杨超然

博士，研究员，研究组组长

Email: yangchaoran@@gdiist.cn

主要研究方向:

类脑计算模型与系统、机器人视觉感知与控制、视觉-语言模型

目前致力于开发基于类脑计算及深度学习的开放环境视觉智能机器人算法-软件-芯片优化系统及关键技术。

个人简介:

2016年毕业于澳门大学电机与电子工程系、模拟与混合信号超大规模集成电路国家重点实验室，从事超低功耗CMOS心电图检测算法及专用数字处理器芯片的研究，获哲学博士学位。曾任澳门大学模拟与混合信号超大规模集成电路国家重点实验室技术员、职能主管。2017-2023年在深圳市华为技术有限公司从事昇腾AI处理器、深度学习算法与系统、图像与视频检测分析、数字人与具身智能、自动驾驶鸟瞰环视视觉感知等研究、开发工作，并负责多项与知名高校的技术研究合作。

曾获ISSCC参与赞助奖、第三届华为公司十大发明奖等奖项。发表SCI期刊及国际会议论文20篇，中国专利3项，美国、欧洲专利各1项。相关研究成果在IEEE Transactions on Biomedical Circuits and Systems, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, International Solid-State Circuits Conference (ISSCC) SRP, IEEE International Conference on Consumer Electronics (ICCE), Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)等期刊与会议上发表。其中发表于“IEEE Transactions on Biomedical Circuits and Systems”的关于“超低功耗心电图 QRS 波检测处理器架构”的学术 论文被两篇Nature Scientific期刊论文、一本学术专著书籍，以及该子领域论文广泛引用。

研究组简介:

自然界中生物的智能存在于其身体之中，而身体则存在于三维物理世界中。具身智能研究的动机是将智能置于三维物理世界的真实约束中，关注智能体的看、听、说、推理和行动，以更“类人”的方式对环境进行感知、理解、交互，并获取知识。具身智能这一场景约束具有普遍性，同时使得智能的研究更具针对性。具身智能领域吸引来自计算机视觉、语言、图形和机器人等跨学科的研究人员，包括李飞飞等知名研究者，解决具身智能领域的共同问题，推进数字人与机器人、自动驾驶、人机交互等多个领域的发展。近期，语言基础模型的发展为基于自然语言模型的推理能力带来了显著提升，为视觉-语言模型提供了新机会。课题组期望结合视觉感知和语言推理能力，以应对现实世界中复杂多样的场景挑战。

类脑计算是一种创新的计算技术，它借鉴了脑科学的基本原理，从算法层面模拟人脑神经元和突触的信息处理机制，并在芯片架构上突破传统“冯诺依曼”架构的限制，被普遍认为具有高能源效率的显著特点。近期，类脑计算取得了进一步的发展。如IBM继True North类脑AI芯片后，在2023年第四季发布了North Pole芯片，其在ResNet-50模型上测试的能效是相同工艺GPU竞品的25倍； Intel推出了Lolhi 2类脑芯片；OpenAI对类脑芯片进行了投资；Science Robotics期刊发表多篇类脑计算与仿生机器人的文章；世界多国以及我国的脑计划也大力支持新型类脑芯片及计算系统的研发。

具身智能机器人在开放环境中的应用需要解决三维空间中复杂物体的感知与操作问题，以及如何在本地实现高性能、高能效智能计算的问题。因此，本课题组目前专注于类脑视觉算法与系统、基于视觉-语言模型的具身智能机器人的技术研究，同时也致力于相关软硬件优化系统的研发。期望通过视觉-语言模型解决具身智能机器人的多样复杂场景适应问题，以及通过类脑计算与软硬件优化系统解决机器人本地算力的高效计算问题。

本课题组招聘博士后、工程师、实习生（软硬件系统、FPGA/ASIC、AI Processor、视觉计算、机器人学习、类脑算法），感兴趣的同学，请邮件联系。

代表论著：

International Journal Papers

[1] Boyu Zheng, et.al. "A Scheme for Solving Fuzzy Motion Planning for Manipulators", Submitted to IEEE Transactions on Systems, Man, and Cybernetics, 2024.

[2] Boyu Zheng, et.al. "A Hybrid-Gain ZNN and Its Application in Robotic Arm", Submitted to IEEE Transactions on Neural Networks and Learning Systems, 2024.

[3] Xie, Xinyu, et al. "Fusionmamba: Dynamic feature enhancement for multimodal image fusion with mamba." arXiv preprint arXiv:2404.09498, 2024.

[4] L. Zhao, R. Xu, T. Wang, T. Tian, X. Wang, W. Wu, C. Ieong, X. Jin, "BaPipe: Balanced Pipeline Parallelism for DNN Training", Parallel Processing Letters, 2022.

