Fan T Jiang

US Patent:

20080163238, Jul 3, 2008

Filed:

Dec 28, 2006

Appl. No.:

11/648028

Inventors:

Fan Jiang - Foster City CA, US

International Classification:

G06F 9/46

US Classification:

718105

Abstract:

A system and method to perform dynamic balancing of task loads are described. A plurality of task files stored within a storage device are organized in descending order based on a respective processing time parameter associated with each task file, which characterizes the length of time necessary for processing of each respective task file. Processing of the task files is further initiated. Finally, each available task file is retrieved and processed successively from the plurality of ordered task files.

US Patent:

20200031195, Jan 30, 2020

Filed:

Jul 24, 2018

Appl. No.:

16/043262

Inventors:

- SAN JOSE CA, US
DALI WANG - FREMONT CA, US
FAN JIANG - SAN JOSE CA, US
RYAN SCOTT MIDDLETON - MOUNTAIN VIEW CA, US

International Classification:

B60H 1/00

Abstract:

Systems and methods are provided for controlling a HVAC system of a vehicle. An exemplary method may comprise: collecting data describing environmental measurements and one or more states of the HVAC system; predicting one or more target values by inputting the collected data into one or more inference models that include a personal inference model, wherein the personal inference model is used to predict a personal target value for the vehicle or a user of the vehicle; and outputting the one or more target values including the personal target value for the vehicle or the user of the vehicle to control the HVAC system of the vehicle.

US Patent:

20170236226, Aug 17, 2017

Filed:

Sep 20, 2016

Appl. No.:

15/270407

Inventors:

Ashutosh Malaviya - San Jose CA, US
Fan Jiang - San Jose CA, US
Eric Fang - Albany CA, US
Jason Hiver Tondu - Coeur d'Alene ID, US

International Classification:

G06Q 50/16
G06F 17/30
G06N 5/04
G06Q 30/02
G06Q 10/06

Abstract:

In one aspect, a computerized method for determining a probability value that a real-estate asset is to be placed on the market for sale includes the step of obtaining a database of real-estate assets. The method includes the step of merging a set of similar near real-estate tracts using a breadth-first search. The method, includes the step of creating a submarket of real-estate assets by performing duster analysis with a hierarchal-clustering method in a county context. The method includes the step of identifying a set of datasets of real-estate assets on a per-county level. The method includes the step of identifying a set of datasets of real-estate assets on a per-state level. The method includes the step of determining a probability that each real-estate asset will be placed for sale based on a set of geo-models. The method includes the step of mapping the probability that each real-estate asset will be placed for sale to a score. The method includes the step of implementing one or more weighting methods on the probability for each geo-model to smooth. The method includes the step of calculating a set of ensemble probabilities for each geo-model. The method includes the step of generating a globalized score for each real-estate asset in the database of real-estate assets.

US Patent:

20150356576, Dec 10, 2015

Filed:

May 27, 2015

Appl. No.:

14/722151

Inventors:

Ashutosh Malaviya - San Jose CA, US
Jason Hiver Tondu - Coeur d'Alene ID, US
Aniruddha Banerjee - Albany CA, US
Anita Narra - Pleasanton CA, US
Yu Pan - La Crescenta CA, US
Eric Fang - Albany CA, US
Fan Jiang - San Jose CA, US

International Classification:

G06Q 30/02

Abstract:

In one aspect, a method of generating a prediction list of real-estate assets that have a specified probability of being placed for sale within a specified period of time includes the step of providing a list of real-estate assets. Each real-estate asset is associated with one or more real-estate assets attributes. The method includes the step of providing a training data set wherein the training data set comprises a past population of data associated with a plurality of real-estate assets and a set of training-data set attributes for each real-estate asset in the plurality of real-estate assets. The method includes providing a testing data set wherein the testing data set comprises another past population of data associated with the plurality of real-estate assets and a set testing-data set attributes for each real-estate asset in the plurality of real-estate assets, wherein the set of testing data set attributes comprises an updated version of the training data set attributes from a specified later time.