Feng Gu is a senior data scientist at Privacy Analytics, where she has been performing statistical re-identification risk measurement and providing clients with data anonymization strategies across various jurisdictions since 2021.
Feng holds a master’s degree in psychology from Carleton University, specializing in mathematical cognition, and graduated as a recipient of the Senate Medal for Outstanding Academic Achievement.
Feng is committed to maximizing data utility while protecting data privacy to ensure safe and responsible uses of data. She also helps organizations develop privacy frameworks and performs architectural assessment to provide operational guidance. Prior to joining Privacy Analytics, Feng worked at the Institute of Mental Health Research at Royal Ottawa Mental Health Center for three years, collecting and analyzing clinical research data, including structured, unstructured, and imaging data, in collaboration with Beth Israel Deaconess Medical Center of Harvard Medical School.
Situation: California’s Consumer Privacy Act inspired Comcast to evolve the way in which they protect the privacy of customers who consent to share personal information with them.
Situation: Integrate.ai’s AI-powered tech helps clients improve their online experience by sharing signals about website visitor intent. They wanted to ensure privacy remained fully protected within the machine learning / AI context that produces these signals.
Situation: Novartis’ digital transformation in drug R&D drives their need to maximize value from vast stores of clinical study data for critical internal research enabled by their data42 platform.
Situation: CancerLinQ™, a subsidiary of American Society of Clinical Oncology, is a rapid learning healthcare system that helps oncologists aggregate and analyze data on cancer patients to improve care. To achieve this goal, they must de-identify patient data provided by subscribing practices across the U.S.
Situation: Needed to ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR.
Situation: Needed to enable AI-driven product innovation with a defensible governance program for the safe and responsible use
of voice-to-text data under Shrems II.
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