1. REU 2019 Week 2
Volodymyr Bobyr

2. Overview Background Experience What I Learned First Assignment
Insights
Research Topics

3. 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

4. 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

5. 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

6. 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%

7. 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

8. 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