Private machine learning at Apple. Computer science Ph.D at Cornell.
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Apple Inc.
Data Scientist
June 19, 2026 – Present
minitorch-quizzes-csong27
January 31, 2024 – January 31, 2024
minitorch-quizzes-csong27 created by GitHub Classroom
View Projectauditing-text-generation
May 27, 2019 – June 18, 2019
Code for Auditing Data Provenance in Text-Generation Models (in KDD 2019)
View Projectproperty-inference-collaborative-ml
November 28, 2018 – May 28, 2019
Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
View Projectml-model-remember
October 14, 2017 – October 15, 2017
Code for Machine Learning Models that Remember Too Much (in CCS 2017)
View Projectmembership-inference
June 6, 2017 – November 15, 2017
Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
View ProjectNgramNeuralNetworks
November 6, 2015 – December 24, 2015
This is the final course project for natural language processing
View ProjectCultural Fit Analysis
The candidate's project history is heavily focused on academic research in machine learning privacy and security, primarily using Python. While this demonstrates deep technical expertise in a niche area, the diversity of projects and technologies is limited. The current role at Apple as a Data Scientist aligns well with the target role, but the overall breadth of experience outside of ML privacy research is not evident from the provided data. This specialization might indicate a strong fit for roles requiring deep expertise in ML security but less so for broader data science roles requiring diverse skill sets.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. Psychometric and English test scores are 0, providing no basis for evaluation.