It is well known that electromagnetic waves can penetrate many kinds of materials. When illuminated by electromagnetic waves, different materials will respond differently. Therefore, electromagnetic physics provides us with an essential tool for sensing and imaging. We can infer the properties of the targets under investigation from the measured electromagnetic signal. Electromagnetic sensing has been applied to hydrocarbon production, land mine detection, and many other areas since the 1920s. However, due to the limit in computing powers, researchers can only interpret the domain of investigation by directly browsing the recorded signal. Reasonable interpretation requires ample experience, but it still needs to be more accurate. In the 1970s, computers were used in data processing, and algorithms were developed to estimate the electromagnetic properties of the investigation domain from the recorded survey data. During this time, inversion algorithms could only reconstruct simple one-dimensional models with tens of unknowns based on linear approximation. Still, even so, it took a long time to compute. These days, nonlinear inversion algorithms can reconstruct three-dimensional models with millions of unknowns on high-performance computing platforms. Many new electromagnetic sensing methods were developed with these developments, such as the widely used marine-controlled source electromagnetic surveys for hydrocarbon explorations, breast cancer detection using microwaves, etc. With the help of new sensors, big data technology, massive parallelization, fast algorithms, electromagnetic sensing, and imaging has improved their effectiveness and gained more and more applications. In this talk, the presenter would like to discuss the fundamentals of electromagnetic sensing and imaging, the solution to electromagnetic inverse problems, and many practical examples from hydrocarbon exploration, radar imaging, biomedical diagnosis, non-destructive testing, etc. The presenter will discuss the challenges and new research directions for future electromagnetic sensing and imaging. Co-sponsored by: STARaCom Speaker(s): Prof. Maokun Li , Virtual: https://events.vtools.ieee.org/m/351678