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Applied Mathematics 1
Applied Mathematics 1 MATH 0180 Intermediate Calculus 1 Applied Mathematics MATH 0520 Linear Algebra 2 1 APMA 0350 Applied Ordinary Differential Equations 2 & APMA 0360 and Applied Partial Differential Equations Chair I 3 4 Bjorn Sandstede Select one course on programming from the following: 1 APMA 0090 Introduction to Mathematical Modeling Associate Chair APMA 0160 Introduction to Computing Sciences Kavita Ramanan CSCI 0040 Introduction to Scientific Computing and The Division of Applied Mathematics at Brown University is one of Problem Solving the most prominent departments at Brown, and is also one of the CSCI 0111 Computing Foundations: Data oldest and strongest of its type in the country. The Division of Applied CSCI 0150 Introduction to Object-Oriented Mathematics is a world renowned center of research activity in a Programming and Computer Science wide spectrum of traditional and modern mathematics. It explores the connections between mathematics and its applications at both CSCI 0170 Computer Science: An Integrated the research and educational levels. The principal areas of research Introduction activities are ordinary, functional, and partial differential equations: Five additional courses, of which four should be chosen from 5 stochastic control theory; applied probability, statistics and stochastic the 1000-level courses taught by the Division of Applied systems theory; neuroscience and computational molecular biology; Mathematics. APMA 1910 cannot be used as an elective. numerical analysis and scientific computation; and the mechanics of Total Credits 10 solids, materials science and fluids. The effort in virtually all research 1 ranges from applied and algorithmic problems to the study of fundamental Substitution of alternate courses for the specific requirements is mathematical questions. -
Alireza Sheikh-Zadeh, Ph.D
Alireza Sheikh-Zadeh, Ph.D. Assistant Professor of Practice in Data Science Rawls College of Business, Texas Tech University Area of Information Systems and Quantitative Sciences (ISQS) 703 Flint Ave, Lubbock, TX 79409 (806) 834-8569, [email protected] EDUCATION Ph.D. in Industrial Engineering, 2017 Industrial Engineering Department at the University of Arkansas, Fayetteville, AR Dissertation: “Developing New Inventory Segmentation Methods for Large-Scale Multi-Echelon In- ventory Systems” (Advisor: Manuel D. Rossetti) M.Sc. in Industrial Engineering (with concentration in Systems Management), 2008 Industrial Engineering & Systems Management Department at Tehran Polytechnic, Tehran, Iran Thesis: “System Dynamics Modeling for Study and Design of Science and Technology Parks for The Development of Deprived Regions” (Advisor: Reza Ramazani) AREA of INTEREST Data Science & Machine Learning Supply Chain Analytics Applied Operations Research System Dynamics Simulation and Stochastic Modeling Logistic Contracting PUBLICATIONS Journal Papers (including under review papers) • Sheikhzadeh, A., & Farhangi, H., & Rossetti, M. D. (under review), ”Inventory Grouping and Sensitivity Analysis in Large-Scale Spare Part Systems”, submitted work. • Sheikhzadeh, A., Rossetti, M. D., & Scott, M. (2nd review), ”Clustering, Aggregation, and Size-Reduction for Large-Scale Multi-Echelon Spare-Part Replenishment Systems,” Omega: The International Journal of Management Science. • Sheikhzadeh, A., & Rossetti, M. D. (4th review), ”Classification Methods for Problem Size Reduction in Spare Part Provisioning,” International Journal of Production Economics. • Al-Rifai, M. H., Rossetti, M. D., & Sheikhzadeh, A. (2016), ”A Heuristic Optimization Algorithm for Two- Echelon (r; Q) Inventory Systems with Non-Identical Retailers,” International Journal of Inventory Re- search. • Karimi-Nasab, M., Bahalke, U., Feili, H. R., Sheikhzadeh, A., & Dolatkhahi, K. -
Spring 2019 Fine Letters
