I am a M.S. candidate student in Computer Science at Washington University in St. Louis and joined Ponce Lab in 2019. My main research area is using generative adversarial networks (GANs) to maximize the activity of individual neurons in the brain, through the synthesis of artificial images, and utilizing deep learning models to understand the emergence of mind from the brain.
My research interests include signal and image processing, large-scale optimization, machine learning, computer vision, and statistical inference.
I received my B.S. in Computer Science and B.S. in Electrical Engineering at Washington University in St. Louis in 2020. I am the Co-president of Tau Beta Pi Engineering Honor Society, Missouri Gamma Chapter.
When not in the lab, I enjoy water-color painting, hiking and teaching my cockatiel Ashe cool tricks.
Ponce Laboratory under Dr. Carlos Ponce MD. PhD. in Department of Neuroscience in Washington University in St. Louis School of Medicine
Exploring black-box attacks using generative adversarial networks.
Automated visual recognition has the potential to change many facets of society, from biomedical imaging to security and transportation. Convolutional neural networks (CNNs) are the best models for visual recognition, and while they show enormous promise, they are notably vulnerable to "black-box attacks" -- malicious inputs designed to make the networks make mistakes (Papernot et al. 2016, Practical Black-Box Attacks against Machine Learning). Because CNNs share many properties with the brain, we can understand what kind of attacks are particularly effective on the most resilient CNNs, by crafting attacks that manipulate activity in the brain.
The Ponce lab has shown that it is possible to use generative adversarial networks (GANs) to maximize the activity of individual neurons in the brain, through the synthesis of artificial images. I will explore which types of GANs are best in achieving this goal, in both macaque brains and convolutional neural networks.
Aravamuthan Laboratory under Dr. Bhooma Aravamuthan M.D., DPhil in Department of Neurology in Washington University in St. Louis School of Medicine
I am developing an open-field, video-based animal pose tracking framework using computer vision.
AIM Laboratory under Dr. Shantanu Chakrabartty in Department of Electrical Engineering in Washington University in St. Louis.
I investigated sonification techinique that can be used to visualize high-dimensional data like images. The goal is to understand the benefits of sonification compound to visual representations especially in the context of human-in-the-loop systems
Computer Vision Projects#CV
Mini Garage Controller#IoT
3R Robotics#Control System