METU SIAM Student Chapter

We are happy to announce the Institute of Applied Mathematics (IAM) at METU celebrates its 10th Anniversary of the Foundation with ICACM. The conference will take place at the Culture & Convention (CCC) of the METU on October 3rd, 4th, 5th, 6th, 2012. You can visit http://icacm.iam.metu.edu.tr/ for more information.

More importantly, the METU SIAM Student Chapter will also be there to address more people being interested in applied mathematics. You can visit us and get information about SIAM,  METU SIAM Student Chapter.

Hope to see you.

On September 20th,2012 we gathered for the first meeting of the semester. We have many things to do in this semester. In the following weeks, we will be welcoming our new members. Students and graduates being interested in all kinds of applied mathematics, wanting to contribute scientific life are very welcomed.

The first meeting photos can be found at http://www.facebook.com/n/?groups%2F218914604861072%2Fpermalink%2F358318364254028%2F&mid=6c6729bGf480cG3e717c4G96&bcode=epSQ4dL5_1.1348236653.AaT-FtqhDjR2jRje&n_m=devin%40metu.edu.tr

Massive amounts of data are collected every day, often from services we use regularly, but never think about. Scientific data comes in massive amounts from sensor networks, astronomical instruments, biometric devices, etc., and needs to be sorted out and understood. Personal data from our Google searches, our Facebook or Twitter activities, our credit card purchases, our travel habits, and so on, are being mined to provide information and insight. These data sets provide great opportunities, and pose dangers as well.

Four international Math, Applied Math and Statistics organizations (SIAM, AMS, MAA and ASA) have suggested “Mathematics, Statistics, and the Data Deluge” as the theme of this years Math Awareness Month. Our student chapter is proud to present a four day/ two week workshop on the subject. Six scholars from various departments of our university will present lectures on computational and mathematical tools that one can use to work effectively with and model large amounts of data.

The program of our workshop is as follows:

1. May 16, 2012, Wednesday, 11:40-12:30, Estimation of Dynamics under Uncertainty, Gerhard Wilhelm Weber *,
2. May 17, 2012, Thursday, 11:40-12:30, Fractals in Cognitive Science, Annette Hohenberger and Halil Düzcü *,
3. May 17, 2012, Thursday, 14:00-17:30, Introduction to R and GGobi, Ozlem Ilk **,
4. May 23, 2012, Wednesday, 14:00-16:30, MapReduce and Hadoop, Mining Big Data in the Cloud, Aybar Acar *,
5. May 23, 2012, Wednesday, 11:40-12:30, Introduction to Clustering, Cem Iyigun *,
6. May 24, 2012, Thursday, 14:00-15:30, Modeling with MARS and CMARS, Fatma Yerlikaya-Ozkurt * (Cancelled)

** Department of Mathematics, Computer Lab, M202,

* Institute of Applied Math, S209

The R Workshop that will be led by Ozlem Ilk will be completely interactive; the users will be able to implement in realtime everything introduced in the workshop on the computers available in the lab where the workshop will take place. We cordially thank the mathematics department for hosting this event.

All members of our university are invited. If you have any questions please contact us at metusiam@gmail.com.

Fatma Yerlikaya-Ozkurt

Institute of Applied Math, Scientific Computing Program

May 24, 2012, Thursday, 14:00-15:30
Institute of Applied Math, S209

MARS: Multivariate Adaptive Regression Splines
CMARS: Conic (Convex, Continuous) Multivariate Adaptive Regression Splines

(Cancelled)

Conic (Convex, Continuous) Multivariate Adaptive Regression Splines (CMARS), developed at Institute of Applied Mathematics (IAM), Middle East Technical University (METU), is an alternative approach to the Multivariate Adaptive Regression Splines (MARS). MARS is a well-known data mining tool capable of modeling high-dimensional data with nonlinear structure. Flexible nature of MARS modeling leads successful implementation of the method in various application areas. On the other hand, CMARS is based on a penalized residual sum of squares (PRSS) for MARS as a Tikhonov regularization (TR) problem. CMARS treats this problem by a continuous optimization technique, in particular, the framework of Conic Quadratic Programming (CQP). These convex optimization problems are very well-structured, herewith resembling linear programs and, hence, permitting the use of interior point methods. CMARS and MARS methods are preferred by modelers and data analysts in the fields of nonparametric regression/classification, and data mining. By this talk, the implementation of MARS and CMARS methods will be provided on test data. For CMARS algorithm, a user-friendly computing environment which is written in MATLAB will be used. For MARS, R program, a well-known and popular statistical software, will be preferred.

