Courses

M.S. / Ph.D. — Computer Science, University of Maryland

GPA: 4.0/4.0

Fall 2022

• CMSC 723: Graduate Natural Language Processing by Prof. Jordan Boyd-Graber

• CMSC 848C: Selected Topics in Information Processing; Human-AI Interaction by Prof. Hal Daumé III

Spring 2022

• CMSC 828L: Advanced Topics in Information processing: Deep Learning by Prof. David Jacobs

• CMSC 764: Advanced Numerical Optimization by Prof. Tom Goldstein

• Teaching Assistant for CMSC 848Q: How and Why Artificial Intelligence Answers Questions by Prof. Jordan Boyd-Graber.

Fall 2021

• CMSC 828I: Advanced Techniques in Visual Learning and Recognition by Prof. Abhinav Shrivastava

• CMSC 828J: Advanced Topics in Information Processing; Common-sense Reasoning and Natural Language Understanding by Prof. Rachel Rudinger

• Teaching Assistant for CMSC 250: Discrete Structures

MOOCs

• Five course Deep Learning Specialization by Prof. Andrew Ng, deeplearning.ai
  1. Neural Networks and Deep Learning
  2. Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
  3. Structuring Machine Learning Projects
  4. Convolutional Neural Networks
  5. Sequence Models
• Machine Learning by Prof. Andrew Ng, Stanford University