The CRF-C and Cork R-Users are delighted to welcome Avik Sengupta to UCC where he will give an introduction to the Julia programming language. Light refreshments will be served should you wish to continue the discussion with Avik afterwards.
About the talk :
In this talk, Avik will demonstrate how Julia combines dynamic, high level source with a high performance runtime code. He will show what makes Julia unique among programming languages, and how it enables high quality numeric computing libraries. He will survey the machine learning / deep learning ecosystem in Julia, and talk about how that can be extended to new kinds of modelling using differentiable programming. The talk will begin as an introduction to the language, and finish by showing how it opens up new paradigms of computing.
Julia is the fastest high performance open source computing language for data, analytics, algorithmic trading, machine learning, artificial intelligence, and many other fields. Julia solves the two language problem by combining the ease of use of Python and R with the speed of C++. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. For example, Julia has run at petascale on 650,000 cores with 1.3 million threads to analyse over 56 terabytes of data using Cori, the world’s sixth-largest supercomputer. With more than 3 million downloads and +101% annual growth, Julia adoption is growing rapidly in finance, insurance, machine learning, energy, robotics, genomics, aerospace, medicine and many other fields.
Avik Sengupta is the head of product development and software engineering at Julia Computing, contributor to open source Julia and maintainer of several Julia packages. Avik is the author of Julia High Performance, co-founder of two artificial intelligence start-ups in the financial services sector and creator of large complex trading systems for the world's leading investment banks. Prior to Julia Computing, Avik was co-founder and CTO at AlgoCircle and at Itellix, director at Lab49 and head of algorithmic solutions at Decimal Point Analytics. Avik earned his MS in Computational Finance at Carnegie Mellon and MBA Finance at the Indian Institute of Management in Bangalore.