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Kai Jiang, 71Malden, MA

Known as:
Ka Jang
Related to:
Ling Li 53 Jin Li

Kai Jiang Phones & Addresses

Malden, MA   

Brooklyn, NY   

Flushing, NY   

Norfolk, VA   

Beltsville, MD   

Monterey Park, CA   

Palmdale, CA   

Alexandria, VA   

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Kai Jiang resumes & CV records

Resumes

Kai Jiang Photo 35

Production Assistant

Location:
State College, PA
Work:

Production Assistant
Education:
Penn State University 2016 - 2020
Bachelors
Kai Jiang Photo 36

Analyst At Atlas Capital

Position:
Analyst at Atlas Capital
Location:
Shanghai City, China
Industry:
Venture Capital & Private Equity
Work:
Atlas Capital - Shanghai City, China since Dec 2012
Analyst UC San Diego - Greater San Diego Area Oct 2010 - Jul 2011
Research Associate Gladstone - San Francisco Bay Area Feb 2011 - Jun 2011
Research Associate Shanghai Jiao Tong University - Shanghai City, China Aug 2010 - Oct 2010
Intern
Education:
Imperial College London 2008 - 2012
Bsc, Bioscience St. Edmund's College, Ware 2006 - 2008
Languages:
English
Chinese
Japanese

Publications & IP owners

Wikipedia

Kai Jiang Photo 41

Kai Johan Jiang

Kai Johan Jiang (born 1965) is a Swedish-Chinese businessman and company operator with business interests in Sweden and China. In 2004, Jiang founded...

Us Patents

Alkali Metal Ion Battery With Bimetallic Electrode

US Patent:
2012010, May 3, 2012
Filed:
Sep 20, 2011
Appl. No.:
13/237215
Inventors:
Dane A. Boysen - Pasadena CA, US
David J. Bradwell - Boston MA, US
Kai Jiang - Malden MA, US
Hojong Kim - Arlington MA, US
Luis A. Ortiz - Natick MA, US
Donald R. Sadoway - Cambridge MA, US
Alina A. Tomaszowska - Bienkowice, PL
Weifeng Wei - Hunan, CN
Kangli Wang - Malden MA, US
Assignee:
MASSACHUSETTS INSTITUTE OF TECHNOLOGY - Cambridge MA
International Classification:
H02J 7/00
H01M 10/26
H01M 2/10
H01M 10/46
H01M 4/13
H01M 4/24
US Classification:
320101, 429104, 4292319, 429225, 429149, 320128, 320137, 429207
Abstract:
Electrochemical cells having molten electrodes having an alkali metal provide receipt and delivery of power by transporting atoms of the alkali metal between electrode environments of disparate chemical potentials through an electrochemical pathway comprising a salt of the alkali metal. The chemical potential of the alkali metal is decreased when combined with one or more non-alkali metals, thus producing a voltage between an electrode comprising the molten the alkali metal and the electrode comprising the combined alkali/non-alkali metals.

Retrospective Learning Of Communication Patterns By Machine Learning Models For Discovering Abnormal Behavior

US Patent:
2021032, Oct 21, 2021
Filed:
Jun 28, 2021
Appl. No.:
17/361106
Inventors:
- San Francisco CA, US
Jeshua Alexis Bratman - Brooklyn NY, US
Dmitry Chechik - San Carlos CA, US
Abhijit Bagri - Oakland CA, US
Evan James Reiser - San Francisco CA, US
Sanny Xiao Yang Liao - San Francisco CA, US
Yu Zhou Lee - San Francisco CA, US
Carlos Daniel Gasperi - New York NY, US
Kevin Lau - Long Island NY, US
Kai Jing Jiang - San Francisco CA, US
Su Li Debbie Tan - San Mateo CA, US
Jeremy Kao - Corona CA, US
Cheng-Lin Yeh - Menlo Park CA, US
International Classification:
H04L 29/06
G06N 20/00
Abstract:
Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.

