With the advent of modern hardware, parallelism has been more important than ever, and top-tier conference papers reporting performance results are rarely run sequentially. Parallel algorithms have been extensively studied since the 1970s, so what's new and still needs to be explored? In this talk, the speaker argues that there are still numerous important directions to investigate. He will briefly overview some of his recent work on graph analytics (SSSP, connectivity, k-core, etc.), data structure design (search trees, priority queues, kd-trees, etc.), and highlight ongoing challenges such as space-efficiency, synchronization costs, and the need for simplicity.