REU 2019 Week 2 Volodymyr Bobyr

Overview Background Experience What I Learned First Assignment Insights Research Topics

Background Higher Education School: Stonehill College & University of Notre Dame 3-2 Computer Science & Engineering program Going into third year School: Moved between Ukraine, Greece, Italy, and the US Interests: Computer Science, Math, Philosophy, and Psychology, hence interest in Machine Learning

Experience Machine Learning Video Game Development 2 personal projects (App/Play Store) Interned at Warner Bros Turbine (2018) Machine Learning Coursera deep-learning specialization An evolutional algorithm project involving map navigation

What I Learned Deeper understanding of the theory and mathematics behind CNNs & RNNs Applications of CNNs: Discriminative and Generative Models Hands-on experience Solid introduction to Keras and PyTorch Practices before deep learning took over

First Assignment Purpose: Application of CNNs Dataset: CIFAR100 Framework: Keras My model: Structure: regular convolutions + residual blocks Size: 160k params Validation Set Accuracy: 51.4%

Insights Normalization is very important Residual blocks can yield significant results Expanding is not always necessary Tweaking hyperparameters may be more helpful Difficult to predict required size of the network without much experience

Research Topic Topic: Using Audio Self-Supervision for Situational Safety Classification in Videos Mentor: Robert Browning Idea: Incorporating audio to improve video analysis, as a lot happens off-camera