Dr Qiu Presents “Jump Regression Analysis and Imaging Processing”

The following blog entry is from Jiayang Sun, Professor of Statistics and Professor of Epidemiology and Biostatistics from Case Western University. Dr. Sun is leading the imaging working group  together with Dr. Dani Dushizima, as part of the Statistical and Computational Methodology for Massive Datasets Program.

As part of SAMSI’s imaging working group activity, on Oct 29, Professor Peihua Qiu from U. of Minnesota gave a special talk on “Jump Regression Analysis and Imaging Processing” as an imaging tutorial from statistician’s perspective, based on his book published by Wiley, in addition to his recent research on blind image deblurring (BID), 3d image denosing and registration.

Cover of Peihua Qiu's book

The talk sparked interesting discussions on challenges and needs from a high level to the specifics that may motivate further research and better formulation of the various research problems.

Andreas Artemiou from Michigan Technological University said,

“It was insightful. I did not know the jump regression analysis and its application to imaging. Could I have a copy of the slides?”

SAMSI Postdoctoral Fellow Yi Grace Wang (whose research is in imaging from the mathematical side) said,

“I liked the tutorial very much. It included the big picture of image processing from statistical perspective as well as details from the Jump Regression Analysis in particular. It provided inspiring insights and also enlightened interesting thoughts and debates.”

SAMSI Postdoctoral Fellow Dan Yang (who has identified imaging from a statistical perspective as an area of research she would like to pursue) said,

“For me who has little experience in imaging, I enjoyed the tutorial a lot. It is neither too general nor too technical, giving me a big picture as well as the key ideas. I especially appreciate Prof. Qiu’s presentation for his careful organization, approachable explanation and interesting illustration.”

SAMSI Postdoctoral Fellow Garvesh Rasketti (who was interested to find out more about imaging) noted,

“I enjoyed the talk. I was unfamiliar with jump regression prior to the talk. It seems very applicable to imaging and other areas and the talk has encouraged me to read up more on jump regression.”

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The Undergraduate Workshop Focusing on SAMSI Computational Methodology for Massive Datasets

This blog entry was written by James Anderson, undergraduate student double majoring in statistics-mathematics and economics from the University of Connecticut.

The undergraduate workshop attendees

Attendees and some presenters from the SAMSI undergraduate workshop held October 26-27, 2012.

This undergraduate workshop was notably different from my previous experience, though in no way inferior.  In fact, I would argue the content of this workshop was better for my current position. Massive datasets are surprisingly common and the topics covered included astronomy, high dimension regression, climate change, and image rescaling. In these contexts, we mainly discussed how to manage large datasets without crashing an individual computer.

The other aspect of the workshop, which I really enjoyed, was discussion panels. The students got a chance to talk to people working in academia and industry, as well as graduate students and postdocs. The professionals talked about their respective occupations and how they got to where they are, which was very interesting. On the other hand, the younger group talked about their transitions out of their respective undergraduate programs. This was particularly useful as I will be going through this phase over the next few months. One thing I was once more impressed with was SAMSI’s concern for the attendees. The presenters were happy to go into great detail about their presentations and field any general discipline related questions they could with interested attendees (the presentations had to be kept pretty short). This really impressed me; it didn’t matter if it was in the context of a presentation or not, the mentality seemed to be that the workshop was happening all the time. There was a great opportunity during panels or breaks to ask questions and get information that was quite personalized and would have been hard to find in another way. The workshop gave me a lot of information and resources that will be valuable going forward.