Ping Gao from West Lafayette, IN, age 55

Medicine Doctors

Ping Gao

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Specialties:

Occupational Medicine

Work:

Mercy ClinicMercy Clinic Orthopedics
100 Mercy Way STE 430, Joplin, MO 64804
(417)6252278 (phone), (417)5562277 (fax)

Education:

Medical School
Shanxi Med Coll, Taiyuan City, Shanxi, China
Graduated: 1984

Languages:

English

Description:

Dr. Gao graduated from the Shanxi Med Coll, Taiyuan City, Shanxi, China in 1984. He works in Joplin, MO and specializes in Occupational Medicine. Dr. Gao is affiliated with Mercy Hospital Joplin.

Resumes

Ping Gao

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Location:

North Chicago, Illinois

Industry:

Pharmaceuticals

Awards:

AAPS Fellow

Ra At Wright State University

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Position:

RA at Wright State University

Location:

United States

Industry:

Higher Education

Work:

Wright State University
RA

Ping Gao

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Location:

United States

Lead Systems Consultant At Verizon Business

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Location:

Greater Boston Area

Industry:

Telecommunications

License Records

Ping Gao

License #:

5601004646 - Expired

Category:

Physicians Assistants

Issued Date:

Sep 1, 2005

Expiration Date:

Mar 1, 2007

Type:

Physician Assistant - Temporary

Lawyers & Attorneys

Ping Gao - Lawyer

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Office:

Law Office of Ping Gao

Specialties:

General Practice
Immigration Law
Family Law
Business Law

ISLN:

911736593

Admitted:

1995

Law School:

Peking University, LL.B., 1984; University of Hawaii, J.D., 1992

Us Patents

System & Method For Computationally Efficient And Statistically Robust Design Of Multi-Arm Multi-Stage Experiments
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US Patent:

20170329880, Nov 16, 2017
Filed:

May 12, 2017
Appl. No.:

15/594024
Inventors:

- Cambridge MA, US
Lingyun Liu - Sharon MA, US
Pralay Senchaudhuri - Cambridge MA, US
Cyrus Mehta - Cambridge MA, US
Ping Gao - Bridgewater NJ, US
Steve Herbert - Concord MA, US
International Classification:

G06F 17/50
G06F 5/01
G06F 17/18
Abstract:

A method and system providing an improved technology for efficiently computing experimental design in strict statistically controlled settings. The method and system utilize a unique combination of statistical algorithms for designing, comparing the performance, and conducting multi-arm, multistage experiments efficiently, while radically reducing the computation time required on a personal computing device, thereby improving computer technology and performance. In particular, the method and system enable personal computing devices to compute very large multi-arm multistage experiments in a significantly reduced period of time. The present invention allows experimentalists to examine in a single statistically controlled experiment a vastly greater range of experimental options, with the possibility of dropping uninformative arms of the experiment, changing goals and parameters during the course of the experiment.