Data Envelopment Analysis (DEA) has been widely used for performance evaluation. In July 2016, Nanjing Audit University will host The DEA International Conference in Nanjing, China. The keynote speakers are Chiang Kao, Jesus Pastor, and David Sherman.

The North American Productivity Workshop (NAPW) is a Biennial workshp that brings together academic scholars and practitioners in the field of productivity and efficiency analysis. The 9th North American Productivity Workshop (NAPW) will be held in Quebec City, Canada, on June 15 – 18, 2016, at the Hotel Le Concorde-Quebec City.

This workshop brings together thought-leaders from the Civil, Mechanical and Industrial Engineering academic research communities to define a roadmap for Broader Impact innovations for CMMI. This 1.5-day workshop will include academic researcher leaders who have demonstrated innovation in Broader Impact activities, creating measurable economic, human capital, and societal value through their research. People in positions who can advance and promulgate the vision from this workshop will also be invited to participate and contribute to this effort. The output of this workshop will be a report and road map that outlines how new thinking on Broader Impact and institution initiatives can facilitate greater value for NSF investments, how to support panelists to identify, evaluate, and value innovative Broad Impact ideas, and how researchers can reposition their Broader Impact activities to provide a wider footprint of value for NSF investments.

Nonparametric shape constraints, such as monotonicity, convexity or log-concavity, offer statisticians the potential of freedom from restrictive parametric assumptions, while still permitting fully automatic procedures. In this sense, they combine the best of both the parametric and nonparametric worlds. Fundamental statistical problems such as density estimation and regression problems will be treated, along with more exotic questions related to, for example, semiparametric inference.

Inference under shape constraints is a core area of statistical theory and methodology, but the methods often involve challenging optimisation problems and have important applications in many areas, including biology and econometrics.

The College-Industry Council on Material Handling Education (CICMHE) will holds its bi-annual business meeting May 14th and 15th in Atlanta, Georgia. CICHME is an academic/industry council of the Material Handling Industry (MHI) that promotes increased awareness of material handling and logistics through a variety of educational and research activities. The council is organized into two working committees: Events and Projects. At this meeting we will be welcoming 5 new members.

Workshop organized by James Long and Tanya Garcia and feature speakers such as Aurore Delaigle, Ray Carroll, and Ying Wei. Talks emphasize nonparametric methods and measurement error with several interesting applications.

http://www.stat.tamu.edu/measurement-error-workshop/

MODEX is the greatest supply chain show on earth feature 850 leading manufacturing and supply chain providers gathered to showcase their latest and greatest solutions hosted by the Material Handling Industry (MHI). This is the 3rd Modex show which have all been held in Atlanta Georgia. Modex is held in even years while ProMat is held in odd years in Chicago. The College-Industry Council on Material Handling Education (CICMHE) has partnered with the Material Handling Equipment Distributors Association (MHEDA) to offer a special program for students and professors in engineering, technology, manufacturing, operations, supply chain and logistics at the MODEX and ProMat trade shows.

http://www.modexshow.com/

Bodhi Sen is an Associate Professor in the Statistics Department at Columbia University. One of his research interests is nonparametric functional estimation with shape restrictions. He introduces his work by saying,

“Nonparametric function estimation is mostly concerned with understanding the structure (trend/pattern) in the data without making strong parametric assumptions on its form. Most estimation procedures for a nonparametric function (e.g., kernel smoothing), be it a regression function or a probability density, make smoothness assumptions on the underlying function and use local averaging techniques. These estimators depend crucially on tuning parameter(s) (e.g., smoothing bandwidths) and the choice of such parameter(s) can be very problematic.”

His seminar will be held on March 11 at 1:40pm in ETB room 1005; he will also be presenting related work in the Statistics Department on March 10th.

Title: Nonparametric Convex Regression
Abstract: We consider nonparametric least squares estimation of a
convex regression function. We will discuss the characterization,
computation and consistency of the estimator. A computational
framework for multivariate convex regression and some of its variants
— non-decreasing/non-increasing convex regression and Lipschitz
convex regression — will also be presented.

An approach to obtaining smooth convex approximations to the fitted
(piecewise affine) convex least squares estimator, with provide formal
bounds on the quality of approximation, will also be discussed. If
time permits, dimension reduction techniques in this setup will also
be presented.