Dean's Seminar Series: Professor Padhraic Smyth

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Professor Geoff Webb, Director of the Monash University Centre for Data Science on behalf of Professor Jon Whittle, Dean of the Faculty of IT, is pleased to invite you to attend the Monash Dean’s Seminar Series - Deep Learning and Statistics: Connections.

Deep learning techniques have received widespread attention in recent years for their impressive performance across a range of prediction problems in areas such as computer vision, machine translation, and speech processing.

What are deep learning techniques? How do we explore the connections between different fields of deep learning techniques? How can we use AI and big data as an enabler to solve big problems?

Hear from Professor Padhraic Smyth, Chancellor's Professor in the Department of Computer Science and Department of Statistics at the University of California, Irvine (UCI) as he shares his insights and vision for advancing data science, applied statistics and AI.

During this workshop you will:

  • Explore several of the key ideas underlying deep learning and their statistical foundations

  • Learn about the relationship between key concepts in deep learning and traditional ideas in statistical modelling and estimation

  • Discover the key differences, both technically and culturally, in how data analysis problems are approached by researchers in various fields


Friday 12th July 2019


2:00 pm- 3:30 pm

Where: Monash University

Clayton Campus: C1, 25 Exhibition Walk

Caulfield Campus: K.309, Building K (Video Conferencing)


This is a free event but seats are limited and registration is required to secure your seat

About Professor Padhriac Smyth

Padhraic Smyth is a Chancellor's Professor in the Department of Computer Science and in the Department of Statistics at the University of California, Irvine (UCI). He is also the founding director of the UCI Data Science Initiative and the UCI Center for Machine Learning and Intelligent Systems. His research interests include machine learning, data mining, pattern recognition, and applied statistics. He is an ACM Fellow (2013), an AAAI Fellow (2010), and a recipient of the ACM SIGKDD Innovation Award (2009). He served as program chair of the ACM SIGKDD 2011 conference and the UAI 2013 conference and in editorial and advisory positions for journals such as the Journal of Machine Learning Research, the Journal of the American Statistical Association, and the IEEE Transactions on Knowledge and Data Engineering. In addition to his academic research he is also active in industry consulting and he served as an academic advisor to Netflix for the Netflix prize competition from 2006 to 2009. Padhraic received a first class honors degree in Electronic Engineering from NUIG in 1984, and the MSEE and PhD degrees (in 1985 and 1988 respectively) in Electrical Engineering from the California Institute of Technology. From 1988 to 1996 he was a Technical Group Leader at the Jet Propulsion Laboratory, Pasadena, and has been on the faculty at UC Irvine since 1996.

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