Working Experience
Research Assistant, Spring 2017 - Present
Themes: Deep Learning, Machine Learning, Computational Biology
Developing deep learning approaches for pixel-level predictions on biological images
Key techniques: U-Nets, CNNs, GANs, Attention mechanism, Skip connections
Investigating the interpretability of deep neural networks for both images and text models
Key techniques: Feature visualization, Optimization, Saliency map, Policy gradient, Discriminative learning, Reinforcement learning
Machine Learning Engineer Intern, Facebook, Summer 2020
Topic: Building Efficient Lightweight Baselines for Offline Explorations
Key techniques: Data sampling, Feature reduction
Summer Research Intern, NEC Labs America, Summer 2019
Topic: Multi-modal Information Retrieval via Deep Active Canonical Correlation Analysis
Key techniques: Deep CCA, Active learning, spectral clustering