郝祁
| 姓名 | 郝祁 |
| 性别 | 发明专利4999代写全部资料 |
| 学校 | 南方科技大学 |
| 部门 | 计算机科学与工程系 课题组网站 |
| 学位 | 发明专利包写包过 特惠申请 |
| 学历 | 版权登记666包过 代写全部资料 |
| 职称 | 教授 |
| 联系方式 | 深圳市南山区学苑大道1001号南山智园A7栋906 |
| 邮箱 | hao.q@sustech.edu.cn |
| 集群智慧云企服 / 知识产权申请大平台 微信客服在线：543646 急速申请 包写包过 办事快、准、稳 软件产品登记测试 软件著作权666元代写全部资料 实用新型专利1875代写全部资料 |
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教师主页 团队成员 科研项目 研究领域 学术成果 教学 科研分享 新闻动态 疼痛医学中心 成果介绍 软件 毕业去向 加入我们 联系我们 郝祁 Google Scholar ResearcherID 教授 计算机科学与工程系 课题组网站 郝祁博士 南方科技大学 计算机科学与工程系 教授 研究领域：仿生智能传感器设计、智能感知、机器学习、无人自主系统。 教育经历： 2001/09 — 2006/05 美国杜克大学，电子与计算机工程，博士 1994/09 — 1997/04 上海交通大学，电机工程，硕士 1990/09 — 1994/07 上海交通大学，电机工程，学士 工作经历： 2014/05 — 至今 南方科技大学，计算机科学与工程系，教授 2007/08 — 2014/05 美国阿拉巴马大学，电子与计算机工程系，助理教授 2006/07 — 2007/07 美国肯塔基大学, 虚拟环境与可视化中心, 博士后 1998/08 — 2001/08 新加坡国立数据研究所，助研 1997/05 — 1998/06 上海电动工具研究所, 工程师 郝祁博士是南方科大计算机科学与工程系的教授、系副主任。研究领域包括：智能感知、机器学习与无人自主系统。于2006年在美国杜克大学获取电子与计算机工程系博士学位，于美国肯塔基大学虚拟环境与可视化中心进行博士后研究。曾在美国阿拉巴马大学电子与计算机工程系担任助理教授, 主持两项、共同主持一项美国国家科学基金项目。加入南科大后，主持一项国家自然科学基金面上项目（已结题）、参与一项国家自然科学基金重点项目（已结题），主持一项国家自然科学基金重点合作项目、共同主持深圳市机器人视觉与导航重点实验室，主持深圳市可信自主系统研究院无人驾驶中心，深圳南山区领航团队、南科大海梁智能交通中心、南科大工学院人工智能无人驾驶公共科研平台、南科大风向标智能网联汽车教育联合实验室、Intel自动驾驶数据集项目、华为2012实验室无人驾驶仿真平台项目与安全驾驶决策项目，以及多项深圳科创委重点基础研究、中外合作、创客平台项目和省市级教改项目。曾多次担任过美国国家科学基金会(NSF)和美国能源部先进科研项目(DOE ARPA-E)评委，已经发表了44篇SCI学术论文、70篇EI学术论文，获批20项国家专利，以及合作编写专著一本。 个人简介 郝祁 计算机科学与工程系 副教授兼系副主任 南方科技大学-海梁智能交通研究中心 执行主任 研究方向 仿生智能传感器设计、智能感知、机器学习、与无人自主系统 教育背景 ◆ 2002-2006，美国杜克大学，博士 ◆ 1994-1997，上海交通大学，硕士 ◆ 1990-1994，上海交通大学，学士 工作经历 ◆ 2007-2014 (美国）阿拉巴马大学电子与计算机工程系助理教授 ◆ 2006-2007 （美国）肯塔基大学可视化与虚拟环境中心博士后 ◆ 1998-2001 新加坡数据储存研究院研究助理 ◆ 1997-1998 上海电动工具研究所工程师 荣誉与奖项 ◆ NSF Award“Intelligent Compressive Multi-Walker Recognition and Tracking (iSMART) through Pyroelectric Sensor Networks”, 2009 ◆ NSF Award “Cognitive Sensing Research Infrastructure for Distributed Behavioral Biometrics”, 2011 ◆ IEEE 智能系统多传感器融合与整合会议“最佳论文”入围奖，2012年 ◆ IEEE 传感器会议“最佳学生论文”（指导教授），2013年 ◆ IEEE 智能系统多传感器融合与整合会议“最佳论文”入围奖，2016年 ◆ IEEE 智能系统多传感器融合与整合会议“最佳论文”入围奖，2016年 ◆ IEEE 传感器会议“最佳学生论文”第三名（指导教授），2018年 ◆ IEEE通信会议“最佳论文”，2020年 ◆ 深圳市先进教育工作者，2017年 ◆ 广东省南粤优秀教师，2021年 ◆ 校内荣誉： （1）2017-2021年南科大优秀书院导师奖 （2）2017年南科大青年教学竞赛二等奖 （3）2017年南科大杰出服务奖 （4）2018年南科大杰出科研奖 （5）2015-2021年南科大招生先进个人 （6）2017年南科大海外招生荣誉奖 （7）2019年南方科技大学优秀服务奖 （8）2021年南科大国际招生杰出贡献奖 （9）2021年南科大名师中学讲座天问奖 代表性论文 R. Han, S. Chen, S. Wang, Z. Zhang, R. Gao, Q. Hao, J. Pan, "Reinforcement learned distributed multi-robot navigation with reciprocal velocity obstacle shaped rewards," IEEE Robotics and Automation Letters, Vol.7, No.3, Jul., pp. 5896-5903, 2022. S. Wang, R. Han, Y. Hong, Q. Hao, M. Wen, L. Musavian, S. Mumtaz, and D. W. K. Ng," Robotic wireless energy transfer in dynamic environments: system design and experimental validation," IEEE Communication Magazine, Vol.60, No.3, Mar., pp. 40-46, 2022. G. Ding, M. Zhang, E. Li, and Q. Hao, "JST: Joint self-training for unsupervised domain adaptation on 2D&3D object detection," IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, May 2022. L. Ding, D. Li, B. Liu, W. Lan, B. Bai, Q. Hao, W. Cao and K. Pei, "Capture uncertainties in deep neural networks for safe operation of autonomous driving vehicles," IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA 2021), New York, USA, Oct. 2021. (best paper) K. Huang and Q. Hao, "Joint multi-object detection and tracking with camera-LiDAR Fusion for autonomous driving," IEEE International Conference on Intelligent Robots and Systems (IROS), Prague, Oct 2021. Z. Zhang, S. Wang, Y. Hong, L. Zhou, and Q. Hao, " Distributed dynamic map fusion via federated learning for intelligent networked vehicles, " IEEE International Conference on Robotics and Automation (ICRA), Xi'an, May 2021. S. Wang, M. Wen, M. Xia, R. Wang, Q. Hao, Y. Wu, “Angle aware user cooperation for secure massive MIMO in Rician fading channel," IEEE Journal on Selected Areas in Communications, vol. 38, no. 9, Jun., pp. 2182 – 2196, 2020. R. Ma, G. Lan, Q. Hao, "Enabling Cognitive Pyroelectric Infrared Sensing: From Reconfigurable Signal Conditioning to Sensor Mask Design," IEEE Transactions on Industrial Informatics, vol. 16, no. 7, Sep., pp. 4436 – 4446, 2019. S. Wang, F. Jiang, R. Ma, and Q. Hao, "Development of UAV based target tracking and recognition systems," IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 8, Jun., pp. 3409 – 3422, 2020. F. Han, D. Li, Q. Hao, “Autonomous driving framework for bus transit systems towards operation safety and robustness”, IEEE Intelligent Transportation Systems Conference, Oct. 2019. H. Xu, G. Lan, S. Wu, Q. Hao, "Online intelligent calibration of cameras and LiDARs for autonomous driving systems," IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, Oct. 2019. R. Ma, G. Lan, Q. Hao, “Enabling cognitive pyroelectric infrared sensing: from reconfigurable signal conditioning to sensor mask design”, IEEE Transactions on Industrial Informatics, accepted, 2019. S. Wang, F. Jiang, R. Ma, and Q. Hao, “Development of UAV based target tracking and recognition systems”, IEEE Transactions