Atlas Wang

Atlas Wang, a faculty member at UT Austin and research director at XTX Research, dives into the captivating realms of symbolic AI and quantitative finance. He unveils how neural networks can learn symbolic equations through gradient descent, challenging our understanding of AI reasoning. In finance, he demystifies high-frequency trading’s complexities, highlighting the struggle against market noise and the pursuit of predictive accuracy. Atlas advocates for robust time-series models and suggests that researchers should explore finance for the unique opportunities it presents.