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OSSC Meeting Oct. 4, 2023

When:
Wednesday, October 04, 2023
Where:
The Circadian Room, Pasadena City College
The Circadian Room, Pasadena City College
Pasadena, CA  91106

(626) 585-7233
Additional Info:
Contacts(s):
Nicholas J Croglio, Jr.
Programs & Zoom
 
Russell Rauch
Zoom Login (events@ossc.org)
 
Donn M Silberman
Arrangements
9496366170 (c)
Category:
OSSC Regular Meeting
Registration is required
Payment in Full In Advance Or At Event
Cancellation Policy:
Please let the Arrangements Chair (Events@ossc.org) know as soon as possible.

Payments made in advance will normally be issued a credit that may be applied to future payments (membership or events). Please contact the Treasurer (Treasurer@ossc.org) if this posses a significant burden.
Activities/Items    (Click the down-arrow to view details )
Dinner
Sponsor a Student
Sponsor a Table
Donate to the OSSC (Suggested Donation)
Online Presentation Only
In-Person No Dinner
 

Wednesday Oct. 4, 2023
 In-Person Reception 6:00 pm; Dinner 7:00 pm
(No fee to attend presentation only in-person or on-line)

Online Login: 7:30 pm PDT
OSSC Business: 7:40 pm
Presentation: 8:00 pm

OSSC Combination in-Person and Zoom

"

Computation in microscopy: How computers are

changing the way we build and use microscopes"

by
Changhuei Yang, Ph.D., California Institute of Technology


         


Abstract:

The level of computational power we can currently access, has significantly changed the way we think about, process and interact with microscopy information. In this talk, I will discuss some of our recent computational microscopy and deep learning work, that showcase some of these shifts in the context of pathology and life science research. I will talk about Fourier Ptychographic Microscopy (FPM) – the first demonstrated computational approach for numerically zeroing out physical aberrations from microscopy images. As a novel way to collect and process microscopy data, FPM can also bring significant workflow advantages to pathology. I will also talk about the use of Deep Learning in image analysis and point out some of impactful ways Deep Learning can improve the way we deal with image data in pathology and life science research. Looking into the near future, the surprising findings of these current endeavors strongly indicate that the redesign of microscope to better suit these computational needs would be instrumental for the next level of AI based image analysis.

About Our Speaker:                                                                                                                                                  

Changhuei Yang is the Thomas G. Myers Professor of Electrical Engineering, Bioengineering and Medical Engineering and a Heritage Medical Research Institute Principal Investigator at the California Institute of Technology. He works in the area of biophotonics and computational imaging. His research team has developed numerous novel biomedical imaging technologies over the past 2 decades – including technologies for focusing light deeply into animals using time-reversal optical methods, lensless microscopy, ePetri, Fourier Ptychography, and non-invasive brain activity monitoring methods. He has worked with major companies, including BioRad, Amgen and Micron-Aptina, to develop solutions for their technological challenges.

 

He has received the NSF Career Award, the Coulter Foundation Early Career Phase I and II Awards, and the NIH Director's New Innovator Award. He is a Coulter Fellow, an AIMBE Fellow and an OSA Fellow. He was elected as a Fellow in the National Academy of Inventors in 2020.

 

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