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吴华明

吴华明

职称:
副研究员
院系:
应用数学中心
电子邮箱:
whming@tju.edu.cn
办公地点:
卫津路校区25教

研究方向

移动云计算; 移动边缘计算; 雾计算;无线通信; 物联网; 深度学习

教育背景

  • 2005.09 - 2009.07  哈尔滨工业大学(威海)   本科/学士
  • 2009.09 - 2011.07   哈尔滨工业大学    研究生/硕士
  • 2011.09 - 2015.12    德国 柏林自由大学(Freie Universtät Berlin)  研究生/博士(summa cum laude, 最高荣誉)

工作经历

  • 2010.06 - 2010.08   韩国  光州科学技术院GIST   实习生
  • 2016.05 - 2018.06   天津大学应用数学中心         讲师
  • 2019.01 - 2019.02   澳大利亚墨尔本大学, 云计算和分布式系统(CLOUDS)实验室  访问学者, 导师: Rajkumar Buyya
  • 2018.06 -  今          天津大学应用数学中心         副研究员

教学工作

《概率论与数理统计》48学时

科研工作

在研:
  • 2018-2021:项目骨干,社区风险监测与防范关键技术研究,国家重点研发计划重点专项,项目号:2018YFC0809800.
  • 2018-2021:参与,可触摸的解剖教学虚拟现实系统,天津市互联网跨界融合创新科技重大专项,项目号:18ZXRHSY00160.
  • 2019-2021:主持,云雾协同计算环境下基于时延约束的混合任务卸载研究,国家自然科学基金-青年基金项目,项目号:61801325.
  • 2018-2021:主持,移动云计算环境下的多目标任务卸载决策研究,天津市自然科学基金项目,项目号:18JCQNJC00600.
  • 2018-2019:主持,基于Auto-Encoder和EBGAN的通信系统收发机建模,华为创新研究计划(HIRP)项目,项目号:HO2018085138.
  • 2018-2019:主持,用于AI训练的非结构化数据模拟生成,华为创新研究计划(HIRP)项目,项目号:HO2018085347.
已结题:
  • 2018-2019:主持,新一代信息技术热点调研与发展趋势展望,阿里活水计划课题项目.
  • 2018-2019:主持,创新人才培养项目:天津大学博士研究生学术论坛—数学学院分论坛(应用数学与多学科交叉), 项目号:YCX18050.
  • 2017-2018:主持,端-云系统中基于时延和能耗的任务卸载,华为创新研究计划(HIRP)项目,项目号:HIRPO2017050307.

主要荣誉

  • 2019年 软计算与机器学习国际会议(SCML2019) 特邀讲者
  • 2018年 入选第五批天津市创新人才推进计划-青年科技优秀人才
  • 2018年 入围2018阿里活水计划学者
  • 2018年 Future Generation Computer Systems(SCI 二区,IF:4.639)  杰出审稿人
  • 2018年 第七期智能自动化学科前沿讲习班 特邀讲者
  • 2018年 亚洲太平洋计算机和信息研究学会(APSCIT) -计算与信息技术研究会议(CITR 2018)  特邀讲者
  • 2018年 天津大学沈志康奖教金
  • 2017年 第五届“英特尔杯”2017全国并行应用挑战赛人工智能“并行基金”赛区优胜奖(指导老师)
  • 2015年 德国博士学位(summa cum laude, top 3%, 最高荣誉奖)
  • 2013年 Student Travel Grant  ACM Sigmetrics

学术兼职

Conference Activities:

  • Lead Guest Editor, Wireless Communications and Mobile Computing (SCI), SI on Deep Learning Driven Wireless Communications and Mobile Computing
  • Work in Progress and Vision Track Chair, PC Member, ACM International Conference on Performance Engineering (ICPE), 2019 in Mumbai, India.
  • Workshop Chair & PC Member, 30th IEEE International Symposium on Software Reliability Engineering (ISSRE 2019) in College Park, Maryland, USA
  • Publicity Chair & PC Member, ACM International Conference on Performance Engineering (ICPE), 2018 in Berlin, Germany.
  • TPC Member, 5th International Conference of Pioneering Computer Scientists, Engineers and Educators (ICYCSEE 2019)  Guilin, China.
  • Committee Chair, Asia Pacific Society for Computing and Information Technology (APSCIT)
  • TPC Member, First International Workshop on Intelligent Cloud Computing and Networking (ICCN 2019) in conjunction with IEEE INFOCOM 2019 in Paris, France.
  • TPC Member, Computer Vision Conference (CVC) 2019,  Las Vegas, Nevada, United States
  • TPC Member, Future of Information and Communication Conference (FICC) 2019, San Francisco
  • TPC Member, Intelligent Systems Conference (IntelliSys) 2018, London, UK.
  • PC Member, 15th European Performance Engineering Workshop (EPEW) 2018 in Paris, France.
  • PC Member, Conference on Quantitative Evaluation of SysTems (QEST) 2018 in Beijing.
  • Student Forum Chair, PC Member, Conference on Quantitative Evaluation of SysTems (QEST) 2017 in Berlin, Germany.
  • PC Member, 14th European Performance Engineering Workshop (EPEW) 2017 in Berlin, Germany.
  • IEEE 会员,ACM 会员,中国计算机学会CCF 会员, 中国数学会会员,中国工业与应用数学学会会员
  • 国家自然科学基金委(信息学部)  评议人 

