Neurobiology: Wellspring of Machine Learning, Spatial AI for 3D Perception & Introduction to Deep Learning
Neurobiology: Wellspring of Machine Learning, Spatial AI for 3D Perception & Introduction to Deep Learning.
Prof Barak A. Pearlmutter, Maynooth University, Neurobiology: Wellspring of Machine Learning
Brief synopsis of lecture content: We will explore the brain as an information-processing device, and hows its apparent operating principles have influenced Machine Learning. Lecture-style delivery.
Prof Thomas Naughton, Maynooth University Department of Computer Science, Introduction to deep learning. Brief synopsis of lecture content: A brief one-hour introduction to deep learning will be given. Live demos will be included using open source software. The full source code (using the Python programming language) will be provided so that participants will be able to replicate the demos after the presentation. Lecture style, with live demosDr John McDonald, Maynooth University , Spatial AI for 3D PerceptionBrief synopsis of lecture content: The last decade has seen considerable progress in the development of systems that must perceive, plan, and act autonomously in 3D real-world environments. This can be seen in the intense research and commercial focus in areas including self-driving cars, unmanned aerial vehicles, augmented reality (AR) and virtual reality (VR), etc. This session will review some of the underlying computational techniques that are key to this area, the emerging framework for SpatialAI, and examples of applications of deep learning within this framework. Lecture style.
Time: 2pm-5pm.Venue: MS Teams. Once registered you will be added to the MS Teams channel (FDSI) before the 4th of September.
Please note each Enterprise Alliance registration is 0.5 of a training day deducted from the overall training allowance per employee registered
Speaker biography: Dr McDonald is a Professor at the Maynooth University Department of Computer Science where he has held a faculty position since 2001. In the past he has been a visiting scientist at the University of Connecticut, the Maynooth University National Centre for Geocomputation (NCG), and the Computer Science and Artificial Intelligence Lab (CSAIL) at the Massachusetts Institute of Technology (MIT). His primary research interests include computer vision, robotics, and machine learning, where he has worked in areas including visual simultaneous localisation and mapping (vSLAM), intelligent vehicle systems, vision based geotechnologies, face and gesture analysis, and digital holography. He is a member of the Maynooth University Hamilton Institute, the Assisted Living and Learning (ALL) Institute, he is a Funded Investigator in Lero – the SFI Research Centre for Software, a named supervisor on the SFI Centre for Research Training in Foundations of Data Science, and a collaborator on the SFI Blended Autonomous Vehicles Spoke. His research has been funded under various research programmes from Science Foundation Ireland, the EU, Enterprise Ireland, and the Irish Research Council.
Speaker biography: Thomas J. Naughton is a Professor in the Maynooth University Department of Computer Science. His research and teaching areas are related to digital holography, optical image processing, and computer theory. He has published over 200 peer-reviewed publications and supervised seven PhD students to completion. During 2008-2011 he was the Coordinator and Scientific Leader of the 40-person-year European Commission FP7 Collaborative Project about digital holography called “Real 3D.” During 2007-2009 he was a European Commission Marie Curie Fellow based in University of Oulu, Finland. He was jointly awarded the IEEE Donald G. Fink Prize Paper Award in 2008. He has 5000+ academic citations and an h-index of 35 according to Google Scholar, and has won over €5M in research funding in his name. Naughton is currently the coordinator of the computer science module of the Certificate in Science at MU for mature students returning to education. He is one of two representatives from Ireland to the International Bebras Task Workshop, which designs the most popular, and most gender-balanced, computer science-related activity for primary and secondary school pupils world-wide: the annual Bebras Computational Thinking Challenge (3 milion participants from 54 countries last year alone, see www.bebras.org).
Speaker biography: Prof Barak Pearlmutter received a BS in Mathematics from CWRU, a PhD in Computer Science from Carnegie Mellon University (where he worked on neural networks the second time they were cool), postdoctoral training in Neuroscience at Yale University, and spent several years in Industry at Siemens Corporate Research and on the faculty at the University of New Mexico. He is currently in the Department of Computer Science at Maynooth University, in Ireland. His main current research interests are two-fold: understanding information processing in the brain, and figuring out how to build artificial systems that exhibit brain-like performance. The focus of the former is currently on exploring criticality in the brain, while the later is upon building mathematical formalizations and programming languages that support the construction of complex adaptive systems.
The SFI Centre for Research Training in Foundations of Data Science will train a cohort of PhD students with world-class foundational understanding in the horizontal themes of Applied Mathematics, Statistics, and Machine Learning.
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