Narrative CV

楊富量博士，現任特聘研究員暨教授，專精於以光體積變化描記法(Photoplethysmography, PPG)進行非侵入式血糖(Non-invasiveBloodGlucose, NIBG)量測技術。楊教授原本亦專注於心腦血管疾病物理性治療的研究，但因技術已完成專屬技轉，該領域研究已正式終止。他於英國劍橋大學取得博士學位。在2013年之前，曾任台積電5奈米CMOS前瞻計畫經理，以及國家奈米元件實驗室主任。

主要研究成果與影響如下:

1. 2024年國家新創獎(技術非專屬轉移進行中)　創新耳機型含血壓等多功能生理感測器與居家智慧醫療應用
2. 2022年國家新創獎(技術非專屬轉移)　AI演繹法非侵入式血糖機
3. 2020年國家新創獎(技術專屬轉移並成功衍生新創公司)　螺旋體外反搏系統(HelixExternalCounterPulsationSystem)

楊教授及其團隊的最新一代非侵入式血糖量測技術已成功應用於空腹血糖的測量，但在飯後血糖的準確性表現仍有待提升。為克服飯後血糖偵測的挑戰，他們將進一步開發全新的人工智慧演算法，並與台北慈濟醫院合作，針對加護病房病患進行資料收集。首要的合作目標，是能夠即時偵測低血糖，或進行早期預測以提供預警。

Education

• Ph.D., Dept. of Materials Science and Metallurgy, University of Cambridge, UK, 1991–1994
• B.S., Dept. of Materials Science and Engineering, NTHU, Taiwan, R.O.C. 1985–1989

Positions and Career

• 中央研究院應用科學研究中心 特聘研究員 (2013.08-Present)
• 中央研究院智財技轉處 處長 (2013.08-2016.09)
• 國家奈米元件實驗室 特聘研究員 (2008.08-2013.08)
• 國家奈米元件實驗室 主任 (2008.08-2013.05)
• 台積科技院 科技委員 (2004)
• 台積電研究發展組織 先後擔任副理、經理、部門經理及副處長 (2000.3-2008.7)
• 世界先進 研究開發處元件部 先後擔任主任工程師與副理 (1994.12-2000.3):

Honors and Awards

重要奬項

• 2024 國家新創奬(創新耳機型含血壓等 多功能生理感測器 與居家智慧醫療應用)
• 2022 國家新創奬(AI 演繹法非侵入式血糖機)
• 2020 國家新創奬(螺旋型體外反搏系統)
• 2004 「優秀青年工程師」獎章 (中國工程師學會)
• 2004 台積科技院第二屆科技委員
• 2004 台積電 Innovation Award (台積電研發最高獎項)
• 2006 台積電公司頒發“Best Invention Disclosures Award”(for an outstanding transistor structure invention)
• 1999 於世界先進積體電路公司任職期間(1994-1999)因負責領導開發關鍵技術的元件淺溝渠隔離(STI)，榮獲公司頒發“0.19微米64百萬位元SDRAM試製成功獎”

國際研討會邀請專題演講

• 2023 “Optical Sensing for Non-invasive Blood Glucose Measurements via Machine Learning” International Workshop on Bio-medical and Optical Sensing, Taipei, Taiwan
• 2015 “Next Generation Blood Test Electronics for Home-Based Health Care” ISNE, Taipei, Taiwan
• 2012 “Exploratory Study of R-RAM Scaling beyond 10nm”, IEEE Non-Volatile Memory Technology Symposium, Singapore
• 2012 “Outlook for 10nm Generation CMOS Technology and Resistive Memory Device”, CNSI-NPNT-BETRC Joint Workshop, Taiwan

國際研討會邀請擔任規劃委員

• 2022 擔任日本固態元件與材料國際研討會(SSDM)議程委員會副主席Vice Program Chair
• 2013-2021 擔任日本固態元件與材料國際研討會(SSDM)分組議程委員會副主席Program Subcommittee Vice Chair
• 2013 Symposium organizer of 10th Pacific Rim Conference on Ceramic and Glass Technology (PACRIM 10, San Diego, U.S.A., 2013)
• 2010-2011 擔任IEEE 國際電子元件會議(IEDM)之議程委員
• 2011 擔任Frontier of Spintronics/Nanoelectronics workshop 國際會議之共同主席並受邀演講

擔任重要計畫之審查委員/委員會委員/代表

• 2011 擔任新加坡科學工程研究委員會(Science and Engineering Research Council, SERC)先進記憶體國家計畫評審委員
• 2011-2021 擔任中華民國微系統暨奈米科技協會理事
• 2011.8-2014.12 擔任奈米國家型計畫資深顧問
• 2016.5-迄今 擔任科技部產學及園區業務司「農業生技研發成果鏈結產學合作計畫」輔導顧問團專家

