applied ml engineer. interested in robotics, wearables, and the intersection of biology and tech.
Northwestern Formula Racing Software (EV)
Bilateral Robotic Thumb and Finger with Haptic Feedback for Radioactive Laboratory Settings (RDS 2024)
MRI-Compatible Chest Compression Device (BME Capstone, Robert B. Taggart Best Design Award)
Morphology Evolution with Differentiable Physics Engines (Xenobot Lab)
Image Processing on C.Elegans (Mangan Group)
Skin-Interfaced Wearable for Vocal Fatigue (Rogers Lab)
Butterfly Effect (Dance 335 Performance and Technology Final Project)
Perlin Noise Flow Field Simulation
Weber Arch Model
2020 – 2024
B.S. Biomedical Engineering
M.S. Computer Science
Hi! I'm a machine learning engineer with a background in biomedical engineering and robotics.
My main interests lie in 1) developing robots inspired by intelligent biological systems (such as ourselves) and 2) using computational biology and neuroscience to further our understanding of the human body to better interface with it.
I am currently a MLE at Scale AI working on computer vision for government use cases. I previously interned at Amazon Robotics, Microsoft, and two seed stage startups. In college, I was in the Mangan Group working on quantitative biology research (2021–2023) and the Xenobot Lab working on differentiable evolutionary robotics (2023-2024). I was also on Northwestern's Formula SAE team for four years, where I laid the software groundwork for our first EV car.
In my free time, I like to dance and spend time with my cat Toast. Please feel free to contact me or connect on LinkedIn to chat!