Xiaohu Zhang resumes & CV records
Resumes
Xiaohu Zhang
Xiaohu Zhang
Xiaohu T Zhang, 451705 Goularte Pl, Fremont, CA 94539
Xiaohu Zhang Phones & Addresses
1705 Goularte Pl, Fremont, CA 94539 650-2919399
Milpitas, CA
Sunnyvale, CA
1918 Todd Dr, Tempe, AZ 85283 480-8203628
Mountain View, CA
Stanford, CA
Chandler, AZ
Los Angeles, CA
Maricopa, AZ
1705 Goularte Pl, Fremont, CA 94539
Work
Position:
Professional/Technical
Education
Degree:
High school graduate or higher
Mentions for Xiaohu T Zhang
Publications & IP owners
Us Patents
Adjusting For Uncertainty In Advertisement Impression Data
US Patent:
2008024, Oct 9, 2008
Filed:
May 1, 2007
Appl. No.:
11/743078
Inventors:
Daniel J. Zigmond - Menlo Park CA, US
Jason Bayer - Mountain View CA, US
Xiaohu Zhang - Mountain View CA, US
Jason Bayer - Mountain View CA, US
Xiaohu Zhang - Mountain View CA, US
Assignee:
GOOGLE INC. - Mountain View CA
International Classification:
G06F 17/18
G06Q 30/00
G06Q 30/00
US Classification:
705 10, 705 14
Abstract:
Methods, systems and apparatus, including computer program products, provide adjustments to advertisement impression estimates based on sampled data. According to one method, an estimated number of advertisement impressions is made based on the sampled data and the estimate is discounted to achieve a level of certainty that the resulting discounted estimate is less than the actual number of advertisement impressions. The amount of the discount can be determined based on a sampling error model of the sampling data.
Estimating Tv Ad Impressions
US Patent:
2009015, Jun 11, 2009
Filed:
Mar 26, 2008
Appl. No.:
12/055906
Inventors:
Yaroslav Volovich - Cambridge, GB
Geoffrey R. Smith - Mountain View CA, US
Daniel J. Zigmond - Menlo Park CA, US
Xiaohu Zhang - Mountain View CA, US
Ajoy Bhambani - San Francisco CA, US
Iain Merrick - London, GB
Geoffrey R. Smith - Mountain View CA, US
Daniel J. Zigmond - Menlo Park CA, US
Xiaohu Zhang - Mountain View CA, US
Ajoy Bhambani - San Francisco CA, US
Iain Merrick - London, GB
International Classification:
G06Q 10/00
US Classification:
705 7
Abstract:
The subject matter of this specification can be embodied in, among other things, a method that includes receiving cluster information comprising categories and total numbers of media receivers (e.g. television (TV) viewers) associated with the categories and receiving sample data comprising numbers of advertisements (ads) displayed to sampled receivers (e.g., TV viewers) that are classified within the categories. The method also includes calculating probabilities for numbers of ads displayed to the total numbers of receivers associated with the categories, wherein the calculation is based on the cluster information and the sample data, merging the calculated probabilities associated with two or more of the categories, and outputting an estimated number of ads displayed based on the merged probabilities.
Systems And Methods Of Autonomous Line Flow Control In Electric Power Systems
US Patent:
2021014, May 13, 2021
Filed:
Nov 6, 2020
Appl. No.:
17/091917
Inventors:
- Beijing, CN
- Nanjing, CN
- Jinan, CN
Xiaohu Zhang - San Jose CA, US
- Nanjing, CN
- Jinan, CN
Xiaohu Zhang - San Jose CA, US
International Classification:
G05B 19/042
G06N 3/08
G06N 3/08
Abstract:
Systems and methods for autonomous line flow control in an electric power system are disclosed which includes acquiring state information at a line in the electric power system at a first time step, obtaining a flow data of the line at a next time step based on the acquired state information, generating an early warning signal when the obtained flow data is higher than a predetermined threshold, activating a deep reinforcement learning (DRL) agent to generate an action using a DRL algorithm based on the state information, and executing the action to adjust a topology of the electric power system.
Autonomous Voltage Control For Power System Using Deep Reinforcement Learning Considering N-1 Contingency
US Patent:
2020011, Apr 16, 2020
Filed:
Oct 6, 2019
Appl. No.:
16/594033
Inventors:
Di Shi - San Jose CA, US
Ruisheng Diao - San Jose CA, US
Zhiwei Wang - San Jose CA, US
Qianyun Chang - CA, US
Jiajun Duan - San Jose CA, US
Xiaohu Zhang - San Jose CA, US
Ruisheng Diao - San Jose CA, US
Zhiwei Wang - San Jose CA, US
Qianyun Chang - CA, US
Jiajun Duan - San Jose CA, US
Xiaohu Zhang - San Jose CA, US
International Classification:
H02J 3/18
G06N 3/04
G06N 3/08
G05B 13/02
H02J 13/00
H02J 3/00
G06N 3/04
G06N 3/08
G05B 13/02
H02J 13/00
H02J 3/00
Abstract:
Systems and methods are disclosed to control voltage profiles of a power grid by forming an autonomous voltage control model with one or more neural networks as Deep Reinforcement Learning (DRL) agents; training the DRL agents to provide data-driven, real-time and autonomous grid control strategies; and coordinating and optimizing reactive power controllers to regulate voltage profiles in the power grid with a Markov decision process (MDP) operating with reinforcement learning to control problems in dynamic and stochastic environments.
Mpc-Based Pv Maximum Power Point Tracker For Transformerless H5 Inverter With Leakage Current Reduction
US Patent:
2019036, Nov 28, 2019
Filed:
Apr 22, 2019
Appl. No.:
16/390510
Inventors:
Zhehan Yi - San Jose CA, US
Haifeng Li - Nanjing, CN
Xiaohu Zhang - San Jose CA, US
Xiaoying Zhao - San Jose CA, US
Di Shi - San Jose CA, US
Ruisheng Diao - San Jose CA, US
Zhiwei Wang - San Jose CA, US
Haifeng Li - Nanjing, CN
Xiaohu Zhang - San Jose CA, US
Xiaoying Zhao - San Jose CA, US
Di Shi - San Jose CA, US
Ruisheng Diao - San Jose CA, US
Zhiwei Wang - San Jose CA, US
International Classification:
H02J 3/38
H02M 7/5387
H02M 7/5387
Abstract:
Systems and methods are disclosed to control a power inverter by extracting photovoltaic (PV) maximum power under a plurality of operating conditions as one or more reference variables; predicting the future behaviors of a PV output voltage as one or more controlled variables based on a current operational condition; generating one or more control signals for the H5 inverter that minimizes an error between the reference variable and the controlled variables; and controlling the power inverter with the one or more control signals.
Possible Relatives
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