Spring 2019 • Issue 8 Department of MATHEMATICS Princeton University From the Chair Professor Allan Sly Receives MacArthur Fellowship Congratulations to Sly works on an area of probability retical computer science, where a key the Class of 2019 theory with applications from the goal often is to understand whether and all the finishing physics of magnetic materials to it is likely or unlikely that a large set graduate students. computer science and information of randomly imposed constraints on a Congratulations theory. His work investigates thresh- system can be satisfied. Sly has shown to the members of olds at which complex networks mathematically how such systems of- class of 2018 and suddenly change from having one ten reach a threshold at which solving new Ph. D.s who set of properties to another. Such a particular problem shifts from likely are reading Fine Letters for the first questions originally arose in phys- or unlikely. Sly has used a party invi- time as alumni. As we all know, the ics, where scientists observed such tation list as an analogy for the work: Math major is a great foundation for shifts in the magnetism of certain As you add interpersonal conflicts a diverse range of endeavors. This metal alloys. Sly provided a rigorous among a group of potential guests, it is exemplified by seventeen '18's who mathematical proof of the shift and can suddenly become effectively im- have gone to industry and seventeen a framework for identifying when possible to create a workable party. to grad school; ten to advanced study such shifts occur. -
Laudatio for Michael Aizenman NAW 5/4 Nr
Aernout van Enter, Frank den Hollander Laudatio for Michael Aizenman NAW 5/4 nr. 2 juni 2003 107 Aernout van Enter Frank den Hollander Instituut voor theoretische natuurkunde Eurandom Rijksuniversiteit Groningen Technische Universiteit Eindhoven Nijenborgh 4, 9747 AG Groningen Postbus 513, 5600 MB Eindhoven [email protected] [email protected] Laudatio Laudatio for Michael Aizenman Eens per drie jaar reikt het Wiskundig Ge- Michael is the author of seventy-five research or ‘down’) or as particles (‘occupied’ or ‘emp- nootschap in opdracht van de Koninklijke Ne- papers in journals of mathematics, physics ty’). Their finite-volume conditional distribu- derlandse Academie van Wetenschappen de and mathematical physics. He has collaborat- tions (i.e., the probabilities of events inside a Brouwermedaille uit aan een internationaal ed with many co-authors on a broad range of finite volume given the state outside) are pre- toonaangevend onderzoeker. Hij wordt uit- topics. Much of his work is inspired by proba- scribed by a nearest-neighbor interaction that genodigd om een voordracht te geven op het bility theory and statistical physics, both clas- tends to ‘align spins’ or ‘glue together parti- Nederlands Mathematisch Congres, waar na sical and quantum. In his papers he typically cles’ and that contains the temperature as a afloop de laureaat de Brouwermedaille wordt ‘rides several horses at the same time’, in the parameter. At low temperature and in two uitgereikt. In 2002 werd de medaille toege- sense that cross-fertilization between differ- or more dimensions, there exists more than kend aan Michael Aizenman voor zijn bijdra- ent areas in physics and mathematics is at one infinite-volume probability measure hav- ge aan de mathematische fysica. -
A Life in Statistical Mechanics Part 1: from Chedar in Taceva to Yeshiva University in New York
Eur. Phys. J. H 42, 1–21 (2017) DOI: 10.1140/epjh/e2017-80006-9 THE EUROPEAN PHYSICAL JOURNAL H Oral history interview A life in statistical mechanics Part 1: From Chedar in Taceva to Yeshiva University in New York Joel L. Lebowitz1,a and Luisa Bonolis2,b 1 Departments of Mathematics and Physics, Rutgers, The State University, 110 Frelinghuysen Road, Piscataway, NJ 08854, USA 2 Max Planck Institute for the History of Science, Boltzmannstrasse 22, 14195 Berlin, Germany Received 10 February 2017 / Accepted 10 February 2017 Published online 4 April 2017 c The Author(s) 2017. This article is published with open access at Springerlink.com Abstract. This is the first part of an oral history interview on the life- long involvement of Joel Lebowitz in the development of statistical mechanics. Here the covered topics include the formative years, which overlapped the tragic period of Nazi power and World War II in Eu- rope, the emigration to the United States in 1946 and the schooling there. It also includes the beginnings and early scientific works with Peter Bergmann, Oliver Penrose and many others. The second part will appear in a forthcoming issue of Eur. Phys. J. H. 1 From war ravaged Europe to New York L. B. Let’s start from the very beginning. Where were you born? J. L. I was born in Taceva, a small town in the Carpathian mountains, in an area which was at that time part of Czechoslovakia, on the border of Romania and about a hundred kilometers from Poland. That was in 1930, and the town then had a population of about ten thousand people, a small town, but fairly advanced. -
