Mathematical Programming Society Newsletter 81 Mps Chair's Column Note from the Editors Counting and Estimating Lattice Points: Tools from Algebra, Analysis, Convexity, and Probability

November 20, 2009. Along with so many colleagues, I am deeply saddened by the news of Paul Tseng’s disappearance while on a kayak trip on the Jinsha River in China on August 13, 2009. Many of us have many wonderful memories of times spent with Paul – visits, collaborations, conversations, conference social events – and many have been influenced by his scholarly, incisive, and prolific research. A workshop in Paul’s honor will take place at Fudan University next May (see announcement in this issue), and an article on Paul will appear in the next issue of Optima. A Wikipedia entry about Paul’s life and work can be found at http://en.wikipedia. org/wiki/Paul_Tseng. In MPS news, we have introduced a new section on the web site mathprog.org containing links to faculty job listings in optimization and related areas. Click on the “Jobs” tag at the top of the page, and send any listings you wish to advertise on the site to webmaster@mathprog.org. The increasing visibility of optimization in other areas of mathematics, science, and engineering has become ever more apparent in recent months. Optimization is being recognized more and more as an important tool for modeling and analysis and as a key to many interdisciplinary research efforts. I illustrate the point with two recent developments. First, the Institute for Pure and Applied Mathematics (IPAM) at UCLA is organizing a three-month program entitled “Modern Trends in Optimization and its Applications,” consisting of a series of workshops in Fall 2010. Second, the optimization group at Wisconsin was selected to be one of the five “themes” in the Wisconsin Institutes of Discovery, an interdisciplinary research institute under construction on the UW-Madison campus and funded with $150m of private, state, and alumni research foundation grants. No doubt there are other compelling recent examples of the expanding reach of optimization. Optimization is naturally an outward-looking discipline. It challenges domain scientists to articulate what it is they need to learn from a model and to evaluate the strengths and weaknesses of various formulations. Conversely, opportunities for fundamental research in optimization grow, as optimizers are challenged to provide new theory and algorithms for the large and complex problems that arise in new collaborations. Interdisciplinary initiatives provide us with exciting opportunities to collaborate with top researchers in other fields. Each success increases the visibility of optimization and makes it easier to find new openings and collaborations in new areas. Economics provided much of the initial impetus for our discipline. The “zeroth ISMP” took place at the Cowles Commission for Research in Economics in Chicago in 1949; the proceedings can be found at http://cowles.econ.yale.edu/P/cm/m13/. Sixty years later, in the wake of financial and economic crises, the need for rigorous analytical tools in economics and finance is growing once again. Tools based on recent developments in stochastic optimization, robust optimization, complementarity, and algorithmic game theory will be particularly important. The use of optimization in operations research and engineering has grown steadily over the years, in such specific areas as process control, engineering design, and logistics. But it is the past few years that have seen a striking expansion of the application space, into such areas as structural biology and bioinformatics, signal and image processing (including compressed sensing), computational learning, the design and control of electrical grids, and medical applications (e.g. cancer treatment), to name just a few. The applications that gave rise to our field remain as important as ever, and the vitality and variety of new research topics – both fundamental and interdisciplinary – continues to grow. There has never been a more exciting time to be an optimizer!