[5] Chio-In Ieong, Mingzhong Li, Man-Kay Law, Pui-In Mak, Mang I Vai, and Rui P. Martins, “A 0.45-V 147-to-375 nW ECG Compression Processor with Wavelet Shrinkage and Adaptive Temporal Decimation Architectures”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Apr. 2017.

[6] Ming-Zhong Li, Chio-In Ieong, Man-Kay Law, Pui-In Mak, Mang-I Vai, Sio-Hang Pun, and Rui P. Martins, "Energy Optimized Subthreshold VLSI Logic Family With Unbalanced Pull-Up/Down Network and Inverse Narrow-Width Techniques," IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 23, no. 12, pp. 3119-3123, Dec. 2015.

[7] Chio-In Ieong, Pui-In Mak, Chi-Pang Lam, Cheng Dong, Mang-I Vai, Peng-Un Mak, Sio-Hang Pun, Feng Wan, and Rui P. Martins, "A 0.83-μW QRS Detection Processor Using Quadratic Spline Wavelet Transform for Wireless ECG Acquisition in 0.35-μm CMOS," IEEE Transactions on Biomedical Circuits and Systems, vol. 6, pp. 586-595, Dec. 2012. [Leading work in its field. Citations (Google Scholar)= 137 including citations from a book and two Nature Scientific Reports.]

International Conference Papers

[8] Hang Yu, et. al., “SDP: Spiking Diffusion Policy for Robotic Arm Action Generation”, China Biomedical Engineering Conference, oral presentation, accepted, 2024.

[9] “SDP: Spiking Diffusion Policy for Robotic Manipulation with Learnable Channel-wise Membrane Thresholds”, Nature Conference on Neuromorphic Computing, 2024, accepted.

[10] Chio-In Ieong, Mingzhong Li, Man-Kay Law, Pui-In Mak, Mang I Vai and Rui P. Martins, “A 0.45V 147-to-375nW Hardware-Efficient Real-Time ECG Processor with Lossless-to-Lossy Data Compression for Wireless Healthcare Wearables”, Presentation at the 2016 International Solid-State Circuits Conference (ISSCC 2016) Student Research Preview session, Jan. 2016, San Francisco, United States.

[11] Chio-In Ieong, Pui-In Mak, Mang-I Vai and Rui P. Martins, “Sub-μW QRS Detection Processor Using Quadratic Spline Wavelet Transform and Maxima Modulus Pair Recognition for Power-Efficient Wireless Arrhythmia Monitoring”, in Proc. of The 21st Asia and South Pacific Design Automation Conference - University Design Contest (ASP-DAC UDC 2016), Jan. 2016, Macau, China.

[12] Chio-In Ieong, Mingzhong Li, Man-Kay Law, Pui-In Mak, Mang I Vai, Peng-Un Mak, Feng Wan, Rui P. Martins, "Standard cell library design with voltage scaling and transistor sizing for ultra-low-power biomedical applications," in Proc. of 2013 IEEE International Conference of Electron Devices and Solid-State Circuits (EDSSC), Jun. 2013, Hong Kong, China

[13] Ming-zhong Li, Chio-In Ieong, Man-Kay Law, Pui-In Mak, Mang I Vai, and Rui P. Martins, "Sub-threshold standard cell library design for ultra-low power biomedical applications," in Proc. of 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1454-1457, Jul. 2013, Osaka, Japan

[14] Chio-In Ieong, C. Dong, W. Nan, A. Rosa, R. Guimarães, M.-I Vai, P. U. Mak, “A snoring classifier based on Heart Rate Variability analysis”, Computing in Cardiology, pp. 345-348, Sep. 2011.

[15] Chio-In Ieong, Mang I Vai, Peng-Un Mak, and Pui-In Mak, "ECG heart beat detection via Mathematical Morphology and Quadratic Spline wavelet transform," in Proc. of 2011 IEEE International Conference on Consumer Electronics (ICCE), 2011, pp. 609-610, Jan. 2011, Las Vegas, USA

[16] Chio In Ieong, Mang I Vai, and Peng Un Mak, “ECG QRS Complex Detection with Programmable Hardware”, in Proc. of The 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2008). 2008: Vancouver, Canada.

[17] Chio In Ieong, Feng Wan, Mang I Vai, Peng Un Mak, “QRS Complex Detector Using Artificial Neural Network”, in Proc. of the 4th Regional Inter-University Postgraduate Electrical and Electronics Engineering Conference (RIUPEEEC2006). 2006: Macau SAR., China. [My 1st paper, NN for detection]

Patents

[18] Zhenjiang Dong, Chio-In Ieong, Hu Liu, Hai Chen, "Matrix processing method and device and logic circuit", US11734386B2, CN111010883B

[19] Zhenjiang Dong, Chio-In Ieong, Hu Liu, Hai Chen, "Convolutional Method and Device for Neural Network", CN112106034A

[20] Chenglin Zheng, Chio-In Ieong, Hai Chen, "Image processing method and apparatus based on convolutional neural network", CN110321996B