Who will be speaking at NLP Day Texas

We're just now beginning to announce the speakers. Check this page regularly for updates.

Robert Munro (San Francisco) @WWRob

Robert Munro (Linkedin) is a computational linguist and data scientist working at the leading edge of scalable language technologies. Robert is a world leader in applying machine learning, natural language processing, crowdsourcing and big data analytics to human communication. He has worked in many diverse environments, from Sierra Leone, Haiti and the Amazon to London, Sydney and San Francisco, with organizations ranging from Silicon Valley Startups to the United Nations.
Robert is currently the Principal Product Manager at Amazon AI, where he leads product for Natural Language Processing and Machine Translation. Formerly, he was co-founder of the NLP startup, Idibon.
Robert has published more than 50 papers on natural language processing and is a regular speaker about technology in an increasingly connected world. He completed a PhD in Computational Linguistics as a Graduate Fellow at Stanford University. Outside of work, Robert has learned about the world’s diversity by cycling more than 20,000 kilometers across 20 countries, mostly through the mountains.
Robert Munro will be the MC for NLP Day 2017.

Christopher Moody (SF Bay) @chrisemoody

Chris Moody loves high-performance computing, high dimensions & high fashion. He loves learning the beautiful symmetries between physics, data, and analytics. Went to Caltech, did astrostats & supercomputing and now Data Labs at Stitch Fix. Currently enjoying coding up word2vec, Gaussian Processes, Deep RNNs and t-SNE.

 

 

 

Jonathan Mugan (Austin) @jmugan

Jonathan Mugan (Linkedin) is Co-Founder and CEO at DeepGrammar. Dr. Mugan specializes in artificial intelligence and machine learning. His current research focuses in the area of deep learning, where he seeks to allow computers to acquire abstract representations that enable them to capture subtleties of meaning. Dr. Mugan received his Ph.D. in Computer Science from the University of Texas at Austin. His thesis was centered in developmental robotics, which is an area of research that seeks to understand how robots can learn about the world in the same way that human children do. Dr. Mugan also held a post-doctoral position at Carnegie Mellon University, where he worked at the intersection of machine learning and human-computer interaction. He is also the author of The Curiosity Cycle: Preparing Your Child for the Ongoing Technological Explosion.