Patents by Inventor Su Li

Su Li has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 12297425
    Abstract: A nucleic acid extraction composition, reagents and kits containing the same and uses thereof. Provided is a nucleic acid extraction and purification reagent free of volatile organic solvents, which prevents the damage of volatile organic solvents to people and greatly improves the timeliness of nucleic acid extraction and purification, making the operation extremely simple, and the nucleic acid can be obtained within 10 minutes. The obtained nucleic acid may be used for biological reactions such as PCR, NASBA, LAMP and RPA. Moreover, the reagents of the present disclosure may be used to extract nucleic acids of cells, bacteria, fungi, DNA viruses and RNA viruses from various samples such as blood, throat swab preserving fluid, saliva, urine, sputum, excrement and the like, and very suitable for clinical and scientific research uses.
    Type: Grant
    Filed: April 22, 2021
    Date of Patent: May 13, 2025
    Assignees: CAPITALBIO CORPORATION, WEST CHINA HOSPITAL OF SICHUAN UNIVERSITY
    Inventors: Xiang Chen, Lei Wang, Su Li, Longtang Zheng, Yanan Wang, Fei Wen, Juan Xin, Wentian Zhang, Jing Cheng
  • Patent number: 12255915
    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.
    Type: Grant
    Filed: June 7, 2021
    Date of Patent: March 18, 2025
    Assignee: Abnormal Security Corporation
    Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
  • Publication number: 20240291834
    Abstract: Access to emails delivered to an employee of an enterprise is received. An incoming email addressed to the employee is acquired. A primary attribute is extracted from the incoming email by parsing at least one of: (1) content of the incoming email or (2) metadata associated with the incoming email. It is determined whether the incoming email deviates from past email activity, at least in part by determining, as a secondary attribute, a mismatch between a previous value for the primary attribute and a current value for the primary attribute, using a communication profile associated with the employee, and providing a measured deviation to at least one machine learning model.
    Type: Application
    Filed: March 26, 2024
    Publication date: August 29, 2024
    Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
  • Publication number: 20240187450
    Abstract: It is determined that a first email is present in a mailbox where emails deemed suspicious are placed for analysis. In response to determining that the first email is present in the mailbox, it is determined whether the first email is representative of a threat to an enterprise based at least in part by applying a trained model to the first email. In response to determining that the first email represents a threat to the enterprise, a record of the threat is generated by populating a data structure with information related to the first email. The data structure is applied to inboxes of a plurality of the employees to determine whether the first email is part of a campaign. In response to determining that the first email is part of a campaign, a filter associated with the data structure is applied to inbound emails addressed to employees of the enterprise.
    Type: Application
    Filed: February 15, 2024
    Publication date: June 6, 2024
    Inventors: Evan Reiser, Jeremy Kao, Cheng-Lin Yeh, Yea So Jung, Kai Jing Jiang, Abhijit Bagri, Su Li Debbie Tan, Venkat Krishnamoorthi, Fang Shuo Deng
  • Publication number: 20240171596
    Abstract: A message addressed to a user is received. A first model is applied to the message to produce a first output indicative of whether the message is representative of a non-malicious message. The first model is trained using past messages that have been verified as non-malicious messages. It is determined, based on the first output, that the message is potentially a malicious message. Responsive to determining that the message is potentially a malicious email based on the first output, apply a second model to the message to produce a second output indicative of whether the message is representative of a given type of attack. The second model is one of a plurality of models. At least one model included in the plurality of models is associated with characterizing a goal of the malicious message. An action is performed with respect to the message based on the second output.
    Type: Application
    Filed: September 26, 2023
    Publication date: May 23, 2024
    Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
  • Publication number: 20240159904
    Abstract: The present invention discloses a light detection and ranging (LIDAR) system ranging method, including: circularly allocating, by a light routing device, each periodic signal of a transmit signal to each light channel in a chronological order, monitoring a beat signal or a returned light pulse signal in each light channel, and calculating a target distance according to a frequency of the beat signal or a return delay time of the light pulse signal. The present invention further discloses a LIDAR, including: a laser source, a light routing device, an optical scanning system, a light detector, and a data processing module. A quantity of detection points per second of each beam is increased to N times, where N is a quantity of channels of the light routing device, so as to improve the detection efficiency and reduce the requirement on transmit resources; and a scanning mode and an angular resolution can be dynamically controlled according to needs.