on Intelligent Transportation Systems, accepted, 2019. F. Jiang, F. Navan, Q. Hao, “Design, implementation and evaluation of a neural network-based quadcopter UAV system”, IEEE Transactions on Industrial Electronics, Volume: 67, Issue: 3, pp.2076 - 2085, Mar. 2020. F. Jiang and Q. Hao, “Pavilion: bridging photo-realism and robotics,” Proc. of IEEE International Conference on Robotics and Automation (ICRA), May 2019. F. Navan, C. Lim, Q. Hao, “A reinforced fuzzy ARTMAP model for data classification”, International Journal of Machine Learning and Cybernetics, Jun., pp 1–13, 2018. Q. Miao, F. Hu, Q. Hao, “Deep learning for intelligent wireless networks: a comprehensive survey”, IEEE Communications Surveys & Tutorials, vol. 20, no. 4, Jun., pp.2595-2621, 2018. R. Ma, Q. Hao, X. Hu, and C. Wang, “Space coding schemes for multiple human localization with fiber-optic sensors”, IEEE Sensors Journal, vol. 18, no. 11, Jun., pp.4643-4653, 2018. R. Ma, F. Hu, and Q. Hao, “Active compressive sensing via pyroelectric infrared sensor for human situation recognition,” IEEE Trans. Syst., Man, and Cyber.: Systems, vol. 47, no. 12, Dec., pp. 3340-3350, 2017. J. Lu, T. Zhang, Q. Sun, F. Hao, and Q. Hao, “Binary compressive tracking,” IEEE Trans. on Aerospace and Electronic Systems, vol. 53, no. 4, Aug., pp.1755-1768, 2017. F. Hu, and Q. Hao, “Cyber-physical system with virtual reality for intelligent motion recognition and training,” IEEE Trans. Syst., Man, and Cyber: Systems, vol. 47, no. 2, Feb., pp. 347-363, Feb. 2017. J. Lu, T. Zhang, Fei Hu, and Q. Hao, “Preprocessing design in pyroelectric infrared sensor-based human-tracking system: on sensor selection and calibration,” IEEE Trans. Syst., Man, and Cyber.：Systems, vol. 47, no.2, Feb. pp. 263-275, 2017. F. Hu, Y. Lu, A. V. Vasilakos, Q. Hao, R. Ma, Y. Patil, T. Zhang, J. Lu, X. Li, N. N. Xiong, “Robust cyber-physical systems: concept, models, and implementation,” Future Generation Computer Systems, vol. 16, no. 4, Mar., pp. 449-475, 2016. B. Zan, F. Hu, K. Bo, and Q. Hao, “Dual-resolution friend locator system with privacy enhancement through polygon decomposition,” IEEE Trans. Vehicular Technol, vol. 65, no. 2, Feb., pp. 837-847, 2016. Q. Hao, “Binary sensing and perception for human behavior study,” Proc. of IEEE ChinaSIP, Chengdu, Jul., pp. 368-372. 2015. F. Hu, Q. Hao*, and K. Bo, “A survey on software defined networking (SDN) and openflow: from concept to implementation,” IEEE Comm. Surveys and Tutorials, vol. 16, no. 4, Nov., pp. 2181-2206, 2014. F. Hu, Q. Hao, and K. Bo, “A survey on software defined networking (SDN) and openflow: from concept to implementation,” IEEE Comm. Surveys and Tutorials, vol. 16, no. 4, Nov., pp. 2181-2206, 2014. Q. Sun, F. Hu, and Q. Hao, “Human movement modeling and activity perception based on fiber-optic sensing system,” IEEE Trans. Human-Machine Systems, vol. 44, no. 6, Dec., pp. 743-754, 2014. Q. Sun, F. Hu, and Q. Hao, “Mobile targets scenario recognition via low-cost pyroelectric sensing system: towards a context-enhanced accurate identification,” IEEE Trans. on Systems, Man, and Cybernetics, vol. 44, no. 3, Mar., pp. 375-384, 2014. Y. Wang, K. Liu, Q. Hao, D. L. Lau, and L. G. Hassebrook, “Robust active stereo vision using Kullback-Leibler divergence," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 34, no. 3, Mar., pp. 548-563, 2012. Y. Wang, K. Liu, Q. Hao, D. L. Lau, and L. G. Hassebrook, “Period Coded Phase Shifting Strategy for Real–time 3-D Structured Light Illumination,” IEEE Trans. on Image Processing, vol. 20, no. 11, pp. Nov., 3001-3013, 2011. F. Hu, Q. Hao, M. Lukowiak, Q. Sun, K. Wilhelm, S. Radziszowski, and Y. Wu, “Trustworthy data collection from implantable medical devices via high-speed security implementation based on IEEE1363,” IEEE Trans. on Information Technology in Biomedicine, vol.14, no. 6, Nov., pp. 1397-1404, 2010. K. Liu, Y. Wang, D. L. Lau, Q. Hao, and L. G. Hassebrook, “Maximum SNR pattern strategy for phase shifting methods in structured light illumination,” J. Opt. Soc. Am. A, vol. 27, no. 9, Sept., pp. 1962-1971, 2010. 主要在研项目： 1．国家自然科学基金面上项目，“面向多目标定位、动作捕捉与行为分析的智能二进制感知技术研究”， 2017~2020，主持； 2． 深圳市南山区领航团队，“下一代智能超高清相机阵列系统研究及产业化”， 2018~2022，主持； 3．横向经费，深圳市海梁科技有限公司，“南方科技大学海梁智能交通研究中心”， 2018~2020，主持； 4．横向经费，英特尔智能网联汽车大学合作研究中心，“Development of Open Datasets for Autonomous Transportation with Smart Samples and Multi-agent Benchmarks”, 2019~2021，主持。 5. 深圳国家自然科学基金机器人基础研究中心，“机器人关键基础零部件及基础软件核心技术分析研究，” 2019年，参与 6. 横向经费，深圳市风向标教育资源科技有限公司，“南科大计算机系风向标智能网联汽车国际工程教育联合实验室，” 2020~2022，主持 7. 华为2012研究院，“自动驾驶系统自主安全决策与规划研究，” 2020~2022，共同主持 8. 高水平二期专项经费项目，“工学院人工智能与无人驾驶公共科研平台，” 2019~2021，主持 9. 