Annette Hohenberger and Halil Düzcü

METU, Informatics Institute, Cognitive Science Program

May 17, 2012, Thursday, 11:40-12:30
Institute of Applied Math, S209

Fractals are self-similar structures with a precise definition in mathematics. They are ubiquitous in nature: coastlines, clouds, flowers, bodily organs, and many more, exhibit self-similarity. Their existence in the cognitive sciences, however, is just beginning to be revealed and their significance is not yet fully appreciated.

In our talk, we will distinguish two kinds of self-similarity: geometrical and statistical self-similarity. An example of the former is the Koch curve; an example of the latter is the power law scaling of probability density functions observed in the temporal patterns of cognitive processes. We will present examples of such power-laws in eye-gaze patterns and response latencies (reaction times) and explain what they possibly reveal about the functioning of the mind.

We will discuss with the audience how the concept of fractals may raise the mutual awareness of cognitive and natural scientists of the similarity of the processes they are studying in their respective areas.

Gerhard Wilhelm Weber

METU, Institute of Applied Mathematics

May 16, Wednesday, 11:40-12:30
Institute of Applied Math, S209

This presentation introduces recent research efforts and results in identifying and predicting time-dependent processes, based on given data and with various degrees of model discontinuity and uncertainty. This generalization is gradually unfolded, while always being motivated by real-world challenges and applications of them.

We aim at displaying joy and interest in state-of-the art applied mathematics and to invite to education, research and developing our countries by its help, in our scientific community. In fact, we try to “make appetite” for this!

Speaker: Dr. Çağrı Haksöz

Sabancı School of Management, Sabancı University, İstanbul, Turkey

cagrihaksoz@sabanciuniv.edu

Seminar : Strategic Value of Bundled Options for Managing Breach of Contract Risk

Date: May 15, 2012, Tuesday, 15:30
Place: Institute of Applied Mathematics, S-209

Abstract

In this talk, my main objective is to demonstrate the strategic value of bundled options in supply chain contracts for managing breach of contract risk. We design and value a bundled option that is composed of contract abandonment and price renegotiation. We show that the bundled option is more valuable for the contract than either of the options, i.e., contract abandonment and price renegotiation, in isolation. The value of the bundled option is less than the sum of the individual option values, hence showing the sub-additive property. We demonstrate that in the presence of high spot price volatility, the bundled option is more valuable when renegotiation date is selected to be closer to the half-life of the contract. We further show that early contract abandonment probability goes down in the presence of renegotiation option. We conclude that a commodity supplier should negotiate a supply chain contract with flexible options at the design stage with a buyer, obtaining contract abandonment and price renegotiation options –as a bundled option—in order to enhance the value of the supply chain contract and manage the breach of contract risk intelligently.

Biography

Professor Haksöz is a faculty member of Operations and Supply Chain Management at Sabancı School of Management, Sabancı University, İstanbul, Turkey. He is also an affiliate member of the Regent’s Centre for Transnational Studies, Regent’s College, London, UK. His current research focuses on supply chain risk management, risk intelligence, managing supply chain networks on the Silk Road, supply chain and energy contract management, product recall risk management and climate change/weather risk. He has published two books, namely Managing Supply Chains on the Silk Road: Strategy, Performance, and Risk (with S. Seshadri and A. V. Iyer, 2011) and Global Perspectives: Turkey (with M. Çakanyıldırım, 2012). His publications appeared in Operations Research, Mathematics of Operations Research, MIT Sloan Management Review, The Journal of Operational Risk, The Journal of the Operational Research Society, and International Journal of Production Research, as well as The Wall Street Journal, The Financial Times, among others. He serves as the Area Editor (Operations) for the International Journal of Emerging Markets as well as the Associate Editor of Transnational Marketing Journal. Before joining Sabancı University, Professor Haksöz taught at New York University, Stern School of Business, Cass Business School, City University of London, UK, and New York University in London. Between 2008-2011, he was an honorary visiting fellow at Cass Business School, City University of London, UK. He also guest lectured at Poznań School of Logistics, Poznań, Poland. Professor Haksöz provides executive teaching and also consults national/international firms and government organizations. He holds a PhD and MPhil in Operations Management from New York University, Stern School of Business and BSc in Industrial Engineering from Bilkent University, Turkey.

Institute of Applied Mathematics, http://www3.iam.metu.edu.tr
Society for Industrial and Applied Mathematics, http://siam.org