NVIDIA Deep Learning Roadshow - Downunder Edition (Melbourne)

LECTURE THEATRE HAS BEEN CHANGED TO ACCOMMODATE A LARGER AUDIENCE

Please note the workshop location is now S4 Theatre, 16 Rainforest Walk (same building).
The map reference has been updated.

Introduction

Deep learning is the fastest-growing field in artificial intelligence (AI) and machine learning (ML). It is used in the research community and in industry to tackle some of the most challenging big data problems in computer vision, speech recognition, and natural language processing.

AI researchers and data scientists now have access to a wealth of hardware and software platforms, all powered by NVIDIA GPUs for training and deployment of neural networks. This workshop will give you a chance to experience some of those tools, and introduce NVIDIA's first supercomputer in a box: the NVIDIA DGX-1™ Deep Learning System.

In association with Monash University and MASSIVE, we are pleased to present the Deep Learning Roadshow Downunder Edition (Melbourne). Below you will find a full day technical workshop from our line-up of international deep learning experts, as well as guest speakers from Monash University.

You will see that several sessions have been left up to the audience to decide.

During the registration process, you may nominate from a number of available topics, including questions you would like our experts to consider prior to the workshop, as well as hands-on components (these require a laptop with internet connection, and may involve working in a group).

We look forwawrd to welcoming you to the Deep Learning Roadshow!

Agenda

• 8:30 AM - Arrival and coffe; registration
• 9:00 AM - Welcome
• 9:15 AM - Intro to Deep Learning on GPUs
• 10:00 AM - NVIDIA Deep Learning SDK
• 10:30 AM - NVIDIA DGX-1™ Deep Learning Supercomputer
• 11:30 AM - Expert panel Q&A session
• 12:00 PM - Lunch
• 1:30 PM - Robotic and Bionic Vision: Applications of GPU Computing (Prof Tom Drummond, Monash University)
• 2:00 PM - Intro to RNNs (talk)
  
• 3:00 PM - Afternoon tea and networking session
• 3:30 PM - Object detection using DIGITS (instructor led hands-on)
• Depending on session choices, we will finish between 4-5pm.

Other important information

Parking

At Monash University parking restrictions apply all year and infringement notices will be issued to vehicles parked illegally. Please observe signs at all times whilst on campus. For details visit http://www.monash.edu/people/transport-parking

Lecture theatre location

Note: please ignore the auto-generated map displayed at the bottom of this Eventbrite page in yellow colour scheme.

Interactive and downloadable PDF maps here: http://www.monash.edu/people/maps

Guest expert bio

Tom Drummond

Prof Tom Drummond has been a principal investigator on several EU Framework projects and is a chief investigator in the ARC Centre of Excellence for Robotic Vision. Tom studied mathematics for his B.A. at the University of Cambridge. In 1989, he emigrated to Australia and worked for CSIRO in Melbourne for four years before moving to Perth for his Ph.D. in computer science at Curtin University. In 1998, he returned to Cambridge as a postdoctoral research associate and in 1991 was appointed as a university lecturer and was subsequently promoted to senior university lecturer. In 2010, he returned to Melbourne and took up a professorship at Monash University.

NVIDIA experts bios

Jon Barker

Jon Barker is a Solution Architect with NVIDIA, based in Boulder, CO. Jon helps customers and partners develop applications of GPU-accelerated machine learning and data analytics to solve defense and national security problems. He is particularly focused on applications of the rapidly developing field of deep learning. Prior to joining NVIDIA, Jon spent almost a decade as a government research scientist within the U.K. Ministry of Defence and the U.S. Department of Defense R&D communities. While in government service, he led R&D projects in sensor data fusion, big data analytics, and machine learning for multi-modal sensor data to support military situational awareness and aid decision making. He has a Ph.D. and B.Sc. in pure mathematics from the University of Southampton, U.K.

Pradeep Gupta

Pradeep Gupta is a Lead HPC & Deep Learning Solutions Architect at NVIDIA, where he supports customers and developers across Asia Pacific, Japan and India regions for Deep Learning and HPC application development. Pradeep also works to enable the GPU computing ecosystem in universities and research labs across region. Pradeep is also responsible for running and managing R&D Projects at NVIDIA Technology Centre at Singapore. Before joining NVIDIA, Pradeep had worked with various technologies in High Performance Computing at IBM and HP. Pradeep received a Master's degree in research from the Indian Institute of Science (IISc), Bangalore

Ryan Olson

Ryan Olson is a Solutions Architect in the Worldwide Field Organization at NVIDIA. His primary responsibilities involve supporting deep learning and high performance computing initiations. Ryan is particularly interested in scalable software design that leverages the unique capabilities of the underlying hardware. Prior to NVIDIA, Ryan spent 8 years working at Cray where he helped architect novel solutions that enabled applications to run at scale on some of the world’s largest supercomptuers including Oak Ridge National Lab’s Jaguar and Titan machines as well as the National Science Foundation’s Blue Waters machine at NCSA. Ryan holds a Ph.D. in Physical Chemistry from Iowa State University where he was a member of the Gordon Group working on the popular GAMESS chemistry package.

Ryan also spent a semester during his graduate work visiting Australian National University working with Alistair Rendell on novel hybrid communication methods for onesided frameworks.

Robotic and Bionic Vision: applications of GPU computing