Lucas Frey
Scientist. Developer.
Mostly Harmless.

I am a passionate machine learning engineer with a deep interest in using cutting-edge technology to revolutionize the fields of computer technology, medicine, and autonomous vehicles. My journey in this domain began with a fascination for robotics and how and how AI can transform lives for the better. As I delved into the world of machine learning, I discovered the immense opportunities it presents in addressing crucial issues in healthcare and transportation.

My educational background reflects my determination to excel in these areas. I hold a degree in Computer Science, with a focus on machine learning and artificial intelligence. Throughout my academic journey, I undertook specialized courses that allowed me to gain a comprehensive understanding of the nuances in these domains.

In industry, I have honed my skills by working on diverse machine learning projects. From creating sophisticated algorithms to analyze hundreds of thousands of high resolution images, to implementing optimization frameworks to accelerate scientific discovery. I have collaborated with multidisciplinary teams to build impactful solutions. My ability to bridge the gap between research and application has allowed me to develop practical and scalable machine learning models.

I thrive in challenging environments, where creativity and innovation are encouraged. My problem-solving mindset and adaptability have enabled me to tackle complex issues with an unwavering determination. I am not content with merely following the status quo; instead, I seek opportunities to push the boundaries of what machine learning can achieve.

Experience

    Senior Machine Learning Engineer | Applied Materials | Santa Clara, CA | September 2022 - Present
    • Implemented a dynamical system-based probabilistic deep learning framework to solve process optimization problems
    • Improved model performance by utilizing prior knowledge of domain experts
    • Enabled model/optimization framework to transition seamlessly between local and cloud compute
    • Developed interactive visualizations to enable interpretable model and optimization results
    Machine Learning Engineer / Data Scientist | Lam Research | Fremont, CA | June 2019 - September 2022
    • Lead architect / codebase owner of Lam's repository of data science products used for optimization of complex semiconductor processes
    • Optimized preexisting model framework resulting in 50X speedup in core optimization algorithm
    • Developed fully automated data products (full back-end and front-end development) in support of real process optimization demos, requiring minimal end-user data science expertise
    • Developed defect detection, segmentation and measurement algorithms used by process engineers to analyze thousands of 1500x1500 scanning electron microscope images per week
    • Researched and implemented several Bayesian optimization algorithms for hyperparameter optimization, benchmarking each along a variety of figures of merit (final delivered algorithm reduced computation time from ~8 hours to ~15 minutes with no compromise in predictive accuracy)
    • Constructed a virtual experimental environment with an interface to codebase, enabling statistically rigorous benchmarking of different algorithmic approaches
    • Contributed bugfix and pull request to the Tensorflow GitHub repository
    Software Engineer / Data Science Intern | Lam Research | Fremont, CA | June 2018 - June 2019
    • Developed computer vision algorithms for analyzing high volume, high magnification images of semi- conductors
    • Implemented DenseNet, Inception, and ResNet variant neural networks for image classification and segmentation
    • Documented development process, logged all analytical data and maintained file integrity using Git
    • Presented work on convolution neural networks to a multi-disciplinary group of engineers
    • Participated in intern poster competition
    Computer Science Tutor | Corvallis, OR | October 2017 - June 2018
    • Developed my own curriculum to teach high school student C++, algorithms, and computer science concepts.
    • Taught concepts of pointers, stack vs heap, object orientation and data structures

Education

  • Oregon State University - Bachelor of Science | 2016 - 2019
    Major: Computer Science Applied in Artificial Intelligence
    Minor: Mathematics
    Clubs: Machine Learning/Artificial Intelligence Club
  • Chemeketa Community College - Associate of Arts | 2015 - 2016

Hobbies

  • My physical and mental health are very important to me; My day is always better if I have time to go for a run.
  • I have a passion for traveling, cooking, and reading.
  • Science fiction and psychology books are my favorites, but occasionally I will read comedies.
  • Video and board games are favorite passtimes with friends.
    • Favorite video games: Apex Legends, Counter Strike, Fallout 3/4/NV, Red Dead Redemption 1/2
    • Favorite board games: Dominion, Concept, Codenames, and Twilight Imperium (4th edition)