About

I am a student at Johns Hopkins University in the Electrical Engineering and Computer Science departments.

These days I’m mostly interested in Machine Learning and Natural Language Processing. Much of my time is spent with The Cybernetics Implantable Devices Lab, where I work on small and interpretable models as well as niche things like the effects different data splitting strategies. In the past, I’ve been heavily involved in robotics 🤖 and mobile development. You can see my automated cocktail machine here. I’m also a big fan of entrepreneurship and innovation 🚀. If you find me in the halls i’ll probably be discussing a new project or two.

My research and career interests lie at the intersection of computer science and engineering. Many of my projects are heavily math and data orientated and are largely based on my own entrepreneurial desires.

Selected Publications #

• Time Scale Network: A Shallow Neural Network For Time Series Data Trevor Meyer, Camden Shultz, Najim Dehak, Laureano Moro-Velazquez, Pedro Irazoqui, Time Scale Network: A Shallow Neural Network For Time Series Data. arXiv, 10 Nov. 2023. arXiv.org, https://doi.org/10.48550/arXiv.2311.06170.
• Camden Shultz, Trevor Meyer, Pedro Irazoqui. Randomized Data Splitting Leads to Inflated Performance for Seizure Forecasting Algorithms. American Epilepsy Society Annual Meeting, 2023. abstract.

Teaching #

• (Spring 2024) EN.601.471/671 NLP: Self-supervised Models w/ Dr. Daniel Khashabi
• (Fall 2023) EN.601.465. Natural Language Processing w/ Dr. Jason Eisner
• (Spring 2022, Fall 2022, Spring 2023) EN.601.226. Data Structures w/ Dr. Ali Madooei
• (Fall 2021) EN.601.220. Intermediate Programming w/ Dr. Joanne Selinski
• (Spring 2021, Fall 2021) 171.102. General Physics for Physical Science Majors.
• (Fall 2020) 171.101. General Physics for Physical Science Majors .