Oliver Chang is a computer science and engineering PhD student at UC Santa Cruz. His research focuses on robust and efficient deep reinforcement learning. His work has applications to autonomous vehicles, efficient data sampling, and out of distribution learning. His current work examines how salient maps could be a memory efficient medium to store in a replay buffer.

He holds a B.A. in Computer Science and Mathematics from Pomona College. Outside of research, Oliver enjoys running, watching baseball, and solving math puzzles - but not necessarily in that order.

• 🧠 I’m currently working on deep reinforcement learning, autonomous vehicles, and salient maps (XAI)
• 🐒 Exploring efficient and salient replay buffers for DRL algorithms
• 🤝 I’m looking to collaborate on deep reinforcement learning projects! If you have a cool environment and are looking for someone to implement DRL methods, let me know!
• 🤔 Would love to learn more about transformer architectures
• 💬 Ask me about my baseball obsession
• 📫 How to reach me: elochang(at) u c s c . e d u
• 🏃🏻‍♂️ Fun fact: I ran a half-marathon in 1 hour and 9 minutes (5:17 min/mile)!