Programmatic Discovery, Retrieval, And Analysis Of Communications To Identify Abnormal Communication Activity

US Patent:
2021029, Sep 23, 2021
Filed:
Jun 7, 2021
Appl. No.:
17/341200
Inventors:
- San Francisco CA, US
Jeshua Alexis Bratman - Brooklyn NY, US
Dmitry Chechik - San Carlos CA, US
Abhijit Bagri - Oakland CA, US
Evan James Reiser - San Francisco CA, US
Sanny Xiao Yang Liao - San Francisco CA, US
Yu Zhou Lee - San Francisco CA, US
Carlos Daniel Gasperi - New York NY, US
Kevin Lau - Long Island NY, US
Kai Jing Jiang - San Francisco CA, US
Su Li Debbie Tan - San Mateo CA, US
Jeremy Kao - Corona CA, US
Cheng-Lin Yeh - Menlo Park CA, US
International Classification:
H04L 29/06
G06Q 10/10
G06F 16/901
H04L 12/24
H04L 12/58
Abstract:
Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.

Retrospective Learning Of Communication Patterns By Machine Learning Models For Discovering Abnormal Behavior

US Patent:
2020039, Dec 17, 2020
Filed:
Jul 13, 2020
Appl. No.:
16/927335
Inventors:
- San Francisco CA, US
Jeshua Alexis Bratman - Brooklyn NY, US
Dmitry Chechik - San Carlos CA, US
Abhijit Bagri - Oakland CA, US
Evan James Reiser - San Francisco CA, US
Sanny Xiao Yang Liao - San Francisco CA, US
Yu Zhou Lee - San Francisco CA, US
Carlos Daniel Gasperi - New York NY, US
Kevin Lau - Long Island NY, US
Kai Jing Jiang - San Francisco CA, US
Su Li Debbie Tan - San Mateo CA, US
Jeremy Kao - Corona CA, US
Cheng-Lin Yeh - Menlo Park CA, US
International Classification:
H04L 29/06
G06N 20/00
Abstract:
Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.

Programmatic Discovery, Retrieval, And Analysis Of Communications To Identify Abnormal Communication Activity

US Patent:
2020038, Dec 10, 2020
Filed:
Jul 13, 2020
Appl. No.:
16/927478
Inventors:
- San Francisco CA, US
Jeshua Alexis Bratman - Brooklyn NY, US
Dmitry Chechik - San Carlos CA, US
Abhijit Bagri - Oakland CA, US
Evan James Reiser - San Francisco CA, US
Sanny Xiao Yang Liao - San Francisco CA, US
Yu Zhou Lee - San Francisco CA, US
Carlos Daniel Gasperi - New York NY, US
Kevin Lau - Long Island NY, US
Kai Jing Jiang - San Francisco CA, US
Su Li Debbie Tan - San Mateo CA, US
Jeremy Kao - Corona CA, US
Cheng-Lin Yeh - Menlo Park CA, US
International Classification:
H04L 29/06
G06Q 10/10
H04L 12/58
H04L 12/24
G06F 16/901
Abstract:
Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.

Multistage Analysis Of Emails To Identify Security Threats

US Patent:
2020034, Oct 29, 2020
Filed:
Jul 13, 2020
Appl. No.:
16/927427
Inventors:
- San Francisco CA, US
Jeshua Alexis Bratman - Brooklyn NY, US
Dmitry Chechik - San Carlos CA, US
Abhijit Bagri - Oakland CA, US
Evan James Reiser - San Francisco CA, US
Sanny Xiao Yang Liao - San Francisco CA, US
Yu Zhou Lee - San Francisco CA, US
Carlos Daniel Gasperi - New York NY, US
Kevin Lau - Long Island NY, US
Kai Jing Jiang - San Francisco CA, US
Su Li Debbie Tan - San Mateo CA, US
Jeremy Kao - Corona CA, US
Cheng-Lin Yeh - Menlo Park CA, US
International Classification:
H04L 29/06
G06F 16/958
G06F 16/955
G06F 16/951
G06Q 10/10
G06N 20/00
Abstract:
Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.

