Explore advanced concentration inequalities for high-dimensional expanders (HDXs) that extend beyond classical Chernoff bounds in this 50-minute conference talk. Delve into derandomization techniques and their applications to HDXs, examining how these methods provide stronger concentration results than traditional approaches. Learn about the mathematical foundations underlying these advanced concentration phenomena and their implications for theoretical computer science and combinatorics. Discover how these techniques contribute to the broader understanding of high-dimensional expansion properties and their connections to error-correcting codes. This presentation is part of the ICTS Workshop on HDXs and Codes, bringing together cutting-edge research at the intersection of high-dimensional expanders and coding theory.