横向经费，深圳市基础研究重点项目，“自主无人驾驶数据集与仿真平台一体化关键技术研究,” 2020~2023，主持 10、华为2012研究院，“自动驾驶虚拟仿真技术,” 2021-2026, 主持 11、深圳市科创委，"深圳市可信自主研究院（图灵奖实验室）无人驾驶中心," 2021~2025, 主持 12、教育部高等教育司，产学合作协同育人项目，“面向新工科教育的智能网联汽车实践基地,” 2021~2022，主持 13、南方科技大学专项人才培养计划，“立足湾区产学结合面向国际：南方科技大学图灵班人才培养探索与实践,”2021-2023，主持 个人简介 研究领域 智能感知、机器学习、无人自主系统 教学 主讲课程：《机器学习》《智能机器人》 学术成果 查看更多 发表期刊论文: [41] R. Han, S. Chen, S. Wang, Z. Zhang, R. Gao, Q. Hao, J. Pan, “Reinforcement learned distributed multi-robot navigation with reciprocal velocity obstacle shaped rewards,” IEEE Robotics and Automation Letters, Vol.7, No.3, Jul., pp. 5896-5903, 2022. (correspondence author) [40] X. Zheng, R. Ma, R. Gao, Q. Hao, “Phase-SLAM: Phase based simultaneous localization and mapping for mobile structured light illumination systems,” IEEE Robotics and Automation Letters, Mar. 2022. (correspondence author) [39] S. Wang, R. Han, Y. Hong, Q. Hao, M. Wen, L. Musavian, S. Mumtaz, and D. W. K. Ng,” Robotic wireless energy transfer in dynamic environments: system design and experimental validation,” IEEE Communication Magazine, Vol.60, No.3, Mar., pp. 40-46, 2022. [38] S. Wang, Y. Hong, R. Wang, Q. Hao, Y. Wu, D. W. K. Ng, “Edge Federated Learning Via Unit-Modulus Over-The-Air Computation,” IEEE Transactions on Communications, Feb. 2021. (correspondence author) [37] S. Zhang, L. Zhao, S. Huang, Q. Hao, Menglong Ye, “A template-based 3D reconstruction of colon structures and textures from stereo colonoscopic images,” IEEE Transactions on Medical Robotics and Bionics, vol. 3, no. 1, Dec., pp. 85 – 95, 2020.（Correspondence author） [36] L. Zhou, Y. Hong, S. Wang, R. Han, D. Li, R. Wang, and Q. Hao, “Learning centric wireless resource allocation for edge computing: algorithm and experiment,” IEEE Transactions on Vehicular Technology, vol. 70, no. 1, Dec., pp. 1035 – 1040, 2020. (Q1, Cited 2) [35] S. Wang, M. Wen, M. Xia, R. Wang, Q. Hao, Y. Wu, “Angle aware user cooperation for secure massive MIMO in Rician fading channel,” IEEE Journal on Selected Areas in Communications, vol. 38, no. 9, Jun., pp. 2182 – 2196, 2020. (Q1, Cited 2) [34] R. Ma, G. Lan, Q. Hao, “Enabling cognitive pyroelectric infrared sensing: from reconfigurable signal conditioning to sensor mask design,” IEEE Transactions on Industrial Informatics, vol. 16, no. 7, Jul, 2020, Sep., pp. 4436 – 4446, 2019. (Q1, Cited 20) (Correspondence author) [33] S. Wang, F. Jiang, R. Ma, and Q. Hao, “Development of UAV based target tracking and recognition systems,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 8, Jun., pp. 3409 – 3422, 2020. (Q1, Cited 3) (Correspondence author) [32] F. Navan, Y. Shi, C. Lim, Q. Hao, C. Tan, “Feature selection based on brain storm optimization for data classification,” Applied Soft Computing Journal, vol. 80, Jul., pp. 761-775, 2019.（Q1, Cited 20） [31] F. Jiang, F. Navan, Q. Hao, “Design, implementation and evaluation of a neural network based quadcopter UAV system,” IEEE Transactions on Industrial Electronics, vol. 67, no. 3, Mar., pp. 2076 – 2085, 2019. (Q1, Cited 9) (Correspondence Author) [30] F. Navan, C. Lim, Q. Hao, “A reinforced fuzzy ARTMAP model for data classification,” International Journal of Machine Learning and Cybernetics, Jun., pp. 1–13, 2018. (Q1, Cited 14)(Correspondence author) [29] Q. Miao, F. Hu, Q. Hao, “Deep learning for intelligent wireless networks: a comprehensive survey,” IEEE Communications Surveys & Tutorials, vol. 20 , no. 4, Jun., pp. 2595 – 2621, 2018. (Q1, Cited 196) (Correspondence author) [28] R. Ma, Q. Hao, X. Hu, and C. Wang, “Space coding schemes for multiple human localization with Fiber-optic sensors,” IEEE Sensors Journal, vol. 12, no. 8, Mar., pp. 4643 – 4653, Mar. 2018. (Q2, Cited 2) (Correspondence author) [27] J. Lu, T. Zhang, Q. Sun, F. Hao, and Q. Hao, “Binary compressive tracking,” IEEE Transactions on Aerospace and Electronic Systems, vol. 53, no. 4, Aug., pp.1755 – 1768, 2017. (Q2, Cited 9) [26] R. Ma, F. Hu, and Q. Hao, “Active compressive sensing via pyroelectric infrared sensor for human situation recognition,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 47, no. 12, Dec., 3340 – 3350, 2017. (Q1, Cited 23) [25] F. Hu, and Q. Hao, “Cyber-physical system with virtual reality for intelligent motion recognition and training,” IEEE Transactions Systems, Man, and Cyber: Systems, vol. 47, no. 2, Feb., pp. 347-363, 2017. (Q1, Cited 26) [24] J. Lu, T. Zhang, Fei Hu, and Q. Hao, “Preprocessing design in pyroelectric infrared sensor-based human-tracking system: on sensor selection and calibration,” IEEE Transactions Systems, Man, and Cyber.：Systems, vol. 47, no.2, Feb., pp. 263-275, 2017. (Q1, Cited 31) [23] F. Hu, Y. Lu, A. V. Vasilakos, Q. Hao, R. Ma, Y. Patil, T. Zhang, J. Lu, X. Li, N. N. Xiong, “Robust cyber-physical systems: concept, models, and implementation,” Future Generation Computer Systems, vol. 16, no. 4, Mar., pp. 449-475, 2016. (Q1, Cited 132) [22] B. Zan, F. Hu, K. Bo, and Q. Hao, “Dual-resolution friend locator system with privacy enhancement through polygon decomposition,” IEEE Trans. Vehicular Technol, vol. 65, no. 2, Feb., pp. 837-847, 2016. (Q1, Cited 2) [21] F. Hu, Q. Hao, and K. Bo, “A survey on software defined networking (SDN) and openflow: from concept to implementation,” IEEE Comm. Surveys and Tutorials, vol. 16, no. 4, Nov., pp. 2181-2206, 2014. (Q1, Cited 602) [20] Q. Sun, F. Hu, and