Join the experts making groundbreaking advances across a variety of AI applications, specifically deep learning, including image classification, video analytics, speech recognition, and natural language processing.
AI and Deep Learning will be front and center at GTC 2017. Explore key industries, including healthcare and financial services. Rising AI startups will discuss key technologies and discoveries. Innovative researchers will speak to critical breakthroughs accelerated with GPU deep learning.
The Deep Learning Institute is a key part of the GTC experience, providing hands-on workshops using NVIDIA’s latest GPU-accelerated deep learning platforms. Last year, more than 7,000 people were trained on deep learning. Read the blog to learn more.
Senior Research Scientist
OPENAI, Senior Research Scientist
ABOUT THE SPEAKER: Ian is a Senior Research Scientist. He is the lead author of the textbook Deep Learning (www.deeplearningbook.org). He studies new methods to improve deep learning. His interests include generative models, machine learning in the adversarial setting, and accelerating the training of neural networks. He has contributed to several open source machine learning libraries that leverage CUDA, including Theano, Pylearn2, and TensorFlow.
FACEBOOK, Research Engineer
ABOUT THE SPEAKER: Soumith Chintala is a Research Engineer at Facebook AI Research. Prior to joining Facebook in August 2014, Soumith worked at MuseAmi, where he built deep learning models for music and vision targeted at mobile devices. In the past, Soumith worked on state-of-the-art deep learning models for pedestrian detection, natural image OCR, depth-images among others while driving his research heavily using CUDA and multiple GPUs.
TWITTER, Tech Lead
ABOUT THE SPEAKER: Clement has a PhD in Deep Learning with LeCun at NYU. He founded Madbits which was acquired by Twitter, building core deep learning stack at Twitter Cortex.
Data Science Consultant
CHILDREN'S HOSPITAL LOS ANGELES, Data Science Consultant
ABOUT THE SPEAKER: David Ledbetter has an extensive and deep understanding of decision theory. He has experience implementing various decision engines, including convolutional neural networks, random forests, extra trees, and linear discrimination analysis. His particular area of focus is in performance estimation, where he has demonstrated a tremendous ability to accurately predict performance on new data in nonstationary, real-world scenarios. David has worked on a number of real-world detection projects, including detecting circulating tumor cells in blood, automatic target recognition utilizing CNNs from satellite imagery, make/model car classification for the Los Angeles Police Department using CNNs, and acoustic right whale call detection from underwater sonobuoys. Recently, David has been developing a CNN to generate personalized treatment recommendations to optimize patient outcomes using unstructured electronic medical records from 10 years of data collected from the Children's Hospital Los Angeles Pediatric Intensive Care Unit.
MICROSOFT, Senior Researcher
ABOUT THE SPEAKER: Xiaodong is a Senior Researcher in the Deep Learning Technology Center, Microsoft Research, Redmond, WA, USA. He is also an Affiliate Full Professor in the Department of Electrical Engineering at the University of Washington (Seattle) serving in the PhD reading committee. His research interests include deep learning, speech, natural language, vision, information retrieval, and knowledge representation and management. He has published in IEEE TASLP, IEEE SPM, Proc. IEEE, ICASSP, ACL, EMNLP, NAACL, CVPR, SIGIR, WWW, CIKM, ICLR, NIPS and other venues. He has received several awards including the Outstanding Paper Award of ACL 2015. He and colleagues developed the MSR-NRC-SRI entry and the MSR entry that won No. 1 in the 2008 NIST Machine Translation Evaluation and the 2011 IWSLT Evaluation (Chinese-to-English), respectively, and the MSR image captioning system that won the 1st Prize at the MS COCO Captioning Challenge 2015. He has held editorial positions on several IEEE Journals and has served on the organizing committee/program committee of major speech and language processing conferences. He is a senior member of IEEE and a member of ACL.
BAIDU, Senior Researcher
ABOUT THE SPEAKER: Bryan Catanzaro is a research scientist at Baidu's Silicon Valley AI Lab, where he leads the systems team. His research is focused on efficient tools and methodologies for training and deploying large deep neural networks. Before joining Baidu, Bryan was involved in popularizing GPUs for machine learning while working at NVIDIA, including the creation of CUDNN. Bryan received his PhD from the University of California at Berkeley, where he wrote the first Support Vector Machine training library to run on Graphics processors, and created Copperhead, a Python-based DSL for parallel programming.