- Dario Amodei. Dario was one of the lead authors of Deep Speech 2, a speech system which achieved near-human performance on many speech tasks. He is also a main co-author of “Concrete Problems in AI Safety”, which highlights issues related to accidents in machine learning systems. Prior to OpenAI, he worked at Google Brain.
- Filip Wolski. Filip’s recent background is in “practical” modeling, having spent the last few years working in the high-frequency trading space. In the past he enjoyed problem-solving in programming competitions, and won the IOI and ACM ICPC.
- Jack Clark. Jack has spent the past few years writing about artificial intelligence and distributed systems, most recently at Bloomberg and BusinessWeek. His articles have covered technologies like memory networks, image generation, and reinforcement learning for robots, and issues like diversity within AI. As our Strategy and Communications Director, he will help with community outreach, policy, communications, and strategy.
- Scott Gray. Scott was previously an engineer at Nervana Systems where he focused on optimizing the performance of deep networks on GPUs. His assembly-level optimizations for dense linear algebra and convolution remain the fastest available. When not writing software he’s usually spending his time reading up on the latest research in neuroscience and related fields.
- Zain Shah. Zain previously led deep learning efforts to build a collaborative human-machine intelligence system at Clara Labs. He’s also worked on speech synthesis and computational neuroscience, built Mosaic, and founded a mobile behavioral analytics company. He most recently built a GIF search engine using deep multimodal embeddings.
Interns & visitors
We’re also pumped to be working with the following people for a more limited period of time:
- Catherine Olsson. Catherine built OpenAI Gym’s REST API, which has already attracted users in Lua, C++, Java, and Rust. She graduated with a perfect GPA in CS and Brain & Cognitive Science from MIT, and has extensive research experience in computational neuroscience and psychology. Catherine has taught programming and applied math for six years, including outreach to women and underrepresented minorities.
- Harri Edwards. Harri is a PhD student at the University of Edinburgh, where he is researching models that can quickly adapt to new situations by learning to represent datasets.
- Igor Mordatch. Igor is interested in optimal control, machine learning, and their applications to robotics, biomechanics, and neuroscience. His PhD was in automated discovery and learning of complex movement behaviors. He will join the faculty at CMU in September 2017.
- Taco Cohen. Taco is a PhD student working on applied and theoretical problems in representation learning. Most recently he invented group equivariant convolutional neural networks (G-CNNs), a generalization of CNNs that improves the statistical efficiency of these models by exploiting symmetries.
- Tambet Matiisen. Tambet is a PhD student from University of Tartu, Estonia. He previously worked as a software engineer and founded his own startup. His recent projects range from making deep reinforcement learning agents cooperate to predicting a rat’s location from its brain activity. He also wrote an accessible introduction to deep Q-learning.