Q. Hao, “Human movement modeling and activity perception based on fiber-optic sensing system,” IEEE Trans. Human-Machine Systems, vol. 44, no. 6, Dec., pp. 743-754, 2014. (Q2, Cited 19) [19] Q. Sun, F. Hu, and Q. Hao, “Mobile targets scenario recognition via low-cost pyroelectric sensing system: towards a context-enhanced accurate identification,” IEEE Trans. on Systems, Man, and Cybernetics, vol. 44, no. 3, Mar., pp. 375-384, 2014. (Q1, Cited 49) [18] Y. Wang, K. Liu, Q. Hao, D. L. Lau, and L. G. Hassebrook, “Robust active stereo vision using Kullback-Leibler divergence,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 34, no. 3, Mar., pp. 548-563, 2012. (Q1, Cited 65) [17] Y. Wang, K. Liu, Q. Hao, D. L. Lau, and L. G.Hassebrook, “Period coded phase shifting strategy for real–time 3-D structured light illumination,” IEEE Transactions on Image Processing, vol. 20, no. 11, Nov., pp. 3001-3013, 2011. (Q1, Cited 66) [16] F. Hu, Q. Hao, M.Lukowiak, Q. Sun, K. Wilhelm, S. Radziszowski, and Y. Wu, “Trustworthy data collection from implantable medical devices via high-speed security implementation based on IEEE1363,” IEEE Transactions on Information Technology in Biomedicine, vol.14, no. 6, Nov., pp. 1397-1404, 2010. (Q1, Cited 26) (Correspondence author) [15] K. Liu, Y. Wang, D. L. Lau, Q. Hao, and L. G. Hassebrook, “Maximum SNR pattern strategy for phase shifting methods in structured light illumination,” Journal of the Optical Society of America A, vol. 27, no. 9, Sept., pp. 1962-1971, 2010. (Q3, Cited 44) [14] Y. Wang, Q. Hao, A. Fatehpuria, L. G. Hassebrook, and D. L. Lau, “Quality and matching performance analysis of three-dimensional unraveled fingerprints,” Optical Engineering, vol. 49, no. 7, Jul., pp. 077202(1-10), 2010. (Q3, Cited 5) [13] K. Liu, Y. Wang, D. L. Lau, Q. Hao, and L. G. Hassebrook, “Dual-frequency pattern scheme for high-speed 3-D shape measurement,” Optics Express, vol. 18, no. 5, Mar., pp. 5229-5244, 2010. (Q1, Cited 277) [12] K. Liu, Y.Wang, D. L. Lau, Q. Hao, and L. G. Hassebrook, “Gamma model and its analysis for phase measuring profilometry,” Journal of the Optical Society of America A, vol. 27, no. 3, Feb., pp. 553-562, 2010. (Q3, Cited 156) [11] Q.Hao, F. Hu, and Y. Xiao, “Multiple human tracking and identification with wireless distributed pyroelectric sensor systems,” IEEE Systems Journal, vol. 3, no. 4, Dec., pp. 428-439, 2009. (Q1, Cited 143) [10] F. Hu, S. Lakdawala, Q. Hao, and M. Qiu, “Low-power, intelligent sensor hardware interface for medical data pre-processing,” IEEE Transactions on Information Technology in Biomedicine, vol. 13, no. 4, Jul., pp. 656-663, 2009. (Q1, Cited 26) [9] F. Hu, Y. Xiao, and Q. Hao, “Congestion-aware, loss-resilient bio-monitoring sensor networking for mobile health applications,” I IEEE Journal on Selected Areas in Communications, vol. 27, no. 4, May, pp. 450-465, 2009. (Q1, Cited 107) [8] J.-S. Fang, Q. Hao, D. J. Brady, B. D. Guenther, and K. Y. Hsu, “A pyroelectric infrared biometric system for real-time walker recognition by use of a maximum likelihood principal components estimation (MLPCE) method,” Optics Express, vol. 15, no. 6, Mar., pp. 3271-3284, 2007. (Correspondence author)(Q1, Cited 49) [7] Q. Hao, D. J. Brady, B. D. Guenther, J. Burchett, M. Shankar, and S. Feller, “Human tracking with wireless distributed pyroelectric sensors,” IEEE Sensors Journal, vol. 6, no. 6, Dec., pp. 1683-1696, 2006. (Q2, Cited 200) [6] J.-S. Fang, Q. Hao, D. J. Brady, B. D. Guenther, and K. Y. Hsu, “Real-time human identification using a pyroelectric infrared detector array and hidden Markov models,” Optics Express, vol. 14, no. 15, Jul., pp. 6643-6658, 2006.(Q2, Cited 86) [5] J.-S. Fang, Q. Hao, D. J. Brady, M. Shankar, B. D. Guenther, N. P. Pitsianis, and K. Y. Hsu, “Path-dependent human identification using a pyroelectric infrared sensor and Fresnel lens arrays,” Optics Express, vol. 14, no. 2, Jan., pp. 609-624, 2006. (Q1, Cited 104) [4] M. Shankar, J. Burchett, Q. Hao, B. D. Guenther, and D. J. Brady, “Human-tracking systems using pyroelectric infrared detectors,” Optical Engineering, no. 45, vol. 10, Dec., pp. 106401(1-10), 2006. (Q3, Cited 147) [3] Q. Hao, R. Cheng, G. Guo, S. Chen, and T.-S. Low, “A gradient based track-following controller optimization for hard disk drive,”IEEE Transactions on Industrial Electronics, vol. 50, no. 1, Feb., pp. 108-115, 2003. (Q1, Cited 11) [2] G. Guo, Q. Hao, and T.