Theophilus Siameh is a Data Scientist at AT&T, Dallas, TX. He’s currently a PhD Candidate Computational Engineering at Mississippi State University. He has a significant background in Mathematics and Computer Science from the University of Ghana. He obtained his Master degree in Mathematical Science from East Tennessee State University. He has extensive experience in Machine Learning, Deep Learning, AI and Computer Vision. Currently, his research focuses on Meta-Learning (Few-Shot Learning applied to Federated Learning). When he’s not solving real-world problems with Python, Java, R, or Scala then he’s playing Soccer on Friday’s and Sunday’s. He’s also big fun of orchestration tools like Docker and Kubernetes applied to Model Deployment. He’s also the author of “Stream Processing with Apache Pulsar: Building Real-Time scalable Data Streaming Applications” (Selling on Amazon).