Threat Detection Platforms For Detecting, Characterizing, And Remediating Email-Based Threats In Real Time

US Patent:
2020020, Jun 25, 2020
Filed:
Nov 4, 2019
Appl. No.:
16/672854
Inventors:
- San Francisco CA, US
Jeshua Alexis Bratman - Brooklyn NY, US
Dmitry Chechik - San Carlos CA, US
Abhijit Bagri - Oakland CA, US
Evan James Reiser - San Francisco CA, US
Sanny Xiao Yang Liao - San Francisco CA, US
Yu Zhou Lee - San Francisco CA, US
Carlos Daniel Gasperi - New York NY, US
Kevin Lau - Long Island NY, US
Kai Jing Jiang - San Francisco CA, US
Su Li Debbie Tan - San Mateo CA, US
Jeremy Kao - Corona CA, US
Cheng-Lin Yeh - Menlo Park CA, US
International Classification:
H04L 29/06
Abstract:
Conventional email filtering services are not suitable for recognizing sophisticated malicious emails, and therefore may allow sophisticated malicious emails to reach inboxes by mistake. Introduced here are threat detection platforms designed to take an integrative approach to detecting security threats. For example, after receiving input indicative of an approval from an individual to access past email received by employees of an enterprise, a threat detection platform can download past emails to build a machine learning (ML) model that understands the norms of communication with internal contacts (e.g., other employees) and/or external contacts (e.g., vendors). By applying the ML model to incoming email, the threat detection platform can identify security threats in real time in a targeted manner.

Desert Water Generation Theory And Its Principle Application

US Patent:
2018003, Feb 8, 2018
Filed:
Sep 22, 2017
Appl. No.:
15/732136
Inventors:
Kai Jiang - Brooklyn NY, US
International Classification:
B01D 5/00
E03B 3/40
C02F 9/00
E03B 3/28
Abstract:
Applicant discloses a new viewpoint and its application for the freshwater generation here: Air temperature exchanges between the inside and outside of the deserts always play an important role in the generation of freshwater in desert environment. Because this procedure is continually happening in days and nights, and the desert area is large in the world, so, the amount of the water production by this way is extent to which one could be imagined. According the viewpoint disclosed here, it will bring big benefits to take over the shortage water plight and for the development of the desert. According this doctrine, the easiest way to collect the water from the desert is just setting an impermeable layer under the dune: the fresh water should flow out. By use of artificial stacked large amount sands can also obtain the freshwater in anywhere which the changes of the temperature are big.

Amazon

Kai Jiang Photo 42

Kai Jiang La: Ren Sheng Lu, Mo Huang Zhang (Simplified Chinese)

Author:
Kai jiang la
Publisher:
Bei jing lian he chu ban gong si
Binding:
Paperback
ISBN #:
7550212465
EAN Code:
9787550212466
The ten speeches of the first season of "Open Talk", a TedTalk-like program that airs on CCTV. The program is touted as the ¡§positive voice of China¡¨ and has quickly gained momentum around China. The first season¡¦s theme: ¡§Walk the path of life with firm footsteps¡¨ is given by 10 high profile y...
Kai Jiang Photo 43

Kai Jiang Yin Meng (Vol-1) (Chinese Edition)

Author:
Hong'en. Wu
Publisher:
University of California Libraries
Binding:
Paperback
Pages:
220
This book was digitized and reprinted from the collections of the University of California Libraries. Together, the more than one hundred UC Libraries comprise the largest university research library in the world, with over thirty-five million volumes in their holdings. This book and hundreds of t...
Kai Jiang Photo 44

Volume Vii

Author:
The Altar Collective
Publisher:
Altar Collective, The
Binding:
Paperback
Pages:
36
ISBN #:
0692364390
EAN Code:
9780692364390
The Altar Collective is a literary collective based in Los Angeles, CA. We publish an anthology featuring work from international writers. Volume VII is a poetry anthology featuring: Judd Kinnear Heath William Nicolette Daskalakis Christina Alice Schmidt Carolyn D. Elias William Akin Orli Robin ...

Possible Relatives

Cynthia Jiang  David Q Jiang  Daniel X Jiang  Danny P Jiang  Dennis Jiang  Dian Jiang  Dongyan Jiang  Kai D White  Kai Jones  Kai E Mcnichols 

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