Dr. Longbo Huang is an associate professor (with tenure) at the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University, Beijing, China. He received his Ph.D. in EE from the University of Southern California, and then worked as a postdoctoral researcher in the EECS dept. at University of California at Berkeley before joining IIIS. Dr. Huang’s research focuses on decision intelligence (AI for Decisions), including deep reinforcement learning, online learning and reinforcement learning, stochastic network optimization, distributed optimization and machine learning.

Dr. Huang has held visiting positions at the LIDS lab at MIT, the Chinese University of Hong Kong, Bell-labs France, and Microsoft Research Asia (MSRA). He was a visiting scientist at the Simons Institute for the Theory of Computing at UC Berkeley in Fall 2016. Dr. Huang serves/served on 50+ TPCs and 10+ organizing committees for ACM/AI/IEEE conferences, including the General Chair for ACM Sigmetrics 2021, the TPC co-chair for ITC 2022, WiOpt 2020 and NetEcon 2020. Dr. Huang serves/served on the editorial board for IEEE Journal on Selected Areas in Communications Special Issue on Human-in-the-loop Mobile Network (Lead guest editor 2016), IEEE Transactions on Communications (TCOM 2017-2020), ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS 2017-present), and IEEE/ACM Transactions on Networking (ToN, 2019-present). He is a senior member of ACM and IEEE, an IEEE ComSoc Distinguished Lecturer, and an ACM Distinguished Speaker.

Dr. Huang received 5 best paper nomination/premier paper recognitions at top-tier conferences, including NeurIPS 2021 (Oral presentation, top 1%), AAMAS 2020 (Selected for fast-track publication at JAAMAS, top 5%), IEEE INFOCOM 2018 (Invited to fast-track review at IEEE TNSE, 7 out of 312 accepted papers), ACM e-Energy 2016 (Best paper runner-up) and ACM MobiHoc 2014 (Best paper candidate). Dr. Huang received the Outstanding Teaching Award from Tsinghua university in 2014. He received the Google Research Award and the Microsoft Research Asia Collaborative Research Award in 2014, and was selected into the MSRA StarTrack Program in 2015. Dr. Huang won the ACM SIGMETRICS Rising Star Research Award in 2018.

黄隆波博士是清华大学交叉信息研究院长聘副教授,博士生导师,ACM与IEEE高级会员,ACM杰出演讲人与IEEE通信学会杰出演讲人。加入清华之前,黄博士于美国南加州大学电子工程系获得博士学位,并于美国加州大学伯克利分校电子工程与计算机科学系担任博士后研究员。黄博士曾先后于美国麻省理工学院与加州大学伯克利分校担任访问学者,于法国贝尔实验室与香港中文大学网络编码研究所担任访问教授,并于2016年秋季在伯克利Simons计算理论研究院担任长期访问科学家。黄博士于2013年获选清华先进工作者,于2014年获选清华大学“良师益友”(两年一次,每次全校仅评选约40人),并获谷歌科研奖与微软亚洲研究院联合科研奖,于2015年入选微软亚洲研究院“铸星计划”,并于2018年获国际计算机协会在性能分析评估领域的专业权威机构ACM SIGMETRICS 评选的青年科学家奖(全球每年1人,首位获奖国内学者)。

黄博士的科研集中于人工智能与决策,包括深度强化学习、在线学习与强化学习、随机网络优化、分布式优化与机器学习等。黄博士在ACM/AI/IEEE期刊与会议共发表论文100余篇,其成果5次获得国际会议最佳论文奖提名与优选论文,包括2021年NeurIPS文章获优选口头报告文章(全球9000+投稿中前1%),2020年AAMAS文章获邀投往期刊JAAMAS的快速审稿通道(全球800+投稿中前5%),2018年IEEE INFOCOM 文章获邀投稿至IEEE TNSE期刊(全球1600+投稿中仅7篇获邀),及2016年ACM e-Energy最佳论文亚军奖与2014年ACM MobiHoc最佳论文提名奖。黄博士担任超过10次ACM/IEEE会议的组委,包括ACM Sigmetrics 2021大会唯一主席, ITC 2022、IEEE WiOpt 2020与GameNets 2019的程序委员会主席等, 及2019年ACM Sigmetrics Rising Star奖评委,并担任超过50次ACM/AI/IEEE会议的程序委员。黄博士于2016年担任IEEE期刊IEEE Journal on Selected Areas in Communications (JSAC)特刊Human-In-The-Loop Mobile Networks的首席客座编委, 于2017-2020担任IEEE通信领域期刊IEEE Transactions on Communications (TCOM)的编委。目前黄博士担任ACM建模分析领域期刊ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS),以及网络领域期刊IEEE/ACM Transactions on Networking (TON)的编委。