    Type: Application
    Filed: December 27, 2022
    Publication date: May 16, 2024
    Inventors: Su Li, Fan Qi, Pengfei Cai, Yongpeng Zhao
  • Patent number: 11973772
    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.
    Type: Grant
    Filed: February 22, 2022
    Date of Patent: April 30, 2024
    Assignee: Abnormal Security Corporation
    Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
  • Patent number: 11949713
    Abstract: Introduced here are computer programs and computer-implemented techniques for discovering malicious emails and then remediating the threat posed by those malicious emails in an automated manner. A threat detection platform may monitor a mailbox to which employees of an enterprise are able to forward emails deemed to be suspicious for analysis. This mailbox may be referred to as an “abuse mailbox” or “phishing mailbox.” The threat detection platform can examine emails contained in the abuse mailbox and then determine whether any of those emails represent threats to the security of the enterprise. For example, the threat detection platform may classify each email contained in the abuse mailbox as being malicious or non-malicious. Thereafter, the threat detection platform may determine what remediation actions, if any, are appropriate for addressing the threat posed by those emails determined to be malicious.
    Type: Grant
    Filed: December 14, 2021
    Date of Patent: April 2, 2024
    Assignee: Abnormal Security Corporation
    Inventors: Evan Reiser, Jeremy Kao, Cheng-Lin Yeh, Yea So Jung, Kai Jing Jiang, Abhijit Bagri, Su Li Debbie Tan, Venkatram Kishnamoorthi, Feng Shuo Deng
  • Patent number: 11943257
    Abstract: Selectively rewriting URLs is disclosed. An indication is received that a message has arrived at a user message box. A determination is made that the message includes a first link to a first resource. The first link is analyzed to determine whether the first link is classified as a non-rewrite link. In response to determining that the first link is not classified as a non-rewrite link, a first replacement link is generated for the first link.
    Type: Grant
    Filed: December 21, 2022
    Date of Patent: March 26, 2024
    Assignee: Abnormal Security Corporation
    Inventors: Yea So Jung, Su Li Debbie Tan, Kai Jing Jiang, Fang Shuo Deng, Yu Zhou Lee, Rami F. Habal, Oz Wasserman, Sanjay Jeyakumar
  • Patent number: 11824870
    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.
    Type: Grant
    Filed: November 4, 2019
    Date of Patent: November 21, 2023
    Assignee: Abnormal Security Corporation
    Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
  • Patent number: 11743294
    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.
    Type: Grant
    Filed: June 28, 2021
    Date of Patent: August 29, 2023
    Assignee: Abnormal Security Corporation
    Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan James Reiser, Sanny Xiao Yang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh
  • Patent number: 11729068
    Abstract: An approach is provided in which the approach captures a first user activity log of a first user accessing multiple systems and captures a set of second user activity logs of a set of second users accessing the multiple systems. The approach determines a set of system monitoring preferences based the first user activity log and the set of second user activity logs, and scores the multiple systems based on the set of system monitoring preferences. The approach generates a recommended system monitoring list based on the scored multiple systems, and transmits the recommended system monitoring list to the first user.
    Type: Grant
    Filed: September 9, 2021
    Date of Patent: August 15, 2023
    Assignee: International Business Machines Corporation
    Inventors: Tian Jiao Zhang, Yuan Feng, Yan Yan Han, Su Li Hou, Xue Ying Zhang, Jing Xu, Ling Zhuo
  • Patent number: 11704406
    Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.
    Type: Grant
    Filed: September 12, 2022
    Date of Patent: July 18, 2023
    Assignee: Abnormal Security Corporation
    Inventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
  • Publication number: 20230221847
    Abstract: An embodiment includes detecting an interface element and an element attribute of the interface element in a series of views of a user interface, and then after an update of the user interface, detecting a candidate element and a candidate element attribute in a series of views of the updated user interface. The embodiment then determines that the updated user interface lacks any errors using a decision tree that includes comparisons of all interface elements of the user interface to corresponding candidate elements of the updated user interface. The embodiment then generates an optimized decision tree based at least in part on an analysis of the comparisons of the user interface to the updated user interface resulting in a condition that allows for the determining of a lack of errors based on comparisons of a subset of the interface elements to corresponding candidate elements.