-S. Low, “A dual-stage control design for high track per inch hard disk drives,” IEEE Transactions on Magnetics, vol. 37, no. 2, Mar., pp. 860-865, 2001. (Q3, Cited 50) [1] Q. Hao, “A genetic algorithm with tabu list and sharing scheme for optimal design of electrical machines,” Electrical Machines and Power Systems, vol. 27, May, pp. 543-552, 1999. (Q4, Cited 6) 发表会议文章： [66] S. Chen, Y. Sun, D. Li, Q. Wang, Q. Hao and J. Sifakis,”Runtime safety assurance for learning-enabled control of autonomous driving vehicles,” IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, May 2022. (Correspondence author) [65] G. Ding, M. Zhang, E. Li, and Q. Hao, “JST: Joint self-training for unsupervised domain adaptation on 2D&3D object detection,” IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, May 2022. (Correspondence author) [65] S. Chen, R. Han, L. Zhao, S. Hang, Q. Hao, “Multi-robot feature-based slam using submap joining,” Australasian Conference on Robotics and Automation (ACRA), Dec. 2021. [64] L. Ding, D. Li, B. Liu, W. Lan, B. Bai, Q. Hao, W. Cao and K. Pei, “Capture uncertainties in deep neural networks for safe operation of autonomous driving vehicles,” IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA 2021), New York, USA, Oct. 2021. (best paper) (Correspondence author) [63] R. Ma and Q. Hao, “CS-Fnet: A Compressive sampling frequency neural network for simultaneous image compression and recognition,” IEEE Conference on Multi-Sensor Fusion and Integration (MFI), Bonn, Nov. 2021. (Correspondence author) [62] R. Ma, Y. Ding, and Q. Hao, “Compressive detection for camera array images,” IEEE Conference on Sensors, Sydney, Oct. 2021. (Corresponding author) [61] K. Huang and Q. Hao, “Joint multi-object detection and tracking with camera-LiDAR Fusion for autonomous driving,” IEEE International Conference on Intelligent Robots and Systems (IROS), Prague, Oct 2021. (Correspondence author) [60] X. Zheng, R. Gao, R. Ma, and Q. Hao, “Phase-SLAM: mobile structured light illumination for full body 3D scanning,” IEEE International Conference on Intelligent Robots and Systems (IROS), Prague, Oct 2021. (Correspondence author) [59] C. Li, D. Parker, and Q. Hao, “Vehicle dispatch in on-demand ride-sharing with stochastic travel time,” IEEE International Conference on Intelligent Robots and Systems (IROS), Prague, Oct 2021. (Correspondence author) [58] M. Xu, Y. Song, Y. Chen, S. Huang, and Q. Hao, “Invariant EKF based 2D active slam with exploration task,” IEEE International Conference on Robotics and Automation (ICRA), Xi’an, May 2021. [57] S. Zhang, L. Zhao, S. Huang, R. Ma, B. Hu, Q. Hao, “3D Reconstruction of deformable colon structures based on preoperative model and deep neural network”, IEEE International Conference on Robotics and Automation (ICRA), Xi’an, May 2021. (Correspondence author) [56] Z. Zhang, S. Wang, Y. Hong, L. Zhou, and Q. Hao, ” Distributed dynamic map fusion via federated learning for intelligent networked vehicles, ” IEEE International Conference on Robotics and Automation (ICRA), Xi’an, May 2021. (Correspondence author) [55] C. Li, D. Parker, and Q. Hao, “Optimal online dispatching for high-capacity shared autonomous mobility-on-demand systems,” IEEE International Conference on Robotics and Automation (ICRA), Xian, May 2021. (Correspondence author) [54] R. Han, S. Chen, Q. Hao, “A distributed range-only collision avoidance approach for low-cost large-scale multi-robot systems,” International Conference on Intelligent Robots and Systems (IROS), Nov. 2020.（Correspondence author） [53] S. Wang, R. Wang, Q. Hao, Y. Wu, H. Poor, “Learning centric power allocation for edge intelligence,” IEEE International Conference on Communications (ICC), Jun. 2020. (best paper) (Cited 7) [52] D. Li, Y. Wu, B. Bai, Q. Hao, “Behavior and interaction-aware motion planning for autonomous driving vehicles based on hierarchical intention and motion prediction,” IEEE Intelligent Transportation Systems Conference (ITSC), Jun. 2020. (Correspondence author) [51] E Li, S. Wang, C. Li, D. Li, X. Wu, Q. Hao, “SUSTech POINTS: a portable 3d point cloud interactive annotation platform system,” IEEE Intelligent Vehicles Symposium (IV), Feb. 2020. (Correspondence author) [50] Y. Sun, D. Li, X. Wu and Q. Hao, “Visual perception based situation analysis of traffic scenes for autonomous driving applications,” IEEE Intelligent Transportation Systems Conference (ITSC), May. 2020. (Correspondence author) [49] R. Han, S. Chen, Q. Hao, “Cooperative multi-robot navigation in dynamic environment with deep reinforcement learning,” IEEE International Conference on Robotics and Automation (ICRA), Paris, France, Jan. 2020. (Correspondence author) [48] F. Han, D. Li, Q. Hao, “Autonomous driving framework for bus transit systems towards operation safety and robustness,” IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, Nov. 2019. (Correspondence author) [47] H. Xu, G. Lan, S. Wu, Q. Hao, “Online intelligent calibration of cameras and LiDARs for autonomous driving systems,” IEEE Intelligent Transportation Systems Conference (ITSC), Auckland, Oct. 2019. (Cited 1) [46] F. Jiang and Q. Hao, “Pavilion: bridging photo-realism and robotics,” IEEE International Conference on Robotics and Automation (ICRA), Montreal, QC, May, 2019. (Cited 1) (Correspondence author) [45] G. Liu, R. Ma, Q. Hao, “A reinforcement learning based design of compressive sensing systems for human activity recognition,” IEEE Conference on Sensors, New Delhi, Oct. 2018 (best student paper 3rd prize). (Correspondence author) [44] S. Zhang, R. Han, W. Huang, S. Wang, Q. Hao, “Linear