Selected Publications

• Wei-Ru Lu, Wen-Tse Yang, Justin Chu, Tung-Han Hsieh & Fu- Liang Yang *. "Deduction learning for precise noninvasive measurements of blood glucose with a dozen rounds of data for model training" Scientific Reports volume 12, Article number: 6506 (2022), https://doi.org/10.1038/s41598-022-10360-3
• Chu, J.; Yang, W.-T.; Lu, W.-R.; Chang, Y.-T.; Hsieh, T.-H.; Yang, F.- L*. "90% Accuracy for Photoplethysmography-Based Non- Invasive Blood Glucose Prediction by Deep Learning with Cohort Arrangement and Quarterly Measured HbA1c." Sensors 2021, 21, 7815. https://doi.org/10.3390/s21237815
• Justin Chu, Wen-Tse Yang, Yao-Ting Chang* and Fu-Liang Yang* "Visual Reassessment with Flux Interval Plot Configuration after Automatic Classification for Accurate Atrial Fibrillation Detection by Photoplethysmography" Diagnostics 2022, 12, 1304. https:// doi.org/10.3390/diagnostics12061304
• Justin Chu, Wen-Tse Yang, Tung-Han Hsieh, Fu-Liang Yang*, Feb. 2021 "One-Minute Finger Pulsation Measurement for Diabetes Rapid Screening with 1.3% to 13% False-Negative Prediction Rate" Biomedical Statistics and Informatics 2021; 6(1): 6-13, DOI: 10.11648/j.bsi.20210601.12
• Bitewulign Kassa Mekonnen, Webb Yang, Tung-Han Hsieh, Shien-Kuei Liaw, and Fu-Liang Yang*, May. 2020 "Accurate Prediction of Glucose Concentration and Identification of Major Contributing Features from Hardly Distinguishable Near-Infrared Spectroscopy" Biomedical Signal Processing and Control, Volume 59. DOI: 10.1016/j.bspc.2020.101923
• Bitewulign Kassa Mekonnen, Tung-Han Hsieh, Dian-Fu Tsai, Shien- Kuei Liaw, Fu-Liang Yang and Sheng-Lung Huang, "Generation of Augmented Capillary Network Optical Coherence Tomography Image Data of Human Skin for Deep Learning and Capillary Segmentation" Diagnostics 2021. 11(4), 685; https://doi.org/10.3390/diagnostics11040685
• Yann-Wen Lan1*, Po-Chun Chen, Yun-Yan Lin, Ming-Yang Li, Lain- Jong Li, Yu-Ling Tu, Fu-Liang Yang, Min-Cheng Chen, Kai-Shin Li, Jan. 2019 "Scalable fabrication of a complementary logic inverter based on MoS2 fin-shaped field effect transistors" Nanoscale Horizons, DOI: 10.1039/C8NH00419F
• I-Fang Cheng, Hsien-Chang Chang, Tzu-Ying Chen, Chenming Hu, Fu-Liang Yang, Aug. 2013, "Rapid (<5min) Identification of Pathogen in Human Blood by Electrokinetic Concentration and Surface-Enhanced Raman Spectroscopy", Scientific Reports, 2365(3),1-8. DOI: 10.1038/srep02365(SCI) (IF: 2.927; SCI ranking: 15.1%)

• Bitewulign Kassa Mekonnen, Wei‐Ru Lu, Tung‐Han Hsieh, Justin Chu, & Fu‐Liang Yang*. Accurate and 30-plus days reliable cuffless blood pressure measurements with 9-minutes personal photoplethysmograph data and mixed deduction learning.” Scientific Reports volume 14, Article number: 23722 (2024). https://doi.org/10.1038/s41598-024-75583-y
• Wei‐Ru Lu, Wen‐Tse Yang, Justin Chu, Tung‐Han Hsieh & Fu‐Liang Yang *. “Deduction learning for precise noninvasive measurements of blood glucose with a dozen rounds of data for model training” Scientific Reports volume 12, Article number: 6506 (2022), https://doi.org/10.1038/s41598-022-10360-3
• Chu, J.; Yang, W.-T.; Lu, W.-R.; Chang, Y.-T.; Hsieh, T.-H.; Yang, F.-L*. “90% Accuracy for Photoplethysmography-Based Non-Invasive Blood Glucose Prediction by Deep Learning with Cohort Arrangement and Quarterly Measured HbA1c.” Sensors 2021, 21, 7815. https://doi.org/10.3390/s21237815
• Justin Chu, Wen-Tse Yang, Yao-Ting Chang* and Fu-Liang Yang* “Visual Reassessment with Flux Interval Plot Configuration after Automatic Classification for Accurate Atrial Fibrillation Detection by Photoplethysmography” Diagnostics 2022, 12, 1304. https:// doi.org/10.3390/diagnostics12061304
• Justin Chu, Wen-Tse Yang, Tung-Han Hsieh, Fu-Liang Yang*, Feb. 2021 “One-Minute Finger Pulsation Measurement for Diabetes Rapid Screening with 1.3% to 13% False-Negative Prediction Rate” Biomedical Statistics and Informatics 2021; 6(1): 6-13, DOI: 10.11648/j.bsi.20210601.12