Hao H Wang

7240255, Jul 3, 2007

Mar 22, 2005

11/088636

Charles Akum Njinda - San Jose CA, US
Shalesh Thusoo - Milpitas CA, US
Hao Wang - San Jose CA, US

Cisco Technology, Inc. - San Jose CA

G11C 29/00

714718, 714733

A system with a single BIST for an IC that includes a number of memory arrays that may have varying latencies, widths, and depths. A serial bus (which may be a debug bus) connects the BIST controller, each of the memory arrays on the IC, and a controller. Each memory array has an associated Design for Test Assist Logic (DAL) block. The DAL associated with any particular memory array recognizes commands from the BIST that are for the associated memory array, controls the execution of write/read commands for the associated array and sends data read from the memory array along with appropriate commands to the comparator after a latency that is appropriate for the associated array Thus, there are standardized commands from the BIST, but each DAL executes these commands in a manner appropriate for the memory array (or arrays) associated with the particular DAL.

20220344004, Oct 27, 2022

Mar 9, 2022

17/691049

- Redwood City CA, US
Darya CHUDOVA - San Jose CA, US
Aliaksandr ARTSIOMENKA - Mountain View CA, US
Daniel GAILE - Redwood City, US
Hao WANG - Redwood City CA, US

G16B 30/10
G16B 20/20
G16B 20/10

In implementations described herein, information derived from a sample that is derived from off-target sequences can be used to determine estimates for the copy number of tumor cells and/or the tumor fraction of a sample. Additionally, information derived from the presence of germline SNPs can be used to determine estimates for at least one of the copy number of tumor cells or the tumor fraction of a sample.

20220327331, Oct 13, 2022

Jun 28, 2022

17/809537

- Armonk NY, US
Rajasekar Krishnamurthy - Campbell CA, US
Yunyao Li - San Jose CA, US
Shivakumar Vaithyanathan - San Jose CA, US
Hao Wang - San Jose CA, US
Sang Don Han - Sunnyvale CA, US

G06K 9/62
G06F 21/60

One embodiment provides for a method for evaluation of an artificial intelligence (AI) service, the method includes partitioning, by a processor, data into in-domain data and out-of-domain data. The processor defines held-out data from both of the in-domain data and the out-of-domain data for evaluation by each of domain and sub-domain based on building a taxonomy of both domains and sub-domains for the AI service. The held-out data is excluded from training data used for training the AI service. The processor further determines distribution underlying performance metrics for the held-out data using bootstrap validation processing. The processor also determines performance guarantees for multiple settings conditioned on multiple characteristics of an application scenario for the held-out data of the taxonomy based on the underlying performance metrics.

20230009692, Jan 12, 2023

Jul 7, 2021

17/368997

- Santa Clara CA, US
Hao WANG - Livermore CA, US
David JORGENSEN - Moutain View CA, US
Yi-Chiau HUANG - Fremont CA, US

C23C 18/32
C30B 23/02
C23C 18/16
C23C 16/32
C23C 16/455
C30B 29/06
C23C 18/18
C23C 16/458

Embodiments of the present disclosure generally relate to a substrate support having a two-part surface coating which reduces defect formation and back side metal contamination during substrate processing. A support body includes a body having an upper surface and a two-part coating disposed over the upper surface of the body. The two-part coating includes a first coating layer extending a first radial distance from a center of the body. The first coating layer includes at least one of a metal-containing material or alloy. The two-part coating includes a second coating layer disposed over the first coating layer. The second coating layer extends a second radial distance from the center of the body. The first radial distance is greater than the second radial distance. The second coating layer is non-metal.

20210375391, Dec 2, 2021

Jun 28, 2019

17/255389

- Pleasanton CA, US
Daniel M. Klass - Livermore CA, US
Alexander Lovejoy - Newark CA, US
Seyed Hamid Mirebrahim - Dublin CA, US
Amrita Pati - San Ramon CA, US
Hao Wang - Dublin CA, US

G16B 20/20
C12Q 1/6869

Methods and systems for detecting MSI are provided. Also provided are methods for enriching human genomic DNA for microsatellite loci. Additional, an oligonucleotide array for detecting MSI is provided.

20210357194, Nov 18, 2021

May 18, 2020

16/877204

- Sunnyvale CA, US
John Cortes - Santa Clara CA, US
Hao Wang - Sunnyvale CA, US

Fortinet, Inc. - Sunnyvale CA

G06F 8/41
G06F 8/30

Systems and methods for programming a network device using a domain-specific language (DSL) are provided. According to one embodiment, source code in a form of a DSL, describing a slow-path task that is to be performed by a network device, is received by a processing resource. A determination is made regarding one or more types of processors are available within the network device to implement the slow-path task. For each portion of the source code, a preferred type of processor is determined by which the portion of the source code would be most efficiently implemented. When the preferred type of processor is available within the network device, executable code is generated targeting the preferred type of processor based on the portion of the source code; otherwise, intermediate code is generated in a form of a high-level programming language, targeting a general purpose processor of the network device.

20200082228, Mar 12, 2020

Sep 6, 2018

16/123822

- Armonk NY, US
Rajasekar Krishnamurthy - Campbell CA, US
Yunyao Li - San Jose CA, US
Shivakumar Vaithyanathan - San Jose CA, US
Hao Wang - San Jose CA, US
Sang Don Han - Sunnyvale CA, US

G06K 9/62
G06F 21/60

One embodiment provides for a method for evaluation of an artificial intelligence (AI) service, the method includes partitioning, by a processor, data into in-domain data and out-of-domain data. The processor defines held-out data from the in-domain data and the out-of-domain data for evaluation by domain and sub-domain based on building a taxonomy of domains and sub-domains for the AI service. The processor further determines distribution underlying performance metrics for the held-out data using statistical processing. The processor also determines performance guarantees for multiple settings conditioned on multiple characteristics of an application scenario for the held-out data of the taxonomy based on the underlying performance metrics. The processor further provides confidence intervals based on the performance guarantees.

20180220491, Aug 2, 2018

Jan 25, 2018

15/879885

Ravi Shankar Prasher - Danville CA, US
Hao Wang - Richmond CA, US
Justin Palmer Freedman - Berkeley CA, US

The Regents of the University of California - Oakland CA

H05B 3/00

A multilayer photonic stack comprising a lower plurality of alternating layers comprising at least A and B and an upper plurality of alternating layers comprising at least C and D, layer A comprises at least one of Al, Au, W, Ag, Ni, Ti, Pt, and Cr, layer B comprises at least one of AlO, AlN, MgO, SiO, TiO, SiN, MgF, TaO, SiC, Si, Ge, and Indium Tin Oxide (ITO), and layers C and D comprise at least one of AlO, AlN, MgO, SiO, TiO, SiN, MgF, TaO, SiC, Si, Ge, and Indium Tin Oxide (ITO).