09W5055 Statistical Mechanics on Random Structures
09w5055 Statistical Mechanics on Random Structures Anton Bovier (Rheinische Friedrich-Wilhelms-Universitat¨ Bonn), Pierluigi Contucci (University of Bologna), Frank den Hollander (University of Leiden and EURANDOM), Cristian Giardina` (TU Eindhoven and EURANDOM). 15 November - 20 November 2009 1 Overview of the Field The theme of the workshop has been equilibrium and non-equilibrium statistical mechanics in a random spatial setting. Put differently, the question was what happens when the world of interacting particle systems is put together with the world of disordered media. This area of research is lively and thriving, with a constant flow of new ideas and exciting developments, in the best of the tradition of mathematical physics. Spin glasses were at the core of the program, but in a broad sense. Spin glass theory has found ap- plications in a wide range of areas, including information theory, coding theory, algorithmics, complexity, random networks, population genetics, epidemiology and finance. This opens up many new challenges to mathematics. 2 Recent Developments and Open Problems The workshop brought together researchers whose interest lies at the intersection of disordered statistical mechanics and random graph theory, with a clear emphasis on applications. The multidisciplinary nature of the proposed topics has attracted research groups with different backgrounds and thus provided exchange of ideas with cross-fertilisation. As an example, we mention two problems on which we focused during the workshop. The first problem has its origin in the many fundamental issues that are still open in the theory of spin glasses. Even tough today we have a rigorous proof, in the context of mean-field models, of the solution for the free energy first proposed by G. -
A Mathematical Physicist's Perspective on Statistical Mechanics
A mathematical physicist’s perspective on Statistical Mechanics Michael Aizenman Princeton University André Aisenstadt Lecture (I) CRM, Montreal Sept. 24, 2018 1 /14 Statistical mechanics explains and quantifies the process by which structure emerges from chaos. Its genesis is in Boltzmann’s explanation of thermodynamical behavior and in particular of the concept of entropy. The statistic mechanical perspective was instrumental for Planck’s theory of the light quantization and Einstein’s calculation of the Avogadro number. More recent developments include links between the physics of critical phenomena and the mathematics of conformally invariant random structures, stochastic integrability, and representation theory. The talk will focus on examples of observations and conjectures which turned out to point in fruitful directions. 2 /14 Statistical Mechanics: laws emerging from chaos Laws expressed in equations F = ma, E = mc2, PV = nRT . A bird of a seemingly different feather: ∆S ≥ 0 . Q: what is entropy? L. Boltzmann: Thermodynamics emerges from Statistical Mechanics! Stat-Mech starts with a quantification of chaos: S = kB log W StatMech perspective was embraced and used for further developments by: M. Planck ) quantum theory of light (surmised from the black body radiation) A. Einstein ) Avogadro number from Brownian motion (exp. Perrin) −itH R. Feynman ) path representation of quantum dynamics: Ψt = e Ψ0 J. Wheeler: “There is no law except the law that there is no law.” Paraphrased: all physics laws are emergent features. 3 /14 Statistical Mechanics: laws emerging from chaos Laws expressed in equations F = ma, E = mc2, PV = nRT . A bird of a seemingly different feather: ∆S ≥ 0 . Q: what is entropy? L. -
