CV
Resume
Research Interests
- Image generation, Generative Adversarial Networks
- Automatic/machine colorization, Effective feature fusion
- Contrastive learning, Neuroevolution
Experience
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Spring 2024
Associate Professional Staff I
Johns Hopkins University Applied Physics Laboratory
- Applied research and engineering for machine learning capabilities with the A3G Weapon Control Concepts Development Group.
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Fall 2022
Fall Intern
NASA Goddard Space Flight Center, Greenbelt, Maryland
- Developed multiple neural network regression models to predict in-situ water clarity from multispectral satellite data.
- Built a codebase for data collection, model training, and visualization with flexibility in mind for the NASA team going forward.
- Validated a variety of trained models (w/ various hyperparameters and architectures) for performance on multispectral/in-situ test sets.
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Summer 2022
Summer Intern
NASA Goddard Space Flight Center, Greenbelt, Maryland
- Investigated using unsupervised deep generative models for supplementing current NASA remote sensing datasets.
- Trained a modified StyleGAN2-ADA model to convergence through various training paradigms given scarce data.
- Explored routes to quantitatively evaluate quality of generated samples through trained regression models.
Education
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2023
M.S. in Computer Science
Northwestern University, Evanston, Illinois
- GPA: 3.92/4.00
- Advised by Dr. Aggelos Katsaggelos.
- Thesis: Multi-Stage Automatic Line-Art Colorization with Style and Color Priors
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2021
B.S. in Computer Science
Louisiana State University, Baton Rogue, Louisiana
- Cum laude
- Concentration: Second Discipline in Philosophy
Organizations
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Northwestern AI Journal Club (AIJC), Member
- Presented thesis work “Multi-Stage Automatic Line-Art Colorization with Style and Color Priors”
- Presented review of “Hierarchical Text-Conditional Image Generation with CLIP Latents” by Ramesh, et al.
- Presented review of “Tag2Pix: Line Art Colorization Using Text Tag with SECat and Changing Loss” by Kim et al.
- Presented review of “Segmentation in Style: Unsupervised Semantic Image Segmentation with StyleGAN and CLIP” by Pakhomov et al.
- Presented review of “Unpaired Image-to-Image Translation of Cycle Consistent Adversarial Networks” by Isola et al.
Honors and Awards
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2016
- Tops Honors Award
- Magnolia Scholarship