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.
Personalized Adaptive Hvac System Control Methods And Devices
- 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.
Computerized Systems, Processes, And User Interfaces For Globalized Score For A Set Of Real-Estate Assets
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.
Computerized Systems, Processes, And User Interfaces For Targeted Marketing Associated With A Population Of Real-Estate Assets
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.
Name / Title
Company / Classification
Phones & Addresses
Fan Jiang Chief Investment Officer Of Private Wealth Management Goldman Sachs
Goldman, Sachs & Co.
85 Broad St BLDG 85, New York, NY 10111 2122656575
Nan Hua Futures Macroeconomic Research Centre China, ME Dec 2009 to Apr 2012 Macroeconomic AnalystYong Ci Electronic Machinery Co., Ltd China, ME Feb 2009 to Nov 2009 Accountant Assistant
Education:
Pace University New York, NY 2012 to 2014 MS in AccountingUniversity of Exeter UK 2007 to 2008 MSc in Finance and InvestmentUniversity of Exeter UK 2004 to 2007 BA in Economics
Skills:
Computer skills: Proficient in advanced MS office (Word, Excel and PPT) ;Familiar with the usage of financial databases such as Thomson Banker One Analytics, Data stream and Bloomberg.
Sep 2012 to 2000 InternKawaller & Company Brooklyn, NY Jun 2012 to Aug 2012 Intern
Education:
Columbia University New York, NY 2011 to 2012 MS in Operations ResearchPurdue University West Lafayette, IN Jan 2009 to Jan 2011 MS in SociologyRenmin University of China 2005 to 2009 BM in Agricultural Economics and Agribusiness Management
KMK Consulting Inc Florham Park, NJ Nov 2012 to Nov 2012 InternshipCornell MPS Program Ithaca, NY Oct 2012 to Nov 2012 Project CoordinatorBeijing Institute of Technology
Sep 2008 to Sep 2012 Chairman of Assessment Department of the Student UnionBeijing Institute of Technology
Oct 2011 to Nov 2011 Senior Statistician of Economic Statistics DivisionBeijing Institute of Technology
Oct 2011 to Nov 2011 Certificated ConsultantConcentration New York, NY Jul 2011 to Aug 2011 Marketing, InvestmentBeijing Institute of Technology
Feb 2011 to Jul 2011 Project CoordinatorBeijing Institute of Technology
Aug 2010 to Sep 2010 Financial AnalystUndergraduate Mathematics Model Project
Aug 2010 to Aug 2010 Project CoordinatorChina Youth Development Foundation
Jul 2010 to Aug 2010 VolunteerBeijing Institute of Technology
2010 to 2010 Internship ExperiencesTable Tennis
2009 to 2009 Beijing Institute of Technology
Education:
Cornell University Ithaca, NY Aug 2012 Master of professional studies in Applied Statistics