Adam Markun
Senior Security Analyst at Google
Virginia, United States
Summary
🤩
Rockstar🎓
Top SchoolAdam Markun is a Senior Security Analyst with 13 years of experience in digital forensics, incident response, and reverse engineering, currently contributing to security at Google. He combines low-level development and network protocol implementation expertise with hands-on threat investigation skills cultivated at firms like Stroz Friedberg. Adam is also active in the ML and docs communities—contributing a DQN tutorial to TF-Agents and improving TensorFlow documentation—which reflects a habit of turning complex technical concepts into clear, reproducible guides. A Middlebury College computer science graduate who minored in Chinese and achieved near-perfect major GPA, he brings disciplined communication and organizational skills honed as a year-round collegiate athlete. Comfortable working independently or leading cross-functional teams, he bridges deep technical analysis with effective stakeholder communication. Uncommonly for a security specialist, he pairs technical rigor with creative pursuits in music and education, reflecting a broad intellectual curiosity.
13 years of coding experience
Bachelor of Arts - BA, Computer Science Major; Minor in Chinese, GPA 3.66, Major GPA 3.94, Bachelor of Arts - BA, Computer Science Major; Minor in Chinese, GPA 3.66, Major GPA 3.94 at Middlebury CollegeChinese, A, Chinese, A at Middlebury Language Schools
English, Chinese
Stackoverflow
1reputation
757reached
0answers
1question
Github Skills (16)
algorithm10
dqn10
machine-learning10
agent10
tensorflow10
ai-agent10
python10
reinforcement-learning10
documentation10
technical-writing10
jupyter-notebook9
embedded6
arduino6
stm6
spi6
Programming languages (9)
Github contributions (5)
tensorflow/docs
Jan 2019 - Jul 2019
TensorFlow documentation
Role in this project:
Technical Writer
Technical WriterContributions:83 commits, 12 PRs, 1 branch in 6 months
Contributions summary:Adam's contributions are focused on modifying and improving the documentation for the TensorFlow project. The commits primarily involve edits to existing tutorials, correcting typos, improving explanations, and organizing content. The user's work directly contributes to the clarity and accessibility of the documentation for users of the TensorFlow library.
deep-learningmachine-learningdeep-neural-networkstensorflow-tutorialstensorflow
tensorflow/agents
Aug 2019 - Sep 2019
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Role in this project:ML Engineer
ML EngineerContributions:14 commits, 2 PRs, 4 comments in 16 days
Contributions summary:Adam's contributions primarily focus on developing a DQN tutorial within the TF-Agents framework. The commits demonstrate the creation and modification of a Jupyter Notebook (`.ipynb`) for training a DQN agent on the Cartpole environment. The changes include setting up the environment, defining the agent, implementing policies, utilizing a replay buffer, and visualizing results, effectively guiding users through the RL training process.
scalabletf-agentsmultiagent-reinforcement-learningtensorflow-librarymulti-armed-bandits
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