Bio

My work focuses on robotic remote control and manipulation systems utilizing reinforcement learning (RL). The research centers on developing RL-based algorithms that enable robots to learn optimal control strategies for tasks such as navigation, object manipulation, and interaction within dynamic environments. By training robots through iterative trial-and-error processes, these systems continuously improve performance, adapt to new situations, and enhance autonomous control. The broader goal is to achieve more efficient, precise, and scalable robotic behavior in real-world applications.

In parallel, I have over seven years of experience in investment and asset management. I lead 280 Capital, a family-backed investment office overseeing more than $1 billion across digital assets and emerging technologies.

My technical background spans artificial intelligence, enterprise storage systems, encryption, and large-scale computing infrastructure. I contributed to the design of next-generation enterprise SSD controller and storage system chips ranging from 16nm to 7nm at Broadcom and SK Hynix. At Roche, I led the construction and optimization of large-scale biodata software and hardware architectures supporting advanced DNA sequencing and scalable computational biology workloads. I also hold multiple U.S. patents related to improving storage and computing efficiency through deep learning, AI, and advanced systems design.