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Shuo Li

from Burbank, CA
Age ~41
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Also known as:
Shou Li, Li Shuo
Related to:
Bin LiJackie Hsi Cheng, 54Lee Peng, 60I CheungLiling Dong, 31
Connected to:
Adeline Li, 33Agatha K Li, 48Aiping Li, 33Aiyi Li, 36Andi Li, 34Andre N Li, 27Anyun Li, 34Banny Li, 52Baozhen Li, 68Beatrice O Li, 69

Shuo Li Phones & Addresses

  • Burbank, CA
  • Glendale, CA
  • Los Angeles, CA
  • Rocky Point, NY
  • Brooklyn, NY
  • South Setauket, NY
  • Elmhurst, NY
  • Port Jefferson Station, NY
  • Stony Brook, NY

Resumes

Resumes

Shuo Li Photo 1

Shuo Li

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Work:
United States
Education:
The Ohio State University
Shuo Li Photo 2

Shuo Li

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Shuo Li Photo 3

Shuo Li

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Shuo Li Photo 4

Shuo Li

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Shuo Li Photo 5

Shuo Li Hoboken, NJ

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Work:
Iowa State University

Jan 2014 to May 2014
Graduate Researching Assistant
Iowa State University
Ames, IA
Aug 2013 to May 2014
Graduate Teaching Assistant
YIBADA Global Chinese
New York, NY
Jul 2013 to Aug 2013
News Editor Intern
China - U.S. Chamber of Commerce
New York, NY
May 2013 to Jul 2013
Assistant Writer and Production Assistant Intern
China - U.S. Chamber of Commerce
New York, NY
Dec 2012 to Jan 2013
Public Relations Intern
Advertising Department of Henan Television

Jun 2011 to Sep 2011
TV advertising sales internship Intern
Education:
Greenlee School of Journalism and Communication, Iowa State University
Aug 2012 to 2000
Master in Journalism and Mass Communication
Jiangxi University of Traditional Chinese Medicine
Sep 2008 to Jun 2012
Bachelor of Art in English
Shuo Li Photo 6

Shuo Li Rocky Point, NY

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Work:
Stony Brook University

Sep 2008 to 2000
Research Assistant
HKUST

Dec 2006 to Aug 2008
Research Assistant
Education:
State University of New York at Stony Brook
Stony Brook, NY
2014
Ph.D. in Electrical and Computer Engineering
The Hong Kong University of Science and Technology
Hong Kong, Hong Kong Island
2008
M.Phil. in Electronic and Computer Engineering
Zhejiang University
Hangzhou, CN
2006
B.S. in Electronic and Information Engineering
Shuo Li Photo 7

Shuo Li New York, NY

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Work:
W&Co.
New York, NY
May 2014 to Aug 2014
Software Developer Intern
Education:
New York University
New York, NY
2013 to 2015
Master of Science in Computer Science
Beijing University of Posts and Telecommunications
2008 to 2012
BS in Computer Science

Publications

Us Patents

Method And System For Calibrating Sensing Circuitry Of An Implanted Medical Device

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US Patent:
20230083815, Mar 16, 2023
Filed:
Jul 6, 2022
Appl. No.:
17/810923
Inventors:
- Sylmar CA, US
Dean Andersen - Santa Clara CA, US
Shuo Li - Burbank CA, US
International Classification:
H03M 1/10
H03M 1/12
Abstract:
A system is provided that includes electrodes configured to be implanted in a body, and a pulse generator (PG) circuitry to deliver a stimulus to one or more of the electrodes. The system also includes sensing circuitry configured to define a sensing channel between one or more of the electrodes to sense signals indicative of a physiologic activity of interest, and the sensing circuitry further configured to collect a calibration signal over the sensing channel. The sensing circuitry and PG circuitry are housed within an implantable medical device (IMD). The system also includes one or more processors configured to determine a signal characteristic of interest (COI) of the calibration signal. The one or more processors are also configured to compare a signal COI of the stimulus to the signal COI of the calibration signal, and adjust a parameter of the sensing circuitry or PG circuitry based on the comparison.

Sensitively Detecting Copy Number Variations (Cnvs) From Circulating Cell-Free Nucleic Acid

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US Patent:
20210327535, Oct 21, 2021
Filed:
Aug 22, 2019
Appl. No.:
17/269983
Inventors:
- Oakland CA, US
- Los Angeles CA, US
Shuo LI - Los Angeles CA, US
Chun-Chi LIU - Los Angeles CA, US
Xiaohui NI - Los Angeles CA, US
International Classification:
G16B 20/10
G16B 30/00
G16B 40/30
Abstract:
The present disclosure provides methods and systems for detecting or inferring levels of Copy Number Variants (CNVs) in cell-free nucleic acid samples to detect or assess cancer and prenatal diseases. Cell-free nucleic acid methylation sequencing data may be utilized to distinguish tumor-derived or fetal-derived sequencing reads from normal cfDNA sequencing reads. Each cell-free nucleic acid sequencing read (e.g., containing tumor or fetal methylation markers) may be classified as corresponding to a tumor/fetal-derived or a normal-plasma cell-free nucleic acid, based on the methylation cfDNA sequencing data (e.g., obtained using Bisulfite sequencing or bisulfite-free sequencing methods) and tumor/fetal methylation markers. Next, a profile of the tumor/fetal-derived sequencing read counts may be constructed and then normalized. The CNV status (e.g., gain or loss) of each genomic region may be inferred, and a diagnosis or prognosis can be made based on a subjects inferred CNV profile.

Detecting Somatic Single Nucleotide Variants From Cell-Free Nucleic Acid With Application To Minimal Residual Disease Monitoring

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US Patent:
20210125683, Apr 29, 2021
Filed:
Sep 14, 2018
Appl. No.:
16/647339
Inventors:
- Oakland CA, US
Shuo LI - Los Angeles CA, US
Wenyuan LI - Los Angeles CA, US
Assignee:
THE REGENTS OF THE UNIVERSITY OF CALIFORNIA - Oakland CA
International Classification:
G16B 20/20
G16B 40/20
Abstract:
The present disclosure provides a probabilistic model for accurate and sensitive somatic single nucleotide variant (SNV) detection in cell-free nucleic acid samples comprising a set of sequence data. A joint genotype may be determined for each locus in the set of sequence data, and germline mutations may be intrinsically removed. A set of filtrations can be applied to eliminate low quality somatic variant calls. Further, a global tumor cell-free deoxyribonucleic acid (cfDNA) fraction and overlapping read mates can be considered, thereby enabling accurate SNV detection and variant allele frequency estimation from samples with low tumor cfDNA fraction. A sensitive early detection of minimal residual disease (MRD) is designed by using the probabilistic model and the machine learning model for distinguishing true variants from sequencing errors.
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Shuo Li from Burbank, CA, age ~41 Get Report