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CenBRAIN Neurotech专题学术讲座 | 余浩: Machine-learning Enhanced Biomedical Data Analytics for Point-of-care Diagnosis System
时间
2023年12月26日（周二）
10:30-12:00
地点
必赢76net线路云谷校区E10-304
主持
必赢76net线路工学院讲席教授 Mohamad Sawan
受众
全体师生
分类
学术与研究
CenBRAIN Neurotech专题学术讲座 | 余浩: Machine-learning Enhanced Biomedical Data Analytics for Point-of-care Diagnosis System
时间：2023年12月26日（周二）10:30-12:00
Time: 10:30-12:00, Tuesday, December 26, 2023
地点：必赢76net线路云谷校区E10-304
Venue：E10-304, Yungu Campus
线上会议：腾讯会议：846-682-412
Online：Tencent Meeting：846-682-412
主持人: 必赢76net线路工学院讲席教授 Mohamad Sawan
Host: Mohamad Sawan, Chair Professor of School of Engineering, Westlake University
主讲嘉宾/Speaker：
余浩教授
深港微电子学院副院长
南方科技大学
主讲人简介/Biography:
Prof. Yu obtained his B.S. degree from Fudan University and obtained Ph. D degree from UCLA. He was a faculty at NTU-Singapore, and now is the deputy dean at SUSTech-Shenzhen. Dr. Yu has more than 300 peer-reviewed and referred publications as well as 9 books and 30 patents. He was recipients of Best Paper Award at IEEE Biomedical Circuits and Systems Conference (2018), Best Paper Award at ACM Trans. on Design Automation of Electronic Systems (2010), inventor award from semiconductor research cooperation (SC, Springer PhD thesis award (advisor), 3 best paper award nominations (DAC'O6, ICCAD'06, ASP-DAC'12), 3 student paper competition finalists (SiRF'13, RFIC'13, IMS'15), as well as 2 keynote talks. He was Distinguished Lecturer of IEEE Circuits and Systems Society, Associate Editors of IEEE Trans. on Biomedical Circuits and Systems, ACM Trans. on Embedded Computing Systems, Elsevier Integration, the VLSI Journal/Microelectronics Journal, and Scientific Reports, and has served as TPC member of various IEEE/ACM conferences (BioCAS, CICC. ASSCC, DAC etc). He was also founders of several high-tech companies with 2 WU Wen-Jun Al Science & Technology Award for Al chip. He is a senior member of IEEE and member of ACM.
讲座摘要/Abstract:
Machine learning has significantly enhanced performance across various domains, and this talk delves into recent machine learning advancements applied to biomedical data analytics for point-of-care diagnosis system. One focus is on lensless microfluidic imaging systems employing super-resolution (S) algorithms, aiming to miniaturize conventional optical-lens-based flow cytometers for portable and high-throughput cell detection. Additionally, the talk addresses in the crucial role of machine learning decode genetic information in Next-Generation Sequencing (NGS). This talk presents two single-frame super-resolution algorithms using online machine-learning for lensless microfluidic imaging, realized with compact hardware to perform a real-time image processing. Moreover, recent proposes in an optimized NGS sequencer will be discussed with a deep learning-based analysis pipeline, emphasizing cluster detection and base-calling processes. The relevant high energy efficient Al chips (CNN/Transformer/Large-scale Model) will be reported as well.
讲座联系人/Contact:
Yitian(Claire) Zhang
Fangyuan(Tiffany) Tian
