus is to minimize the human efforts which can be achieved with AI. Human perception of viewing the entities may involve biasedness which is reflected in models formally termed Cognitive Bias since human intervention exists with mind components. The concept of cognitive bias and its impact on various research domains is illustrated and presented. Formally, cognitive science components of bias knowledge are defined, emphasizing its unconscious impact on the prediction of human judgment and analysis of decision-making. It then highlights various research fields which include cognitive science, perception, and forensic science, acknowledging and addressing cognitive bias in their approaches. Large Language Models (LLMs) are susceptible to cognitive bias, and study and analysis on how researchers are modelling approaches for detection and mitigation. Different research fields like fact-checking and perception studies grapple with cognitive bias. Finally, the study focuses on the significant challenges of cognitive bias in research, including hypothesis bias, selection bias, availability heuristic, hindsight bias and groupthink. The paper concludes by emphasizing the importance of recognizing and mitigating cognitive bias for achieving robust and reliable research outcomes.