楊超然

博士，研究員(yuán)，研究組組長

Email: yangchaoran@@gdiist.cn

主要研究方向:

類腦計算模型與系統、機器人視覺感知(zhī)與控制、視覺-語言模型

目前緻力于開(kāi)發基于類腦計算及深度學習的開(kāi)放(fàng)環境視覺智能機器人算法-軟件-芯片優化系統及關鍵技術。

個人簡介:

2016年畢業于澳門大(dà)學電(diàn)機與電(diàn)子工(gōng)程系、模拟與混合信号超大(dà)規模集成電(diàn)路國家重點實驗室，從事超低功耗CMOS心電(diàn)圖檢測算法及專用數字處理器芯片的研究，獲哲學博士學位。曾任澳門大(dà)學模拟與混合信号超大(dà)規模集成電(diàn)路國家重點實驗室技術員(yuán)、職能主管。2017-2023年在深圳市華爲技術有限公司從事昇騰AI處理器、深度學習算法與系統、圖像與視頻(pín)檢測分(fēn)析、數字人與具身智能、自動駕駛鳥瞰環視視覺感知(zhī)等研究、開(kāi)發工(gōng)作，并負責多項與知(zhī)名高校的技術研究合作。

曾獲ISSCC參與贊助獎、第三屆華爲公司十大(dà)發明獎等獎項。發表SCI期刊及國際會議論文20篇，中(zhōng)國專利3項，美國、歐洲專利各1項。相關研究成果在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)等期刊與會議上發表。其中(zhōng)發表于“IEEE Transactions on Biomedical Circuits and Systems”的關于“超低功耗心電(diàn)圖 QRS 波檢測處理器架構”的學術 論文被兩篇Nature Scientific期刊論文、一(yī)本學術專著書(shū)籍，以及該子領域論文廣泛引用。

研究組簡介:

自然界中(zhōng)生(shēng)物(wù)的智能存在于其身體(tǐ)之中(zhōng)，而身體(tǐ)則存在于三維物(wù)理世界中(zhōng)。具身智能研究的動機是将智能置于三維物(wù)理世界的真實約束中(zhōng)，關注智能體(tǐ)的看、聽(tīng)、說、推理和行動，以更“類人”的方式對環境進行感知(zhī)、理解、交互，并獲取知(zhī)識。具身智能這一(yī)場景約束具有普遍性，同時使得智能的研究更具針對性。具身智能領域吸引來自計算機視覺、語言、圖形和機器人等跨學科的研究人員(yuán)，包括李飛飛等知(zhī)名研究者，解決具身智能領域的共同問題，推進數字人與機器人、自動駕駛、人機交互等多個領域的發展。近期，語言基礎模型的發展爲基于自然語言模型的推理能力帶來了顯著提升，爲視覺-語言模型提供了新機會。課題組期望結合視覺感知(zhī)和語言推理能力，以應對現實世界中(zhōng)複雜(zá)多樣的場景挑戰。

類腦計算是一(yī)種創新的計算技術，它借鑒了腦科學的基本原理，從算法層面模拟人腦神經元和突觸的信息處理機制，并在芯片架構上突破傳統“馮諾依曼”架構的限制，被普遍認爲具有高能源效率的顯著特點。近期，類腦計算取得了進一(yī)步的發展。如IBM繼True North類腦AI芯片後，在2023年第四季發布了North Pole芯片，其在ResNet-50模型上測試的能效是相同工(gōng)藝GPU競品的25倍； Intel推出了Lolhi 2類腦芯片；OpenAI對類腦芯片進行了投資(zī)；Science Robotics期刊發表多篇類腦計算與仿生(shēng)機器人的文章；世界多國以及我(wǒ)(wǒ)國的腦計劃也大(dà)力支持新型類腦芯片及計算系統的研發。

具身智能機器人在開(kāi)放(fàng)環境中(zhōng)的應用需要解決三維空間中(zhōng)複雜(zá)物(wù)體(tǐ)的感知(zhī)與操作問題，以及如何在本地實現高性能、高能效智能計算的問題。因此，本課題組目前專注于類腦視覺算法與系統、基于視覺-語言模型的具身智能機器人的技術研究，同時也緻力于相關軟硬件優化系統的研發。期望通過視覺-語言模型解決具身智能機器人的多樣複雜(zá)場景适應問題，以及通過類腦計算與軟硬件優化系統解決機器人本地算力的高效計算問題。

本課題組招聘博士後、實習生(shēng)、工(gōng)程師（軟硬件系統、視覺計算與仿真、機器人、類腦算法），感興趣的同學，請郵件聯系。

代表論著：

International Journal Papers

[1] 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.

[2] 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.

[3] 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.

[4] 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

[5] 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.

[6] 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.

[7] 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

[8] 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

[9] 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.

[10] 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

[11] 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.

[12] 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

[13] Zhenjiang Dong, Chio-In Ieong, Hu Liu, Hai Chen, "Matrix processing method and device and logic circuit", WO2020029018A1, US20200265108A1, EP3690679A4, CN113190791A

[14] Zhenjiang Dong, Chio-In Ieong, Hu Liu, Hai Chen, "Convolutional Method and Device for Neural Network", WO2020010639A1, CN112106034A

[15] Chenglin Zheng, Chio-In Ieong, Hai Chen, "Image processing method and apparatus based on convolutional neural network", WO2019184888A1, CN110321996B