Journal Reviews:

其它

发表论文

  • 1.Congcong Liu and Huaming Wu, Channel Pruning Based on Mean Gradient for Accelerating Convolutional Neural Networks, Signal Processing, 2019, vol. 156, 84-91

  • 2.Monica M.Y. Zhang, Kun Shang, and Huaming Wu. Learning Deep Discriminative Face Features by Customized Weighted Constraint, Neurocomputing, 2019, 332, 71-79

  • 3.Huaming Wu, William J. Knottenbelt and Katinka Wolter. An Efficient Application Partitioning Algorithm in Mobile Environments, IEEE Transactions on Parallel and Distributed Systems

  • 4.Monica M.Y. Zhang, Kun Shang, and Huaming Wu. Deep Compact Discriminative representation for unconstrained face recognition, Signal Processing: Image Communication, 2019

  • 点击下载

    5.Wu, H., and Wolter, K., Stochastic Analysis of Delayed Mobile Offloading in Heterogeneous Networks, IEEE Transactions on Mobile Computing, 17(2), 461-474, 2018.

  • 6.Wu, H., Yi, S., and Wolter, K., Energy-Efficient Decision Making for Mobile Cloud Offloading, IEEE Transactions on Cloud Computing, 2018. IF:7.928

  • 7.Meng T., Wolter, K., Wu, H. and Wang, Q., A Secure and Cost-efficient Offloading Policy for Mobile Cloud Computing against Timing Attacks, Pervasive and Mobile Computing, 45, 4-18, 2018.

  • 8.Chen, Z. L., Wang, J., Li, W. J., Li, N., Wu, Wu, H., & Wang, D. W. Convolutional neural network with nonlinear competitive units. Signal Processing: Image Communication. 60 ,193-198, 2018

  • 9.Wu, H., Multi-Objective Decision-Making for Mobile Cloud Offloading: A Survey, IEEE Access, vol. 6, pp. 3962 - 3976, 2018.

  • 10.Wu, B., Chen, Z., Wang, J., & Wu, H. (2018). Exponential discriminative metric embedding in deep learning. Neurocomputing, 290, 108-120.

  • 11. Monica M.Y. Zhang, Yifang Xu and Wu, H. Orientation Truncated Center Learning for Deep Face Recognition,IET Electronics Letters, Vol. 54, No. 19, 1110–1112

  • 12.Wu, H. Performance Modeling of Delayed Offloading in Mobile Wireless Environments with Failures, IEEE Communications Letters, vol.22, no.11, pp. 2334-2337

  • 13.Zhang, M. M.Y., Shang, K.& Wu, H. (2018). Exponential discriminative metric embedding in deep learning. Neurocomputing, 290, 108-120.

  • 14.Wu, H., Knottenbelt, W., Wolter, K., & Sun, Y. (2016). An Optimal Offloading Partitioning Algorithm in Mobile Cloud Computing. In International Conference on Quantitative Evaluation of Systems (pp. 311-328). Springer International Publishing.

  • 15.Wu, H., Sun, Y., & Wolter, K. (2015) Analysis of the Energy-Response Time Tradeoff for Delayed Mobile Cloud Offloading. ACM SIGMETRICS Performance Evaluation Review, 43(2), 33-35.

  • 16.Wu, H. (2015). Analysis of mHealth Systems with Multi-cloud Computing Offloading. In Mobile Health (pp. 589-608). Springer International Publishing.

  • 17.Wu, H., Knottenbelt, W. J. & Wolter, K. (2015) Analysis of the Energy-Response Time Tradeoff for Mobile Cloud Offloading using Combined Metrics, Teletraffic Congress (ITC), 2015 27th International (pp. 134-142). IEEE.

  • 18.Wu, H., Wang, Q., & Wolter, K. (2013). Tradeoff Between Performance Improvement and Energy Saving in Mobile Cloud Offloading Systems. In Communications (ICC), 2013 IEEE International Conference on (pp. 728-732). IEEE.

  • 19.Wu, H., Wang, Q., & Wolter, K. (2012). Methods of cloud-path selection for offloading in mobile cloud computing systems. In Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on (pp. 443-448). IEEE.

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