Hong Lingli Fan

7407644, Aug 5, 2008

Nov 20, 2006

11/561638

Ramachandran S. Ranganathan - Danville CA, US
Hong (Helen) Fan - Princeton Junction NJ, US
Michael F. Tweedle - Princeton NJ, US
Rolf E. Swenson - Princeton NJ, US

Bracco International B.V. - Amsterdam

A61K 51/00
A61M 36/14

424 169, 424 111, 424 149

The invention provides radiopharmaceuticals for diagnostic and therapeutic applications, conjugates of antioxidants with metal chelating ligands, intermediate compounds, methods of making such radiopharmaceuticals, ligands, and intermediate compounds, and kits for preparing the radiopharmaceutical complexes.

20220321581, Oct 6, 2022

Mar 31, 2021

17/219318

- San Jose CA, US
Sudhindra MURTHY - Bangalore, IN
Ashwin Maruti HEGDE - Bangalore, IN
Nitin S. SHARMA - San Jose CA, US
Hong FAN - San Jose CA, US
Grahame Andrew JASTREBSKI - San Jose CA, US

H04L 29/06
G06N 20/00
G06F 21/55

Systems, methods, and computer program products are directed to machine learning techniques that use a separate embedding layer. This can allow for continuous monitoring of a processing system based on events that are continuously generated. Various events may have corresponding feature data associated with at least one action relating to a processing system. Embedding vectors that correspond to the features are retrieved from an embedding layer that is hosted on a separate physical device or a separate computer system from a computer that hosts the machine learning system. The embedding vectors are processed though the machine learning model, which may then make a determination (e.g. whether or not a particular user action should be allowed). Generic embedding vectors additionally enable the use of a single remote embedding layer for multiple different machine learning models, such as event driven data models.

20210400066, Dec 23, 2021

Aug 31, 2020

17/008323

- San Jose CA, US
Divakar Viswanathan - Tiruchirappalli, IN
Sheena Chawla - Bangalore, IN
Sudhindra Murthy - Bangalore, IN
Vidya Sagar Durga - Bangalore, IN
Hong Fan - San Jose CA, US

H04L 29/06
G06N 20/00

This application discusses identifying data processing timeouts in live risk analysis systems. A service provider, such as an electronic transaction processor, may provide a production computing environment that includes a risk analysis system having one or more risk models, which may be machine-learning based. These risk models may be utilized in order to determine whether incoming data processing requests are fraudulent. To test these risk models using production data traffic, an audit computing environment made of a set of machines that do not service production computing environment requests, but that utilize databases and data connections as are used by the production systems. The audit computing environment may thus mirror the risk models and functionality of the production computing environment without the drawbacks of a typical fully separate testing environment. Thus, risk model performance and execution times may be monitored to determine whether any models encounter errors with production data traffic.

20180026670, Jan 25, 2018

May 26, 2017

15/606649

- San Diego CA, US
Ashok RANGANATH - San Jose CA, US
Deepak DHAMDHERE - San Jose CA, US
Viral MODI - San Jose CA, US
Hong FAN - San Jose CA, US
Pattabiraman SUBRAMANIAN - Fremont CA, US
Gangadhar BURRA - Fremont CA, US

H04B 1/401
H04W 84/12
H04W 76/06
H04B 1/403
H04W 72/04
H04L 5/00

In a particular aspect, a method includes performing a first communication operation associated with a first frequency band using an antenna of a wireless device. The first communication operation is initiated by first communication circuitry of the wireless device. The first communication circuitry is associated with a first communication protocol. The method further includes, based on a duration of a second communication operation, performing the second communication operation associated with a second frequency band using the antenna of the wireless device. The second communication operation is initiated by second communication circuitry of the wireless device. The second communication circuitry is associated with a second communication protocol that is different than the first communication protocol. The first frequency band at least partially overlaps the second frequency band.

20170272507, Sep 21, 2017

Mar 20, 2017

15/463763

- Palo Alto CA, US
Hong FAN - San Jose CA, US
Aman SINGLA - Saratoga CA, US
Kiran EDARA - Cupertino CA, US
Kaixiang HU - Fremont CA, US

H04L 29/08
H04W 4/00

Systems and methods implemented through a user device, for claiming network devices for a home network in a distributed Wi-Fi network includes discovering a newly powered on access point; claiming the newly powered on access point for the home network; and relaying the claimed newly powered on access point to a cloud controller via a disjoint network from the home network, wherein the home network is restricted by the cloud controller to only operate with claimed access points. The discovering, the claiming, and the relaying can be performed by a mobile application executed on the user device.

20170272928, Sep 21, 2017

Mar 20, 2017

15/463647

- Palo Alto CA, US
Sameer VAIDYA - Saratoga CA, US
Paul WHITE - Burlingame CA, US
Kaixiang HU - Fremont CA, US
Hong FAN - San Jose CA, US
Srinivasa TAGIRISA - Cupertino CA, US

H04W 8/00
H04B 7/155
H04L 29/08

Systems and methods include a cloud controller communicatively coupled to one or more distributed Wi-Fi networks and configured to manage the one or more distributed Wi-Fi networks. The cloud controller includes a network interface communicatively coupled to the distributed Wi-Fi networks; one or more processors communicatively coupled to the network interface; and memory storing instructions that, when executed, cause the one or more processors to: determine a new topology state for a topology of Wi-Fi network from a current topology state based on management of the Wi-Fi network; cause one or more nodes to change to new associated parent nodes based on the new topology state; cause an update to a configuration of the one or more nodes based on the new topology state; and continue to change additional nodes to new associated parent nodes based on the new topology state until the new topology state is obtained.

20170272977, Sep 21, 2017

Mar 17, 2017

15/462071

- Palo Alto CA, US
Jian LU - Los Gatos CA, US
Kiran EDARA - Cupertino CA, US
Sameer VAIDYA - Saratoga CA, US
Hong FAN - San Jose CA, US
William MCFARLAND - Portola Valley CA, US

H04W 28/08
H04W 40/12
H04W 28/02
H04L 12/26
H04L 12/727
H04W 24/02
H04W 40/16

Systems and methods for gathering data by an access point in a Wi-Fi system for optimization include periodically or based on command from a cloud-based system performing one or more of i) obtaining on-channel scanning data while operating on a home channel and ii) switching off the home channel and obtaining off-channel scanning data for one or more off-channels; and providing measurement data based on one or more of the on-channel scanning data and the off-channel scanning data to the cloud-based system for use in the optimization of the Wi-Fi system, wherein the measurement data comprises one or more of raw data and processed data.

20170273013, Sep 21, 2017

Mar 17, 2017

15/462284

- Palo Alto CA, US
Kaixiang HU - Fremont CA, US
Jian LU - Los Gatos CA, US
Hong FAN - San Jose CA, US
William MCFARLAND - Portola Valley CA, US

H04W 48/16
H04L 29/08
H04W 48/20

Systems and methods implemented by a cloud controller for steering Wi-Fi client devices in a Wi-Fi network include determining a client needs to be steered from a first access point to a second access point; selecting a client steering approach from a plurality of client steering approaches based on the client; and causing the client to be steered from the first access point to the second access point based on the selected client steering approach. The determining can be based on optimization performed by the cloud controller based on operational parameters associated with the Wi-Fi network.