Bayesian filter based low-cost UWB systems for indoor mobile robot localization,” IEEE Conference on Sensors, New Delhi, Oct. 2018. (Cited 1) (Correspondence author) [43] F. Navan, B. Zhang, R. Ma, Q. Hao, “Anomaly detection and condition monitoring of UAV motors and propellers”, IEEE Conference on Sensors, New Delhi, Oct. 2018. (Cited 4) (Correspondence author) [42] F. Navan, B. Zhang, R. Ma, Q. Hao, “Non-intrusive human motion recognition using distributed sparse sensors and the genetic algorithm based neural network”, IEEE Conference on Sensors, New Delhi, Oct. 2018. (Cited 10) (Correspondence author) [41] R. Ma, G. Liu, Q. Hao, and C. Wang ,”Design of compressive imaging masks for human activity perception based on binary convolutional neural network”, IEEE Conference on Multi-Sensor Fusion and Integration (MFI), Daegu, Nov. 2017. (Cited 10) (Correspondence author) [40] Z. Luo, S. Wang, Q. Hao, and Z. Li, “Autonomous 3D modeling for robot arm based scanning,” IEEE Conference on Multi-Sensor Fusion and Integration (MFI), Daegu, Nov. 2017. (Cited 1) (Correspondence author) [39] S. Zhang, S. Wang, C. Li, G. Liu, and Q. Hao, “An integrated UAV navigation system based on geo-registered 3D point cloud,” IEEE Conference on Multi-Sensor Fusion and Integration (MFI), Daegu, Nov. 2017. (Cited 1) (Correspondence author) [38] R. Ma, Q. Hao, and C. Wang, “Smart microphone array design for speech enhancement in financial VR and AR,” IEEE Conference on Sensors, Glasgow, Nov. 2017. (Cited 1) (Correspondence author) [37] G. Lan, J. Liang, and Q. Hao, “Development of a smart floor for target localization with bayesian binary sensing,” IEEE Conference on Advanced Information Networking and Applications (AINA), Taipei, Mar.2017. (Cited 4) (Correspondence author) [36] G. Liu, J. Liang, G. Lan, Q. Hao, “Convolution neutral network enhanced binary sensor network for human activity recognition,” IEEE Conference on Sensors, Orlando, Nov. 2016. (Cited 11) (Correspondence author) [35] G. Lan, Z. Luo, and Q. Hao, “Development of a virtual reality teleconference system using distributed depth sensors,” IEEE Conference on Computer and Communications (ICC), Chengdu, Oct. 2016. (Cited 7) (Correspondence author) [34] T. Xiang, F. Jiang, J. Sun, G. Liu, G. Lan, Q. Hao, and C. Wang, “UAV based target tracking and recognition,” IEEE Conference on Multi-Sensor Fusion and Integration (MFI), Baden-Baden, Nov. 2016 (Finalist for the best paper). (Cited 7) (Correspondence author) [33] T. Xiang, F. Jiang, Q. Hao, and C. Wang, “Adaptive flight control for quadrotor UAVs with dynamic inversion and neural networks,” IEEE Conference on Multi-Sensor Fusion and Integration (MFI), Baden-Baden, Nov. 2016 (Finalist for the best paper). (Cited 5) (Correspondence author) [32] G. Lan, J. Sun, C. Li, Z. Ou, Z. Luo, J. Liang, and Q. Hao, “Development of UAV based virtual reality systems,” IEEE Conference on Multi-Sensor Fusion and Integration (MFI), Baden-Baden, Nov. 2016. (Cited 5) (Correspondence author) [31] G. Lan, Y. Bu, J. Liang, and Q. Hao, “Action synchronization between human and UAV robotic arms for remote operation,” IEEE Conference on Mechatronics and Automation (ICMA), Harbin, Sept. 2016. (Cited 5) (Correspondence author) [30] G. Lan, Q. Hao, X. Hu, “A Bayesian approach for target localization with binary sensor networks,” International Symposium on Computational Intelligence and Design (ISCID), Hangzhou, Nov. 2015. (Cited 6) (Correspondence author) [29] Q. Hao, “Binary sensing and perception for human behavior study,” IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP), Chengdu, Jul. 2015. [28] R. Ma, Q. Hao, and X. Li, “Active sensing of indoor human scenarios through mobile pyroelectric infrared sensors,” IEEE Conference on Sensors, Baltimore, MD, Oct. 2013. (Cited 2) (Correspondence author) [27] J. Lu, J. Gong, Q. Hao, and F. Hu, “Multi-agent based wireless pyroelectric infrared sensor networks for multi-human tracking and self-calibration,” IEEE Conference on Sensors, Baltimore, MD, Oct. 2013 (best student paper). (Cited 16) (Correspondence author) [26] R. Ma and Q. Hao, “A wireless laser sensor web for human gait disorder recognition based on the Buon’s needle model,” IEEE Conference on Sensors, Baltimore, MD, Oct. 2013. (Cited 1) (Correspondence author) [25] Q. Sun, R. Ma, Q. Hao, and F. Hu, “Space encoding based human activity modeling and situation perception,” IEEE Conference on Cognitive Methods in Situation Awareness and Decision Support , pp. 186-189, San Diego, CA, Mar. 2013 (CogSIMA). (Cited 9) (Correspondence author) [24] Q. Hao “Cognitive sensing for distributed behavioral biometrics,” IEEE Conference on Cognitive Methods in Situation Awareness and Decision Support, pp. 101-104, San Diego, CA, Mar. 2013. (Cited 9) (Correspondence author) [23] Q. Hao, “An integral and differential geometric approach to behavioral information acquisition and integration via binary sensor networks,” IEEE Conference on Sensors (CogSIMA)., pp. 834-837, Taipei, Oct. 2012. (Cited 9) (Correspondence author) [22] J. Gong, L. Zhao, Q. Hao, F. Hu, and X. Hong, “A reconfigurable hardware platform for cognitive sensor networks towards behavioral biometrics,” IEEE Conference on Sensors, pp. 838-841, Taipei, Oct. 2012, (Cited 4) (Correspondence author) [21] R. Ma and Q. Hao, “Buffon’s needle model based walker recognition with distributed binary sensor networks,” IEEE Conference on Multiple Sensor Fusion and Integration (MFI), pp. 120-125, Hamburg, Sep. 2012, (Cited 14) (Correspondence author) [20] J. Lu, J. Gong, Q. Hao, and F. Hu，”Space encoding based compressive multiple human tracking with distributed binary pyroelectric infrared sensor networks,” IEEE Conference on Multiple Sensor Fusion and Integration (MFI), Sep. 2012, pp. 180-185 (Finalist of the best paper). (Cited 32) (Correspondence author) [19] T. Yue, Q. Hao, and D. Brady, “Distributed binary geometric sensor arrays for low-data-throughput human gait biometrics,” IEEE Workshop on Sensor Array Multichannel Signal Processing (SAM), pp. 465-468, Hoboken, NJ, June, 2012. (Cited 10) (Correspondence author) [18] F. Hu, Q. Hao, and D. McCallum, “Multi-dimensional tele-healthcare engineering undergraduate education via Building-Block-based medical sensor labs,” Annual Conference and Exposition, Conference Proceedings (ASEE), June, 2011. [17] K. Vu, R. Zheng, and Q. Hao, “Multi-target tracking in distributed active sensor networks,” IEEE Military Communications Conference (MILCOM), pp. 1044-1049, San Jose, CA, Nov. 2010. (Cited 10) [16] Q. Hao and F. Hu, “A design of compressive EEG sensors,” IEEE Conference on Sensors, Nov. 2010, pp. 318-322. [15] Q. Hao, F. Hu, and J. Lu, “Distributed multiple human tracking with wireless binary pyroelectric (PIR) sensor networks,” IEEE Conference on Sensors, pp. 946-950, Kona, HI, Nov. 2010. (Cited 39) [14] F. Hu, Q. Sun, and Q. Hao, “Mobile targets region-of-interest via distributed pyroelectric sensor network: towards a robust, real-time context reasoning,” IEEE Conference on Sensors, pp. 1832-1836, Kona, HI, Nov. 2010. (Cited 14) [13] X, Zhou, Q. Hao, and F. Hu, “1-bit walker recognition with distributed binary pyroelectric sensors,” IEEE Conference on Multiple Sensor Fusion and Integration (MFI), pp. 156-161, Salt Lake City, UT, Sept. 2010. (Cited 14) (Correspondence author) [12] Q. Sun, F. Hu, and Q. Hao, “Context awareness emergence for distributed binary pyroelectric sensors,” IEEE Conference on Multiple Sensor Fusion and Integration (MFI), pp. 150-155, Salt Lake City, UT, Sept. 2010. (Cited 27) [11] F. Hu, Y. Wu, and Q. Hao, “Primate-teaming-inspired mobile sensor network topology auto-formation modeling,” the 1st International Conference on Sensor Networks and Their Applications (SNA), pp. 142-147, San Francisco, California. [10] Y. Wang, Q. Hao, A. Fatehpuria, L. G. Hassebrook, and D. L. Lau, “Data acquisition and quality analysis of 3-dimensional ngerprints,” the 1st IEEE Conference on Biometrics (SNA), Identity, and Security, pp. 1-9, Tampa, FL, Sep. 2009. (Cited 30) [9] C. Li, Q. Hao, W. Guo, and F. Hu, “A hybrid approach for compressive neural activity detection with functional MR images,” the 31th IEEE Conference on Engineering in Medicine and Biology Society (EMBC), pp. 4787-4790, Minneapolis, MN. (Cited 4) [8] F. Hu, Q. Hao, M. Qiu and Y. Wu, “Low-power electroencephalography sensing data RF transmission: hardware architecture and test,” The 1st ACM International Workshop on Medical-grade Wireless Networks (WiMD), pp. 57–62, New Orleans Louisiana, April 2009. (Cited 7) [7] N. Li and Q. Hao, “Multiple human tracking with wireless distributed pyroelectric sensors,” SPIE Defense and Security, pp. 694033(1-12) , Orlando, Florida, Mar. 2008. (Cited 14) (Correspondence author) [6] N. Li and Q. Hao, “Multiple walker recognition with wireless distributed pyroelectric sensors,” SPIE Defense and Security, pp. 694034(1-12) , Orlando, Florida, Mar. 2008. (Cited 5) (Correspondence author) [5] Y. Wang, K. Liu, Q. Hao, D. L. Lau, and L. G. Hasserbrook, “Multicamera phase measuring profilometry for accurate depth measurement,” SPIE Sensors and Systems for Space Applications, pp. 655509(1-12), Orlando, Florida, May. 2007. (Cited 22) [4] Q. Hao and etc., “A self-tuning robust control for sampled-data HDD servo systems,” American Contr. Conference, pp. 3843-3848, Arlington, VA, June. 2001. (Cited 4) [3] G. Guo, Q. Hao, and T.-S. Low, “Access system requirement for high track per inch hard disk drives,” Asia-Pacic Magn. Recording Conference, TA1/1-TA1/2, Tokyo, Nov. 2000. (Cited 7) [2] Q. Hao and etc., “An optimal multirate control design with robustness specication for sampled-data HDD servo systems,” the 39th IEEE Conference on Decision and Control (CDC), pp. 3100-3105, Sydney, NSW, Dec. 2000. (Cited 7) [1] Q. Hao and etc., “TMR online optimization using quasi-newton method for HDD servo systems,” American Contr. Conference, pp. 3412-3416, Chicago, IL, June 2000. (Cited 7) 编写著作： [1] F. Hu and Q. Hao (Editors), “Intelligent sensor networks: the integration of sensor networks, signal processing and machine learning,” CRC Press, 2012. 