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Thursday, 18 January 2018 08:20

Basic SQL Workshop in SRTC

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Aworkshop on Basic of SQL Programing will be held on Jan 28 2018 (Bahman 8, 1396) by Dr. Sayed Jamal Mirkamali, Platform Department Chair in Statistical Research and Traning Center, Tehran, Iran. Dr. Mirkamali is assitant professor of Statistics in Arak University. For more information, please take click on the following link:

http://goo.gl/fmvBDR

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A two-day workshop on Monte Carlo Simulation ith R will be held on Feb. 14 - 15, 2018 (Bahman 25-26, 1396) by Dr. Mahdi Salehi, Resident Member of SDAT, and Dr. Vahid Fakoor in Fersousi University of Mashhad. Mahdi is assitant professor of Statistics in University of Neyshabur. For more information, please take contact us through 051-38806206. 

 

Thursday, 18 January 2018 07:29

R Workshops Series in Shiraz University

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A Series of Workshops on R Statistical Software will be held by Scientific Data Analysis Team and Shiraz University in Department of Statistics, Shiraz University, Shiraz.  For more information, please take a look at the workshops homepage on http://sdat.ir/RShiraz

 

 

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The 3rd Series of Workshops on Advanced Statistical Methods in Cognitive Sciences will be held by Scientific Data Analysis Team and Neuroimagin Analysis Group at Imam Khomenini Hostpital, Medical Imaging Center.  For more information, please take a look at the workshops homepage on http://sdat.ir/statcog96 or join the workshops Telegram group through https://t.me/StatCog.

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The Conference on Modern Methods in Insurance Pricing and Industrial Statistics (MIPIS 2017) was held at the Bu-Ali Sina University in Hamedan, Iran,  from September 3rd to September 5th, 2017. 

This conference has been jointly organized by a team from Bu Ali Sina University, by Kristina Lurz, the former chair of y-BIS, the society of Young Business and Industrial Statisticians under ISBIS, and Professor Søren Asmussen from Aarhus University in Denmark. 

Thursday, 02 November 2017 05:50

R workshop in Monte Carlo Simulation

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A two-day workshop on Monte Carlo Simulation ith R will be held on November 22 - 23, 2017 (Azar 1-2, 1396) by Dr. Mahdi Salehi, Resident Member of SDAT, in Fersousi University of Mashhad. Mahdi is assitant professor of Statistics in University of Neyshabur. For more information, please take contact us through 051-38806206. 

 

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A talk on "It's a Chancy, Chancy, Chany Collaboration: Fibber Processes and Multivariate Spatial Point Processes in Cognitive Science" will be given by Dr. Farzaneh Safavimanesh, the head of the SDAT Research Department, at the New Challenges in Applied Mathematic seminar. This seminar is held on Sharif University of Technology on July 16-20. For more information, you can take a look at sharif.ir/nciam.

 

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A series of workshops will be held on Statistical Methods in Cognitieve Science. For more information, please take a look at the following page: 

http://sdat.ir/statcog94

 

 

 

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"Modern Methods in Insurance Pricing and Industrial Statistics" conference will be Held in 3-5 September, 2017, Bu Ali Sina University, Hamedan, Iran. The purpose of the conference is to bring together young and senior academics and people working in insurance and other areas of industrial applications of statistics, and to strengthen the links between the respective communities in Iran and abroad. 

For more information please visit Persian local website address: http://sdat.ir/mipis96 

Or English Arhus University website address: http://thiele.au.dk/events/conferences/2017/modernmethods/ 

 Emai: This email address is being protected from spambots. You need JavaScript enabled to view it. 