Math 550-700 Applied Probability and Statistics, Summer 2019
Math 550-700 Applied Probability and Statistics, Summer 2019 MTWTh, 9:00am to 11:45am, synchronous online (via Zoom) In Person, June 10th through June 13th, in Ross 3275 Student Hours: MTWTh 1:00pm to 5:00pm in Ross 2250D Instructor: Neil Hatfield Email: [email protected] Office Number: Ross 2250D Course Website: Canvas https://unco.instructure.com All Course Materials, homework assignments, and tests will be posted to the course website. Catalog Description: Methods related to descriptive and inferential statistics and the concept of probability are investigated in depth. Course Description: This course addresses the statistical processes of formulating questions, collecting and analyzing data, and interpreting results. Methods related to descriptive and inferential statistics and the concept of probability are investigated in depth. This course will act as a first course in the concepts and methods of statistics, with emphasis on data visualizations, the distribution conception, descriptive statistics, and statistical inference. Inference topics include parametric and non-parametric point and interval estimation, hypothesis testing, and measures of effect size. Prerequisites and Placement: Graduates only. Textbook and Reading Materials: • Required Textbook: None. • Required Readings: There will be several required readings; PDFs of these readings will be made available to you at no cost through the course website. These readings fall under Educational Fair Use guidelines. • Recommended Readings: A list of additional readings, sometimes including PDFS, will be posted to the course website. These readings will be optional (strongly recommended) and are meant to help enrich your experience in the course. These readings fall under Educational Fair Use guidelines. If you have a suggestion for the list, please share the details with the instructor. -
On Spin Systems with Quenched Randomness: Classical and Quantum
On Spin Systems with Quenched Randomness: Classical and Quantum Rafael L. Greenblatt(a) ∗ Michael Aizenman(b) y Joel L. Lebowitz(c)∗ (a) Department of Physics and Astronomy Rutgers University, Piscataway NJ 08854-8019, USA (b) Departments of Physics and Mathematics Princeton University, Princeton NJ 08544, USA (a) Departments of Mathematics and Physics Rutgers University, Piscataway NJ 08854-8019, USA December 5, 2009 Dedicated to Nihat Berker on the occasion of his 60th birthday Abstract The rounding of first order phase transitions by quenched randomness is stated in a form which is applicable to both classical and quantum systems: The free energy, as well as the ground state energy, of a spin system on a d-dimensional lattice is continuously differentiable with respect to any parameter in the Hamiltonian to which some randomness has been added when d ≤ 2. This implies absence of jumps in the associated order parameter, e.g., the magnetization in case of a random magnetic field. A similar result applies in cases of continuous symmetry breaking for d ≤ 4. Some questions concerning the behavior of related order parameters in such random systems are discussed. 1 Introduction The effect of quenched randomness on the equilibrium and transport properties of macroscopic systems is a subject of great theoretical and practical interest which is close to Nihat’s heart. He and his collaborators [1, 2, 3] made important contributions to the study of the changes brought about by such randomness in phase transitions occurring in the pure (non-random) system. These effects can be profound in low dimensions. Their understanding evolved in a somewhat interesting way. -
A Tutorial on Palm Distributions for Spatial Point Processes Jean-François Coeurjolly, Jesper Møller, Rasmus Waagepetersen
