Tao Huang is an electronics engineer with 12 years of experience at the intersection of high-energy physics, firmware development, and detector DAQ systems. He holds a PhD in Physics from Texas A&M and has led firmware and trigger algorithm upgrades for CMS at CERN, work that earned a CMS achievement award. Comfortable across C++, Python, Verilog and FPGA toolchains (Xilinx Virtex-6), he has contributed to the widely used CMS Offline Software, improving CSC trigger primitive algorithms. Currently designing precision timing detectors and DAQ tools at Rice University, he pairs hands-on hardware/firmware engineering with large-scale data analysis using machine learning. Tao is actively bridging ML and FPGA acceleration, aiming to deploy ML-augmented trigger and timing solutions for next-generation collider experiments. An uncommonly practical researcher, he builds both the firmware and the C++/Python test-stands that prove it in the lab.
12 years of coding experience
10 years of employment as a software developer
Bachelor of Science - BS, Physics, Bachelor of Science - BS, Physics at University of Science and Technology of China
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at Texas A&M University
Contributions:5 reviews, 56 commits, 8 PRs in 8 years 5 months
Contributions summary:Tao's contributions focus on the L1Trigger/CSCTriggerPrimitives package within the CMS Offline Software repository. They have primarily made changes to the CSCMotherboard and CSCCathodeLCTProcessor classes, which involve implementing or modifying trigger logic and high multiplicity bits. The user has also touched other classes like CSCAnodeLCTProcessor, CSCTMBHeader2020_GEM, and CSCTMBHeader2020_CCLUT, showcasing expertise in the trigger primitive algorithms. These commits suggest a focus on improving the performance and functionality of the CSC trigger system.
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