Important Dates

  • Deadline for abstract submission: June 22, 2017
  • Notification of acceptance of abstracts: July 6, 2017
  • Deadline for early registration and payment: July 22, 2017

Invited speakers

  • Hansjörg Albrecher, University of Lausanne, Switzerland
  • Søren Asmussen, Aarhus University, Denmark
  • Alireza Edalati, Actuary at VHV Insurance AG, Germany
  • Amin Hassanzadeh, Shahid Beheshti University, Iran
  • David Rios Insua, Rey Juan Carlos University, Spain
  • Gholamreza Nakhaeizadeh, Karlsruhe Institute of Technology, Germany
  • Jens Perch Nielsen, CASS Business School, United Kingdom
  • Amir Safari, Insurance Research Center, Iran
  • Ali Shojaie, University of Washington
 

Short Courses

  • "Introduction to Machine Learning with Industrial Applications" by Ali Shojaie. Date: 2nd September, 2017.
  • "Insurance Ratemarking with GLM using SAS" by Alireza Edalati, Actuary at VHV Insurance AG, Germany. Date: 2nd September, 2017
  • "Risk Management with Big Data and Applications in Industry" by David Rios Insua, Spain. Date: 4th September, 2017

For the short courses there will be a fee, which is kept as low as possible just to cover the expenses.

Thursday, 04 May 2017 20:48

KDD bigdas 2017

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The first workshop on Big data analytics-as-a-Service: Architecture, Algorithms, and Applications in Health Informatics is taking place on August 14, 2017 (in conjunction with KDD 2017) in Halifax, Nova Scotia, Canada. The workshop will consist of a combination of invited keynote speakers, panel discussion, and paper/poster presentations. We allocate significant time for open discussions on sharing best practices and future directions. 

Workshop homepage: http://bigdas.org 

Call for Papers

This is a new and emerging area for the KDD community and we hope this workshop will bring together researchers and interested audiences to explore the open problems, applications, and future directions in Big data analytics-as- a-Service: Architecture, Algorithms, and Applications in Health Informatics. We invite submission of papers explaining innovative research studies on all aspects of big data analytics and its application in health informatics. Work-in-progress papers, demos, experimental studies, open-source developments, and visionary papers are also welcome. Suggested topics include (but are not limited to) the following with the focus of health informatics application area:

    • Big data machine learning algorithms
        Big data semi-supervised learning, active learning, inductive inference, organizational learning, evolutional learning, transfer learning, manifold learning, probabilistic and relational learning
        Big data deep learning
        Big data decision support systems
        Big data scientific visualization
        Big temporal data mining
        Big data time series and sequential pattern mining
        Big data clinical/biomedical text analytics
        Automatic semantic annotation of medical content
        Large-scale classification, clustering, and interpretation of biomedical images and videos
        Genetic data analytics, mining big gene databases and biological databases
    • Gold Standards
        Feature engineering considerations and selection
        Algorithm considerations and selection
        Analysis selection criteria
    • Systems Architecture
        Infrastructures for big data analytics
        Scalable and high throughput systems for large-scale data analytics
        Performance evaluation or comparative study of big data analytics tools, such as DataMelt, RapidMiner, Orange, Rattle, Apache Spark MLlib, Apache Mahout, etc.
        Performance evaluation or comparative study of Machine Learning as a Service platforms, such as BigML, Microsoft Azure, Amazon Machine Learning, Google Cloud Prediction API, IBM Watson Analytics, etc.
        Integration PaaS (iPaaS) supporting Big Data applications and services
        Application of cloud computing to big data analytics
    • Big data analytics-as-a-Service
        Big data machine learning-as-a-Service
        Turning big data health informatics into WWW services
        Big data deep learning-as-a-Service
        Big data infrastructure-as-a-Service

Important Dates:

Paper submissions: May 21, 2017 (11:59 PM Pacific Standard Time)
Supplemental material submissions (Optional): May 27, 2017 (11:59 PM Pacific Standard Time)
Paper notifications: June 21, 2017
Final submissions: July, 10, 2017
Workshop date: August 14, 2017 (Morning 8:00 am to 12:00)

 

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About Us

SDAT is an abbreviation for Scientific Data Analysis Team. It consists of groups who are specialists in various fields of data sciences including Statistical Analytics, Business Analytics, Big Data Analytics and Health Analytics. 

Get In Touch

Address:  No.15 13th West Street, North Sarrafan, Apt. No. 1 Saadat Abad- Tehran

Email: info@sdat.ir

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