新闻动态 更多新闻 南科大举办人工智能与自动驾驶技术研讨会 2019-10-21 南方科技大学郝祁副教授与英特尔智能网联汽车大学合作研究中心签订合作协议 2019-03-01 南方科技大学智能交通中心签约暨捐赠仪式——打造智能交通科研平台 推动校企产学研合作新模式 2018-05-04 团队成员 查看更多 PrevNext UpDown 加入团队 南科大智能交通中心研究助理教授岗位职责: 制定自动驾驶技术路线，指导设计具备高效、安全和可扩展性的自动驾驶软件体系架构，把控自动驾驶系统的感知、决策和控制算法的研究和实现。引领团队的自动驾驶技术迈入国际先进水平。 指导博士、硕士研究生，并参与日常实验室管理和运作。 协助中心负责人制定研究计划、申请研究项目。 可以独立申请研究经费来支持课题研究 独立地完成课题研究，发表具有国际竞争力的高水平学术论文。 获得外部竞争性经费后，分担课题组的助研费用和实验室运行费用。招聘条件: 在计算机、电子、机械或相关领域获得博士学位两年以上（或满足深圳市孔雀计划C类人才要求），海外或国内知名大学/研究机构从事博士后或研究工作经历。 对以下自动驾驶相关领域有深入的理解和经历：高精度地图与多传感数据的融合和定位、目标识别与追踪；三维高级地图建立与定位导航、SLAM；路径规划与车辆调度、智能网联车辆系统、智能交通规划；系统健壮优化、分布式计算、仿真与虚拟环境。 热爱科研、具有高度积极性、专业性及团队协作精神。 近5年发表不少于3篇高水平论文。 适应多文化工作环境，英文水平优秀。薪资待遇： 南科大工作人员提供优厚的薪酬待遇和适宜的工作条件。相关福利参照深圳市的有关规定执行。待遇从优，根据申请人能力与资历而定。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn南科大智能交通中心博士后岗位职责: 自动驾驶关键技术和标准的研究，完成自动驾驶系统框架和模块化设计，掌握核心技术。 能够相对独立的进行课题研究并发表高水平国际论文。 能够协助课题组经费申请。 能够协助实验室建设和管理。 能够指导博士、硕士研究生开展科研工作。 协助教学培训等工作。招聘条件: 在计算机、电子或相关领域获得博士学位； 机器视觉slam的自动驾驶定位，具备深度学习的环境感知，视觉感知，目标检测、分割和跟踪、高精度地图和路径规划；多传感器数据融合、驾驶决策算法和控制系统研究；自动驾驶仿真和虚拟环境搭建。 较强的系统集成、软件设计与研究技能，在ML、CV、AI领域的顶级会议或者期刊发表过论文，掌握核心算法，具备一定的行业地位和影响力。 适应多文化工作环境，具有优秀的英语写作能力和表达能力者优先。 深圳市对博士后待遇优厚，可申请各项人才补贴。薪资待遇： 参照《南科大博士后管理办法》及深圳市相关条例，年薪不少于30万元（含市政补贴税后18万元/年），享受正式教职工待遇；优秀者可申请校长卓越博士后，年薪高达40万/年。符合条件者可申请深圳政府高层次人才、孔雀人才计划等政策待遇。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn智能控制研发工程师岗位职责: 负责智能驾驶系统需求分析、方案设计与论证等同步开发工作 负责智能驾驶控制系统及执行控制系统开发需求定义、技术指标的设定、系统接口定义等，并下发相关要求给相关零部件 负责系统控制策略与系统设计逻辑的开发 负责智能驾驶系统与整车其他系统、智慧交通ITS系统的需求分析与集成设计 负责设计过程中问题分析与设计改进及技术更新 负责智能驾驶系统的知识工程建设与能力建设招聘条件: 具有机器人、无人机、自动驾驶领域的控制系统设计、算法开发、动态系统建模的专业知识，针对实际被控对象进行模块化设计和调试的经验 对于汽车动力学模型具有一定的了解；熟练掌握频域、时域中控制器设计与分析方法；熟练掌握动态系统建模及参数辨识方法，掌握MPC，自适应控制等先进控制技术 具备自动驾驶系统、智能驾驶、ADAS系统、智慧交通设计3年以上工作经验优先 良好的团队合作精神，良好的协调与沟通能力，善于表达 可适应多文化工作环境，英语水平良好薪资待遇： 南科大工作人员提供优厚的薪酬待遇和适宜的工作条件。相关福利参照深圳市的有关规定执行。待遇从优，根据申请人能力与资历而定。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn感知融合工程师岗位职责: 负责自动驾驶系统感知算法相关的研发，包括但不限于：3D点云障碍物识别、图像处理、语义分割（2D/3D）、深度学习和传感器融合等 负责多传感器融合系统的架构设计、相关算法的研究、设计和集成 负责ADAS系统多传感器（毫米波雷达、视觉等）数据预处理及目标识别算法开发 能够协助实验室建设和管理，辅助其他科研人员开展科研工作，协助教学培训等工作 申请相关专利招聘条件: 优秀的编程能力，熟练掌握C/C++或Python，熟悉Linux系统 掌握计算机相关基础知识，具备优秀的数学能力，熟悉常用的机器学习算法与理论，有在深度学习平台如Caffe或Tensorflow的工作经验 熟悉3D点云障碍物识别、图像处理、语义分割（2D/3D）、深度学习和传感器融合等相关内容 有Lidar, Camera, Radar等传感器融合经验的优先 在CV领域发表高质量论文、熟悉GPU编程及并行计算的优先 可适应多文化工作环境，英语水平良好薪资待遇： 南科大工作人员提供优厚的薪酬待遇和适宜的工作条件。相关福利参照深圳市的有关规定执行。待遇从优，根据申请人能力与资历而定。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn仿真系统工程师岗位职责: 无人车仿真平台构建，无人车仿真技术研发 三维重建、传感器模拟、虚拟场景生成等仿真相关工作 配合各团队完成各类仿真验证、训练研发工作 能够协助实验室建设和管理，辅助其他科研人员开展科研工作，协助教学培训等工作 申请相关专利招聘条件: 掌握Unreal、Unity等工具或其它类似游戏引擎 了解Prescan、Carsim、Vrep等工具 熟练C 、Python、Nodejs中至少一种研发工具 熟悉数据结构和算法 熟悉Linux优先；至少熟悉一种仿真环境以及相应的的remote API接口编程 在以下领域有研究或实践者加分：虚拟世界仿真建模、点云处理、图像生成、三维重建、地图 可适应多文化工作环境，英语水平良好，良好的沟通表达和团队合作薪资待遇： 南科大工作人员提供优厚的薪酬待遇和适宜的工作条件。相关福利参照深圳市的有关规定执行。待遇从优，根据申请人能力与资历而定。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn规划控制工程师岗位职责: 负责自动驾驶汽车相关各个模块算法的研发工作，包括但不限于：环境感知算法研发，路径规划与控制算法研发、定位算法研发等，同时参与车载自动驾驶系统的工程化实现 实现自动驾驶系统中基于高精度地图导航的相关算法，主要包括但不限于:①基于导航地图数据的路径规划，车道规划，道路模式识别，车道定位等模块的设计和实现；②设计各类相关算法的测试和验证流程；③参与地图方面数据算法自动测试的研发工作；④参与地图数据接口的设计 开发设计算法来解决在真实世界的复杂环境中自动驾驶的决策问题 能够协助实验室建设和管理，辅助其他科研人员开展科研工作，协助教学培训等工作 申请相关专利招聘条件: 计算机，自动化，地理信息系统，电子工程，车辆工程，航空航天等相关专业，本科以上学历 熟悉Linux操作系统，ROS系统，熟悉数据结构，熟悉最优路径规划，决策树模型，优化理论等相关算法 熟练掌握dijkstra, astar算法,熟悉OMLP库，熟悉现代控制理论 熟练掌握C++、Python等语言程序设计及各类 STL 库的使用，或者熟练使用Matlab/Simulink工具，具有良好编程习惯 具有较强的动手能力，善于解决实际问题；具有良好的沟通能力，良好的团队合作精神 可适应多文化工作环境，英语水平良好以下为加分项：具有良好的控制系统设计、信号滤波处理、动态系统建模的专业知识；熟悉深度学习，强化学习相关算法，例如RNN，LSTM，Deep Q-Learning等，掌握一种深度学习框架；熟悉计算几何相关的基础理论，熟悉样条函数，Bézier曲线、曲线/曲面细分方法等相关理论；具有良好的控制系统设计，动态系统建模的专业知识，有无人车控制系统设计经验；有高级辅助驾驶功能（例如ACC、AEB、LKA）开发经验；具有ADAS整车集成或集成测试经验，熟悉整车构造，汽车电子，汽车总线网络；薪资待遇： 南科大工作人员提供优厚的薪酬待遇和适宜的工作条件。相关福利参照深圳市的有关规定执行。待遇从优，根据申请人能力与资历而定。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn系统集成工程师岗位职责: 负责自动驾驶系统模块化、可验证的系统软件架构设计和实时性能优化，集成、测试并优化自动驾驶系统 负责自动驾驶系统在车载嵌入式平台集成调试 负责把算法模块转化为功能完整的产品 深入参与无人车整车软硬件联合调试与系统集成 能够协助实验室建设和管理，辅助其他科研人员开展科研工作，协助教学培训等工作 申请相关专利招聘条件: 在计算机、电子、机械或相关领域获得硕士学位 熟悉自动驾驶系统传感器技术，如摄像头、毫米波雷达、激光雷达等 熟练掌握嵌入式开发和性能调优，有嵌入式软件的开发和测试经验者优先 有计算机视觉、深度学习和ROS开发经验优先，熟悉NVIDIA Drive PX或Jetson TX等嵌入式平台优先，熟悉can总线协议的优先 具有一定的算法实现能力，C++/python, 熟悉Linux编程环境 可适应多文化工作环境，英语水平良好薪资待遇： 南科大工作人员提供优厚的薪酬待遇和适宜的工作条件。相关福利参照深圳市的有关规定执行。待遇从优，根据申请人能力与资历而定。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn研究助理岗位职责: 能够相对独立的进行课题研究并撰写英文论文 能够协助课题组经费申请 能够协助实验室建设和管理 能够指导硕士生、本科生开展科研工作 协助教学培训等工作 完成智能交通中心PI交代的其他事项招聘条件: 在计算机、电子、机械或相关领域获得硕士学位 对以下两个以上方向有深入的了解与研究：图像和三维点云等传感数据的数据融合、语义分割、目标识别与追踪；三维高级地图建立与定位导航、SLAM；路径规划与车辆调度、智能网联车辆系统、智能交通规划；系统健壮优化、分布式计算、仿真与虚拟环境、区块链 较强的系统集成能力与编程能力，数学基础良好、动手能力强的优先 能在国际主流刊物发表高水平学术论文 适应多文化工作环境，英文水平良好 工作主动、踏实认真、责任心强，做事有条理，执行力强；具备良好的沟通、组织、协调能力和团队协作精神薪资待遇： 南科大工作人员提供优厚的薪酬待遇和适宜的工作条件。相关福利参照深圳市的有关规定执行。待遇从优，根据申请人能力与资历而定。简历投递： 请提供中英文简历，邮件标题中请注明应聘岗位名称，投递至hao.q@sustech.edu.cn 查看更多 联系我们 联系地址 深圳市南山区学苑大道1001号南山智园A7栋906 办公电话 086-0755-88018537 电子邮箱 hao.q@sustech.edu.cn |
