楊富量
特聘研究員
Fu-Liang Yang
(Page on Web of Science)
flyanggate.sinica.edu.tw
02-2787-3173
ID
F-5927-2014
楊富量
特聘研究員
Research Interests
- Wearable Devices, Pulsation Waveform
- Characterization and Modulation
- Noninvasive Blood Glucose Measurements via
- AI Deduction Learning
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
- Distinguished Research Fellow/Professor Research Center for Applied Sciences, Academia Sinica (2013.08-Present)
- Director, Division of Intellectual Property and Technology Transfer, Academia Sinica (2013.08-2016.09)
- Distinguished Research Fellow, National Nano Device Laboratories(NDL), National Applied Research Laboratories(Narlabs) (2008.08-2013.08)
- Director General, National Nano Device Laboratories (2008.08-2013.05)
- TSMC, all in R&D Organization(2000.3-2008.7):
- Deputy Director, 2008,
- Department Manager, 2002
- TSMC Academician, TSMC Academy, 2004
- Section Manager, 2000
- Vanguard International Semiconductor Corporation(1994.12-2000.3):
- Section Manager, Dept. of Device Development, 1998
- Principal Integration Engineer, 1996
- Senior Process Engineer, 1994
Honors and Awards
- 2022, "AI Deduction Learning Non-Invasive Blood Glucose Meter" awarded National Innovation Award.
- 2020, "Helix External Counter Pulsation System" awarded National Innovation Award.
- 2012, "A Label-Free Method for the Rapid Identification of Rare-Pathogens from Human Blood (<5min)" awarded National Innovation Award.
- 2004, Outstanding Young Engineer Award from the Chinese Institute of Engineering
- 2004, TSMC Academician of TSMC Academy.
- 2004, TSMC Innovation Award (for <100> boosted PMOS)
- 2006, TSMC Best Invention Disclosures Award(for an outstanding transistor structure invention)
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%)