Santanu Bhattacharya resumes & CV records
Resumes
Project & Program Management At Paypal/Ebay
Location:
San Francisco Bay Area
Industry:
Information Technology and Services
Santanu B Bhattacharya, 597116 Via Correto Dr, Austin, TX 78749
Santanu Bhattacharya Phones & Addresses
7116 Via Correto Dr, Austin, TX 78749
Fremont, CA
Santa Clara, CA
Sunnyside, NY
Suffern, NY
Park Ridge, NJ
Hillsdale, NJ
Allendale, NJ
Warrenton, VA
San Jose, CA
4310 44Th St APT 6B, Sunnyside, NY 11104 201-2631152
Social networks
Santanu B Bhattacharya
Linkedin
Work
Position:
Sales Occupations
Education
Degree:
Bachelor's degree or higher
Emails
Industries
Information Technology and Services
Mentions for Santanu B Bhattacharya
Publications & IP owners
Us Patents
Application Programming Interface Anomaly Detection
US Patent:
2021009, Apr 1, 2021
Filed:
Oct 1, 2019
Appl. No.:
16/589990
Inventors:
Nagraj K. Naidu - Foster City CA, US
Sheeban Raza Zaheer Shaikh - Foster City CA, US
Christopher Patrick - Foster City CA, US
Santanu Bhattacharya - Foster City CA, US
Sheeban Raza Zaheer Shaikh - Foster City CA, US
Christopher Patrick - Foster City CA, US
Santanu Bhattacharya - Foster City CA, US
International Classification:
G06F 9/54
G06Q 20/20
G06Q 20/20
Abstract:
A central server receives API calls requesting services. The central server identifies whether the API calls are associated with a merchant. A distribution is constructed based on the API calls. The central server further executes a pre-defined rule to identify a set of the API calls belonging to a maximum percentile in the distribution and a set of the API calls belonging to a minimum percentile in the distribution before estimating a set of the anomalous data points with one or more goodness of fit functions against the maximum percentile and the minimum percentile. A GUI receives a critical value from a user. In response to receiving the critical value, the central server generates probabilities of the set of the anomalous data points before displaying a set of the anomalous data points in response to the probabilities being less than the critical value.
Machine Learning Based Ranking Of Private Distributed Data, Models And Compute Resources
US Patent:
2021001, Jan 14, 2021
Filed:
May 29, 2020
Appl. No.:
16/888654
Inventors:
- Austin TX, US
Tabish Imran - Mumbai, IN
Santanu Bhattacharya - Austin TX, US
Karishnu Poddar - Mumbai, IN
Tabish Imran - Mumbai, IN
Santanu Bhattacharya - Austin TX, US
Karishnu Poddar - Mumbai, IN
Assignee:
S20.ai, Inc. - Austin TX
International Classification:
G06N 5/04
G06N 20/00
G06N 20/00
Abstract:
A method for ranking includes the steps of receiving, at least one model from a central server to form at least one model node; training, the at least one model node with at least one data node to generate a trained model; generating, a weight from each of the at least one data node for the trained model; transferring, the weight from the at least one data node to the central server; inferencing, an inference output using the trained model and the data node; determining, an edge between the at least one data node and the model node, wherein the edge is determined depending on the influence of the data node or the model node on each other in generating the trained model and the inference output; determining a score for the data node and the model node based on the edge formed.
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