In this talk, I will discuss my research and teaching over the last 20 years in applied econometrics, causal inference, deep learning, and physics, and briefly highlight some of my main research achievements. With a background in physics, statistics, and economics, I will explain how my expertise in statistical software and tools can benefit the NIPS community and how it aligns with my current research and technical interests. Data have become more abundant and more diverse in format, both at NIPS and in rneuroscience and physiology more broadly. In this context, I will briefly discuss how modern analytical frameworks can serve as a starting point for new research and for finding patterns and causal connections that go well beyond the scope of classical statistical tools.