Today's quantum circuit designs are akin to classical circuits in their early stages, which were designed by hand and manually laid out, while the power of classical computing hardware was not fully unleashed until the emergence of Electronic Design Automation (EDA) in the 1950s, enabling the scalable design of integrated circuits. Although quantum computing holds great promise to dramatically speed up many chemical, financial, cryptographic, and machine-learning applications, we are witnessing that the existing quantum computing design workflow significantly relies on human designs, such as manually implementing and verifying quantum circuits on the gate level for quantum algorithms. As such, domain experts from other fields without a sufficient fundamental understanding of quantum operations can hardly leverage the power of quantum computers for their domain applications, and more importantly, they lack toolkits to test the correctness of an ad-hoc designed quantum circuit. Furthermore, since quantum computing has a fundamentally different computing scheme, which relies on superposition and entanglement, the traditional EDA techniques cannot be directly applied to quantum circuits. To close the gap between quantum hardware (in physics) and quantum algorithms (in computer science), we envision the necessity of a quantum EDA framework, which will play a role similar to that of EDA in revolutionizing classical Silicon-based hardware design. Beyond the technical impact, the fu