6月14日
4:00pm - 5:00pm
研討會, 演講, 講座
Speaker: Professor Keisuke GODA
Institution: Professor, Department of Chemistry, University of Tokyo / Adjunct Professor, Institute of Technological Sciences, Wuhan University
Host by: Prof. Hongkai WU
Abstract
A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how the spatial architecture of molecules within the cell is linked to its physiological function. Unfortunately, conventional technologies such as fluorescence-activated cell sorting are limited in uncovering these relations. In this talk, I introduce a machine intelligence technology known as “Intelligent Image-Activated Cell Sorting” [Cell 175, 266 (2018)] that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology integrates high-throughput cell microscopy, focusing, sorting, and deep learning on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision-making, and actuation. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.
About the speaker
Keisuke GODA is a professor in the Department of Chemistry at the University of Tokyo and an adjunct professor in the Institute of Technological Sciences at Wuhan University. He obtained a BA degree from UC Berkeley summa cum laude in 2001 and a PhD from MIT in 2007, both in physics. At MIT, he worked on the development of gravitational-wave detectors in the LIGO group which led to the 2017 Nobel Prize in Physics. After several years of work on high-speed imaging and microfluidics at Caltech and UCLA, he joined the University of Tokyo as a professor. His research group focuses on the development of discovery-enabling technologies based on molecular imaging and spectroscopy together with microfluidics and computational analytics to push the frontier of science. He has published >250 papers, filed >20 patents, and received numerous awards and honors.
Institution: Professor, Department of Chemistry, University of Tokyo / Adjunct Professor, Institute of Technological Sciences, Wuhan University
Host by: Prof. Hongkai WU
Abstract
A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how the spatial architecture of molecules within the cell is linked to its physiological function. Unfortunately, conventional technologies such as fluorescence-activated cell sorting are limited in uncovering these relations. In this talk, I introduce a machine intelligence technology known as “Intelligent Image-Activated Cell Sorting” [Cell 175, 266 (2018)] that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology integrates high-throughput cell microscopy, focusing, sorting, and deep learning on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, intelligent decision-making, and actuation. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.
About the speaker
Keisuke GODA is a professor in the Department of Chemistry at the University of Tokyo and an adjunct professor in the Institute of Technological Sciences at Wuhan University. He obtained a BA degree from UC Berkeley summa cum laude in 2001 and a PhD from MIT in 2007, both in physics. At MIT, he worked on the development of gravitational-wave detectors in the LIGO group which led to the 2017 Nobel Prize in Physics. After several years of work on high-speed imaging and microfluidics at Caltech and UCLA, he joined the University of Tokyo as a professor. His research group focuses on the development of discovery-enabling technologies based on molecular imaging and spectroscopy together with microfluidics and computational analytics to push the frontier of science. He has published >250 papers, filed >20 patents, and received numerous awards and honors.
6月14日
4:00pm - 5:00pm
地點
Room 2503, 2/F (Lifts 25/26), Academic Building, HKUST
講者/表演者
主辦單位
Department of Chemistry
聯絡方法
chivy@ust.hk
付款詳情
對象
PG Students, Faculty and Staff
語言
英語
其他活動
11月22日
研討會, 演講, 講座
IAS / School of Science Joint Lecture - Leveraging Protein Dynamics Memory with Machine Learning to Advance Drug Design: From Antibiotics to Targeted Protein Degradation
Abstract
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研討會, 演講, 講座
IAS / School of Science Joint Lecture - Some Theorems in the Representation Theory of Classical Lie Groups
Abstract
After introducing some basic notions in the representation theory of classical Lie groups, the speaker will explain three results in this theory: the multiplicity one theorem for classical...