个人简历
高浩，男，先进技术研究院院长助理，副教授，硕士生导师。2009年取得工学博士学位。分别于2009年至2011年在清华大学自动化系、2012年7月至2013年8月在香港城市大学计算机系从事博士后研究以及2015年~2016年在澳门大学从事客座研究员工作。主要从事人工智能及模式识别及相关领域的科研工作。
近年来，以第一作者和通讯作者身份在国内外重要学术刊物及学术会议发表学术论文二十余篇，其中包括IEEE Trans. SMC-B, IEEE Trans. Industrial Informatics, IEEE Trans.Instrumentation and Measurements, Information Sciences, Applied Soft Computing等。授权和公开专利5项。长期担任IEEE Trans. SMC-B, IEEE Trans.Industrial Electronics, Information Sciences等国内外著名学术期刊和学术会议审稿人，担任TENCON、ICMLC等多个国内外会议的委员会委员。主持国家自然科学基金、中国博士后基金以及江苏省博士后基金多项。参与了国家973、863、国家自然科学基金重点项目、国家自然科学基金的研究。
目前，承担航天部五院委托等多项横向研究和开发项目。
研究方向及主要成果
主要研究方向
人工智能与模式识别
近年来发表的代表性论文：
Publications:
1.Hao Gao, Sam Kwong, Baojie Fan, Ran Wang. A hybridparticle-swarm tabu search algorithm for solving job shop scheduling problems.IEEE Transaction on IndustrialInformatics, vol. 10 (4), pp. 2044-2054, 2014.
2.Hao Gao, Sam Kwong, J.J Yang, J. J. Cao. Particle swarmoptimization based on intermediate disturbance strategy algorithm and itsapplication in multi-threshold image segmentation, Information Sciences, vol.250 (20), pp. 82-112, 2013.
3.Hao Gao, Wenbo Xu. A new particle swarm algorithm and ItsGlobally Convergent Modifications. IEEETransaction on Systems, Man, and Cybernetics-Part B: Cybernetics, vol.41 (5), pp. 1334-1351, 2011.
4.Hao Gao, Wenbo Xu, Sun J., Tang Y. L.. MultilevelThresholding for Image Segmentation through an Improved Quantum-behaved ParticleSwarm Algorithm, IEEE Transaction onInstrumentation and Measurement, vol. 59 (4), pp. 934-946, 2011.
5.Hao Gao, Wenbo Xu. Particle Swarm Algorithm with Hybrid MutationStrategy, Applied Soft Computing, vol.11 (8), pp.5129-5142, 2011.
6.Hao Gao, WeiqinZang, JingjingCao. A particle swarm optimization with moderate disturbance strategy. IEEE32th Chinese Control Conference, pp. 7994-7999, 2013.
7.Baojie Fan, Hao Gao, Yang Cong,Yingkui Du, Online learning a high-quality dictionary and classifier jointlyfor multitask object tracking. IEEE Multimedia, vol. 21 (4), pp. 56-66, 2014.
8.Baojie Fan, Yingkui Du, Hao Gao,Baoyun Wang, Online discriminative dictionary learning via label informationfor multi task object tracking, IEEE International Conference on Multimedia andExpo, pp. 1-6, 2014.
9.Hao Gao, WeiqinZang, JingjingCao. A particle swarm optimization with moderate disturbance strategy. IEEE32th Chinese Control Conference, pp. 7994-7999, 2013.
10.Hao Gao, Yujiao Shi, Dongmei Wu. Imagesegmentation using an improved differential algorithm. SPIE/COS Photonics Asia,vol. 9773, 2014.
11.Qifeng Qian, Hao Gao, Baoyun Wang. A SVMmethod trained by improved particle swarm optimization for image segmentation,China Conference of Computer Vision, vol. 483, pp. 263-272, 2014.
12.Dongmei Wu, Hao Gao. Study onasynchronous update mechanism in particle swarm optimization. 14thInternational Symposium on Communications and InformationTechnology, pp. 90-93, 2014.
13.Dongmei Wu, Hao Gao. Research of anadaptive particle swarm optimization on engine optimization problem. 5thInternational Conference on Intelligent Human-Machine Systems and Cybernetics,pp. 42-45, 2013.
授权专利：
1.戴琼海，高浩：发明专利：一种基于适度随机搜索行为的多阈值图像分割方法。专利号：ZL2010 10227364.5.
2.戴琼海，高浩：发明专利：一种摄像机标定方法。专利号：ZL 2011 10310622.0.
联系方式
单位电话：025-85866931
Email: gaohao@njupt.edu.cn
