I am a 5th year Ph.D. student in Neuroscience at Baylor College of Medicine. My research focuses on deep learning and perception neuroscience. I am skilled in scientific computing and programming with Python, (NumPy, TensorFlow, Keras, skLearn) and Matlab, and C++.
Until recently, I have worked at Facebook Reality Labs, Johns Hopkins University, and Cambridge University, where I explored diverse research areas including machine learning, computer vision, image analysis, data visualization, signal processing, and multisensory integration. The key areas I contributed to include:
- Deep Learning: Developing spatiotemporal convolutional neural network architectures for the classification of human perception of touch using functional images.
- Machine Learning: Physiological data modeling using regression and support vector machines and hierarchical clustering using multi-dimensional scaling.
- Computational Neuroscience: Probabilistic models of sensory perception and Bayesian models of multisensory integration using psychophysics and function imaging.
I am an independent researcher with experience working together with scientists, engineers and mathematicians, so skilled in identifying, debugging and solving both scientific and engineering problems.