Jeff Erhardt is an executive with more than 11 years of diverse experience at Fortune 400 companies in technology, operations, finance, strategy, and M&A. Erhardt began his career at Advanced Micro Devices where he was responsible for the development and commercialization of leading edge semiconductor devices, eventually authoring more than 30 United States patents. In this capacity, Erhardt was an expert user of numerous statistics and analytics tools (including R) and directed the creation of a cutting edge, fully integrated analysis infrastructure to accelerate the development and introduction of new semiconductor technologies. Most recently Erhardt played a central role in the multi-billion dollar restructuring effort at Spansion, where he advised on operational and performance improvements as well as structured, negotiated, and led numerous complex, multi-national transactions. Erhardt graduated with a B.S. in Engineering Cum Laude, from Cornell University and an M.B.A. with Honors from The Wharton School.
In the past ten years, a new field of data analytics has emerged to deal with the incredible deluge of data flooding the sciences, arts and business. Data scientists overwhelmed by big data technology struggle daily with the complexity of big data solutions, difficulty of applying valid statistical models to analyze the data, and limited insight into the meaning of the data. One of the most popular advanced analytics open source software platform is R, and in recent years has emerged in popularity and functionality as the tool of choice. Over 2 million analysts worldwide in academia and at cutting-edge analytics driven companies such Google, Facebook and LinkedIn use R, including the enterprise version of R delivered by Revolution Analytics. The experience in building open source R solutions with innovations in big data analysis, integration and user experience will be described for Biology and other fields. In particular the management of large data volumes in the context of high performance computing and scaling up will be explained.
WHO SHOULD COME Researchers involved in the following disciplinary areas will find this seminar useful.
Webcast Video for this seminar can be downloaded from here: Seminar_Webcast_R
In today's biological research, massive amount of data are being generated and massive amount of analysis are needed. Unfortunately, our computers are not getting much faster processors. Instead, we are getting larger quantity of processors --- multicore, multi-processor, multi-computer clusters. In order to fully utilize such computing power, we need to use parallel computing techniques. In this hands-on practical, we will demonstrate the use of R computing environment to do parallel computing in the context of solving typical biological problems such as today's next generation sequencing and microarray data.
Hands-on Practical Parallel Computing in R for Bioinformatics
Webcast Video for this hands-on workshop on Parallel R can be downloaded from here: HandsOn_Workshop_R
Registration and ContactRegistration for the seminar and workshop: Register Me Here
If any enquries, please contact
Ms Liu Lizhen and Dr Lim Cheh Peng
Department of Biochemistry
National University of Singapore
Tel: (65) 65163566
Fax: (65) 67777936
Closing date for registration : 7 September 2011.
Brought to you by Biochemistry Core Facility
Last Updated: 18 August 2011
First Created: 18 Aug 2011 Tan Tin Wee