A tutorial on Palm distributions for spatial point processes Jean-François Coeurjolly, Jesper Møller, Rasmus Waagepetersen To cite this version: Jean-François Coeurjolly, Jesper Møller, Rasmus Waagepetersen. A tutorial on Palm distribu- tions for spatial point processes. International Statistical Review, Wiley, 2017, 83 (5), pp.404-420 10.1111/insr.12205. hal-01241277v3 HAL Id: hal-01241277 https://hal.archives-ouvertes.fr/hal-01241277v3 Submitted on 17 Jun 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. A tutorial on Palm distributions for spatial point processes Jean-Fran¸cois Coeurjolly1, Jesper Møller2 and Rasmus Waagepetersen2 1Laboratory Jean Kuntzmann, Statistics Department, Grenoble Alpes University, 51 Rue des Math´ematiques, Campus de Saint Martin d’H`eres, BP 53 - 38041 Grenoble cedex 09, France, email: [email protected]. 1Department of Mathematical Sciences, Aalborg University, Fredrik Bajersvej 7E, DK-9220 Aalborg, email: [email protected], [email protected], June 17, 2016 Abstract This tutorial provides an introduction to Palm distributions for spatial point processes. Initially, in the context of finite point pro- cesses, we give an explicit definition of Palm distributions in terms of their density functions. -
Applied Probability and Stochastic Processes
EECE 7204 - Applied Probability and Stochastic Processes Northeastern University Department of Electrical and Computer Engineering Fall 2018 Instructor: Prof. Pau Closas Place: West Village H 108 Email: [email protected] Time: Mon/Wed Office: 529 ISEC 2:50pm - 4:30pm Sept. 5 { Dec. 5 TA: Berkan Kadıo˘glu Email: [email protected] Office Hours Prof. Closas: After class on Monday/Wednesday (4:30pm to 5:30pm), or by appointment. If emails are sent, please always include [EECE7204] in subject line for filtering. Office Hours TA Kadıo˘glu: Wednesday (9:30am to 11:30am) in 562-A5 ISEC. If emails are sent, please always include [EECE7204] in subject line for filtering. Prerequisites: Knowledge of signals, linear systems and transformations; sets, algebra, calculus. Course Catalog Description: Covers fundamentals of probability and stochastic processes with appli- cations to estimation and queuing theory. Includes basic laws of probability, conditioning, and Bayes rule. Topics include random variables and their functions; PDF, PMF, and CDF notions; statistical averages; moments and characteristic functions; multiple random variables; joint and conditional PDF and PMF; multiple functions of random variables; correlation and covariance; mean squared estimation of random variables; Markov, Chebychev, and Chernov inequalities; various notions of convergence of random variable sequences; laws of large numbers; central limit theorem; and large deviation theory. As time permits, dis- cusses basic notions of estimation and properties of estimators, unbiased and minimum variance estimation, CRLB, sufficient statistics, consistency of estimators, basic notions of discrete and continuous-time random processes, mean and autocorrelation function, WSS and cyclo-stationary processes, ergodicity of random processes, and other topics. -
Stochastic Modelling and Applied Probability
Stochastic Mechanics Stochastic Modelling Random Media Signal Processing and Applied Probability and Image Synthesis (Formerly: Mathematical Economics and Finance Applications of Mathematics) Stochastic Optimization Stochastic Control Stochastic Models in Life Sciences 33 Edited by B. Rozovski˘ı P.W. Glynn Advisory Board M. Hairer I. Karatzas F.P. Kelly A. Kyprianou Y. Le Jan B. Øksendal G. Papanicolaou E. Pardoux E. Perkins H.M. Soner For further volumes: http://www.springer.com/series/602 Paul Embrechts Claudia Klüppelberg Thomas Mikosch Modelling Extremal Events for Insurance and Finance Paul Embrechts Thomas Mikosch Department of Mathematics Department of Mathematics ETH Zurich University of Copenhagen Zurich, Switzerland Copenhagen, Denmark Claudia Klüppelberg Zentrum Mathematik Technische Universität München Garching, Germany Managing Editors Boris Rozovski˘ı Peter W. Glynn Division of Applied Mathematics Institute of Computational Brown University and Mathematical Engineering Providence, RI, USA Stanford University Stanford, CA, USA ISSN 0172-4568 Stochastic Modelling and Applied Probability ISBN 978-3-642-08242-9 ISBN 978-3-642-33483-2 (eBook) DOI 10.1007/978-3-642-33483-2 Springer Heidelberg New York Dordrecht London © Springer-Verlag Berlin Heidelberg 1997, 4th corrected printing and 9th printing 2012 Softcover reprint of the hardcover 1st edition 1997 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.