    Type: Application
    Filed: January 13, 2022
    Publication date: July 13, 2023
    Applicant: International Business Machines Corporation
    Inventors: Yuan Feng, Yan Yan Han, Ling Zhuo, Tian Jiao Zhang, Jing Xu, Xue Ying Zhang, SU LI HOU
  • Publication number: 20230208876
    Abstract: Selectively rewriting URLs is disclosed. An indication is received that a message has arrived at a user message box. A determination is made that the message includes a first link to a first resource. The first link is analyzed to determine whether the first link is classified as a non-rewrite link. In response to determining that the first link is not classified as a non-rewrite link, a first replacement link is generated for the first link.
    Type: Application
    Filed: December 21, 2022
    Publication date: June 29, 2023
    Inventors: Yea So Jung, Su Li Debbie Tan, Kai Jing Jiang, Fang Shuo Deng, Yu Zhou Lee, Rami F. Habal, Oz Wasserman, Sanjay Jeyakumar
  • Patent number: 11687648
    Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.
    Type: Grant
    Filed: December 9, 2021
    Date of Patent: June 27, 2023
    Assignee: Abnormal Security Corporation
    Inventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
  • Publication number: 20230084737
    Abstract: An approach is provided in which the approach captures a first user activity log of a first user accessing multiple systems and captures a set of second user activity logs of a set of second users accessing the multiple systems. The approach determines a set of system monitoring preferences based the first user activity log and the set of second user activity logs, and scores the multiple systems based on the set of system monitoring preferences. The approach generates a recommended system monitoring list based on the scored multiple systems, and transmits the recommended system monitoring list to the first user.
    Type: Application
    Filed: September 9, 2021
    Publication date: March 16, 2023
    Inventors: Tian Jiao Zhang, Yuan Feng, Yan Yan Han, SU LI HOU, Xue Ying Zhang, Jing Xu, Ling Zhuo
  • Publication number: 20230033036
    Abstract: A method for receiving an audiovisual data set that includes audio and/or visual content, receiving a topical data set that includes an indication of, at least, the plurality of topics and the plurality of subtopics, receiving a time mapping data set that maps each topic and subtopic to an associated time point in the audio and/or visual content, creating a mind map diagram, and presenting the mind map to a user.
    Type: Application
    Filed: July 30, 2021
    Publication date: February 2, 2023
    Inventors: Yan Yan Han, SU LI HOU, Yue Yang, Jing Xu, Xue Ying Zhang, Li Zhou, Zhiyi Xiang
  • Publication number: 20230020623
    Abstract: Deriving and surfacing insights regarding security threats is disclosed. A plurality of features associated with a message is determined. A plurality of facet models is used to analyze the determined features. Based at least in part on the analysis, it is determined that the message poses a security threat. A prioritized set of information is determined to be provided as output that is representative of why the message was determined to pose a security threat. At least a portion of the prioritized set of information is provided as output.
    Type: Application
    Filed: September 12, 2022
    Publication date: January 19, 2023
    Inventors: Yu Zhou Lee, Kai Jiang, Su Li Debbie Tan, Geng Sng, Cheng-Lin Yeh, Lawrence Stockton Moore, Sanny Xiao Lang Liao, Joey Esteban Cerquera, Jeshua Alexis Bratman, Sanjay Jeyakumar, Nishant Bhalchandra Karandikar
  • Patent number: 11552969
    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.
    Type: Grant
    Filed: October 11, 2021
    Date of Patent: January 10, 2023
    Assignee: Abnormal Security Corporation
    Inventors: Sanjay Jeyakumar, Jeshua Alexis Bratman, Dmitry Chechik, Abhijit Bagri, Evan Reiser, Sanny Xiao Lang Liao, Yu Zhou Lee, Carlos Daniel Gasperi, Kevin Lau, Kai Jing Jiang, Su Li Debbie Tan, Jeremy Kao, Cheng-Lin Yeh