Qian Han
Senior Research Scientist at Meta
Bellevue, Washington, United States
Summary
👤
Senior🎓
Top SchoolQian Han is a Senior Research Scientist and machine learning lead at Meta specializing in the intersection of cybersecurity and AI, with nine years of experience bridging academic research and production systems. He earned a Ph.D. from Dartmouth, where his work on Android malware detection and adversarial generation drew recognition from the Google Android Security Team and led to invited talks at Google HQ. His research combines practical ML, game theory, and systems-level thinking to predict nation-state exploitation of zero-day vulnerabilities and to generate robust adversarial malware samples to harden detectors. Trained originally as an electrical engineer at Tsinghua—where his distinguished undergraduate dissertation won top honors—he brings hardware, signal-processing, and software security expertise to mobile app integrity at scale. Beyond publications, he contributes to applied data-science projects on GitHub, reflecting a hands-on commitment to reproducible ML practice and continual learning.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Dartmouth CollegeBachelor's degree, Electrical and Electronics Engineering, Bachelor's degree, Electrical and Electronics Engineering at Tsinghua University
English, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (5)
jupyter-notebook10
python10
data-science10
pandas8
machine-learning6
Programming languages (5)
Github contributions (5)
Qian-Han/coursera-Applied-Data-Science-with-Python
Jul 2017 - Dec 2017
Repository for coursera specialization Applied Data Science with Python by University of Michigan
Role in this project:
Data Scientist
Data ScientistContributions:15 commits, 1 PR, 15 pushes in 5 months
Contributions summary:Qian appears to be working on assignments and examples related to data science with Python. The commits involve changes to Jupyter notebooks (week1/week1.ipynb, week2/week2.ipynb, etc.), suggesting the implementation of code examples, and exercises. The changes include modifications to code and assignment descriptions, indicating a focus on learning and completing the course material.
applied-data-science-with-pythondata-analysispythonsciencespecialization
Qian-Han/coursera-Deep-Learning-Specialization
Aug 2017 - Apr 2018
Contributions:31 commits, 31 pushes, 1 branch in 7 months
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