The 11th  Workshop on High Dimensional Data Analysis (HDDA-XI)

As data science jargon has begun to flood into government, businesses, and social circles, navigating statistical information and tools can be an arduous and daunting task for policy makers. The rapid growth in the size and scope of data sets in a variety of disciplines have naturally led to the usage of the term, Big Data. The analysis of such data is important in multiple research fields such as engineering, social media networks, bioinformatics, personalized medicine, environmental, neuroscience, astronomy, nanoscience, and financial studies among others. There are many challenging questions. For example, how to acquire, manage, process, analyze, and make sense of big data? Clearly, big data is the future of research in a host disciplines, and trans-disciplinary programs are required to develop the skills for data scientists. For example, many security agencies are using sophisticated number-crunching, data mining, or big data analytics to reveal patterns in information provided by air carriers about passengers.

This workshop will guide the participants from the basics of big data analytics into a deeper discussion of how to handle unconventionally large data matrices in a multitude of applications. For example, genomics data is large and vast accounting for every gene in the body and every gene’s phenotypic expressions. Model selection, post-estimation, and prediction is imperative for anyone conducting an analysis. As we try to advance government and business practices, being able to predict financial, operational, transactional, etc. information is a lucrative skill. For example, many government-funded initiatives aim to provide appropriate advertisements for programs in their emails. In order to target these customers, the analytics team must collect and analyze the data to monitor consumer behavior. Based on their customers’ history and demographics, the analytics team can predict and provide an appropriate email for the program.

The HDDA-XI is continuing to foster the interaction of researchers in the area of Data Science, Statistics, Biostatistics, Mathematics Education and Computer Science especially in high-dimensional data analysis and to stimulate researching in related applications. It will provide a place and opportunity for participants to meet leading researchers in this field and provide opportunities for interaction and discussion by an online meeting. The objectives include:

• Highlight, discuss and expand the breadth of existing methods in high-dimensional data analysis and their potential for the advance of both Mathematical, Statistical and Computer Sciences.

• Identify important directions for future research in the theory of regularization methods, algorithmic development, Bayesian methods and methodology for different application.

• Facilitate Collaboration between theoretical subject-area researchers and practitioners.

• Provide opportunities for trainees and students to meet and interact with leading international researchers in Data and Statistical Sciences.

The Workshop on High Dimensional Data Analysis (HDDA) was first introduced by Professor Ejaz Ahmed in Canada 2011. This year's meeting we collaborate with The 9th Days on Econometrics for Finance (JEF'2022).

The past HDDA workshops were organized as follows:

• HDDA-I, 2011, Fields Institute, Canada

• HDDA-II, 2012, Centre de Recherches Mathématiques, Canada

• HDDA-III, 2013, University of British Columbia, Canada

• HDDA-IV, 2014, Banff International Research Station, Canada

• HDDA-V, 2015, University of Victoria, Canada

• HDDA-VI, 2016, Fields Institute, Canada

• HDDA-VII, 2017, CIMAT, Mexico

• HDDA-VIII, 2018, Cadi Ayyad University, Morocco

• HDDA-IX, 2019, Uppsala University, Sweden

• HDDA-X, 2020, Universitats Padjadjaran, Sumedand, Indonesia