Time-Domain Explosive Transients studies and identification & classification methods in the era of big data. In the early 1990s, transient science began a dramatic revolution with the confluence of robotic telescopes, technologically mature CCDs, and cheapening computing power. These combined forces fueled an orders of magnitude increase in the number of astronomical transients observed, and helped revolutionize our understanding of the variable universe. Today, we are on the cusp of the culmination of these trends, with multi-messenger telescopes triggering wide field searches for EM counterparts, and these wide field telescopes capturing terabytes of data a night with potentially hundreds of newly discovered uncharacterized transients - the challenge is becoming finding the interesting‚ transient and getting the right telescopes, and the right observations, on them. My primary research interests revolve around using these burgeoning multi-wavelength observations of astronomical transients to understand the progenitors, and oftentimes-extreme physics, that drive them. Current and previous research has included: Fast Evolving Transients and progenitors of stripped-envelope supernovae, Fast, or early, transients & multi-messenger astrophysics - ML for identification and classification in survey data streams, data-driven training set creation using multi-dimensional gaussian process modeling of objects, mission concept development for future TDAMM missions.