Owen Oertell — Resume

B.S. in Computer Science. Minor in Mathematics.

Full Time High School Dual Enrollment

Undergraduate Researcher at Sun Lab, Cornell University

September 2022 – Current • Ithaca, NY

• Researching reinforcement learning theory and algorithms.
• Developing and implementing algorithms for reinforcement learning for diffusion models.

Undergraduate Researcher at Cornell University Artificial Intelligence

September 2022 – Current • Ithaca, NY

• Participating in reading groups for Reinforcement Learning, Computer Vision, and MLSystems.
• Developing novel techniques for active learning for taxonomy expansion via coarsened Shannon entropy with Prof. Emaad Manzoor.

Lab Researcher at Dickson Lab, Georgia Institute of Technology

May 2020 – August 2022 • Atlanta, GA

• Adapted C code from bacterial genome to the human genome for novel copy number variation detection algorithm.
• Reduced memory consumption by 300GB while maintaining speed via parallelization and low-level C programming.
• Assisted in development of efficient blood assay technique for bacterial infection identification.
• Increased data gathering speed by 4x by writing code to use multiple cameras in parallel with single camera port.
• Co-authored low budget blood assay technique paper; submission for publication in process.

Head of Engineering at Y STEM and Chess Inc. 501(c)(3)

April 2020 – July 2022 • Boise, ID

• Managed 30 undergraduate and professional SWEs.
• Led development of website: YStemAndChess.com to provide free mentoring of underprivileged children from around the world and expand Y STEM and Chess to tutor more than 800 children.
• Interviewed and hired interns and full time developers.
• Engineered and implemented scalable microservice architecture designs to minimize cost.
• Developed real-time chess pairing and mentoring system.
• Implemented recording storage system allowing parents and students to review lessons.

PrepByAI

July 2021 • Atlanta, GA

• Led development of website: PrepByAI.com, a free ACT preparation site.
• Built machine learning model to identify needs and suggest questions to improve performance using term frequency–inverse document frequency and k-means clustering.
• Over 500 regular users and 9,000+ questions answered to date.

• Chamblee High School Magnet Salutatorian.
• Technology Student Association National Competition (each category 500+ submissions):
  • 2^nd in software development for DataManager project.
  • Top 25 for data science for pulsar star detection deep neural network.
• Georgia Science and Engineering Fair Award for Novel Application of Document Distance for CNV Detection.
• National Merit Scholarship Recipient.
• Presidential Scholar Semi-finalist.

• Languages: C (OpenACC, OpenMP), Python C++, Java, SQL, C#, JavaScript, Ruby, HTML/CSS
• Developer Tools: Jupyter Notebooks, Git, Docker, Kubernetes, VS Code, Amazon AWS, VIM, Makefiles
• Libraries: TensorFlow, Valgrind, Numpy, Pandas, OpenCV, Pillow, Matplotlib
• Frameworks: React.js, Angular.js, Electron.js, Node.js, Express.js, Svelte, Tailwind.css, .NET core
• Databases: PostgreSQL, MongoDB