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Biography
(只提供英文版)

  • Associate Professor in School of Computing and Data Science at The University of Hong Kong
  • Research interests include the design and analysis of algorithms, with a focus on the role of information and its flip side, uncertainty. Prof. Huang is interested in algorithms for sequential decision-making under uncertainty (online algorithms), learning based on different forms of information (learning theory), incentivizing self-interested agents to share private information (mechanism design), and disclosing one kind of information while keeping the other confidential (differential privacy).
  • RFS project — in modern digital economies, companies such as online advertising platforms, ride-hailing services, and cloud computing providers face significant challenges in resource allocation due to the uncertainty of future demand. This project will address these challenges by developing a unified theory for data-driven online resource allocation.
  • Awards and Honours:
    • RGC Research Fellow (2025)
    • Excellent Young Scientists Fund (HK & Macau) (2021)
    • Best Paper Awards of ESA 2024, FOCS 2020, SPAA 2015
    • Early Career Award (2014)
    • Morris and Dorothy Rubinoff Dissertation Award (2013)

Project Title
(只提供英文版)

  • Data-driven Online Resource Allocation: From Theory to Algorithms

赞词

为表彰黄志毅教授在理论计算机科学领域的基础研究贡献,研究资助局(研资局)特授予其「研资局研究学者」荣誉奖项,以支持其关于「数据驱动的在线资源分配理论与算法」的专项研究。

 

黄教授领导的香港大学研究团队长期致力于探索信息作为计算资源的潜力,并发展不确定性下的优化理论。其研究成果包括建立非线性在线优化的算法理论、提出最优拍卖机制所需数据量的样本复杂度理论,以及解决在线匹配市场序贯决策中多个开放性问题。相关研究成果曾荣获ESA 2024、FOCS 2020及SPAA 2015等多项国际顶级会议最佳论文奖。

 

除研资局研究学者计划外,黄教授亦曾获香港研资局杰出青年学者奖、国家自然科学基金优秀青年科学家基金(港澳)项目,以及Morris and Dorothy Rubinoff优秀博士论文奖等荣誉。