AUS Regional Students Conference on Mathematics RSCM

Overview
First AUS Regional Students' Conference on Mathematics
March 1, 2014

Organized by the Department of Mathematics and Statistics
College of Arts and Sciences
American University of Sharjah

The primary objective of this conference is to bring together undergraduate and graduate students from the UAE and neighboring countries to a forum in which they can exchange ideas in different branches of mathematics and communicate recent developments in mathematical research and education.

The proposed technical program of the conference will include contributed talks by students and two keynote lectures by established mathematicians. There will also be panel discussions on applying for graduate school and on employment opportunities in the UAE led by recent mathematics graduates.

Topics to be covered include, but are not limited to:

• Algebra
• Analysis
• Applied Mathematics
• Differential Equations
• Discrete Mathematics
• Financial Mathematics
• Mathematics Education
• Number Theory
• Numerical Analysis
• Probability Theory
• Statistics and its Applications
• Stochastic Differential Equations
• Topology and Geometry

Contributed talks by undergraduate and graduate students are expected to be research or expository work in any mathematically intensive topic at a level that is appropriate for their educational stage.

Participants are invited to submit extended abstracts or short papers that will be published in the conference proceedings.

Important Deadlines

Registration: January 23, 2014
Abstract submission: January 30, 2014
Late registration: February 7, 2014
Proceedings paper submission: February 7, 2014

Maps 

Here's how to find us:

• AUS Google Map ( 25.3097° N, 55.4906° E ) Link
• AUS Campus Map PDF
  
• AUS Directions Map PDF

Registration

Important Dates

Registration deadline: January 23, 2014
Abstract submission deadline: January 30, 2014
Late registration deadline: February 7, 2014
Proceedings paper submission deadline: February 7, 2014

UAE students registration fee: $30
International students registration fee: $60
Late registration fee (by February 7, 2014): $90

The registration fee covers lunch and refreshments.

To register for the First AUS Regional Students Conference on Mathematics please email a completed registration form to [email protected].

To download the payment registration form click here.

Keynote Lecturers
The keynote lectures take place in Lecture Hall B in the AUS Main Building.

Dr. Federico Camia

Visiting Associate Professor of Mathematics,
NYU Abu Dhabi,
Abu Dhabi, UAE

Associate Professor,
Department of Mathematics, VU University Amsterdam, Netherlands

Biography: Dr. Federico Camia studied physics at the University of Bologna, the Ecole Polytechnique near Paris, and New York University. He obtained his PhD from NYU, where he was also a research assistant at the Courant Institute of Mathematical Sciences. His main research interests lie at the interface between probability theory and statistical physics, particularly in the areas of equilibrium statistical mechanics, phase transitions and spatial stochastic models. He was awarded the Marie Curie Research Fellowship and grants from the US National Science Foundation and the Dutch Organization for Scientific Research, and has co-organized seminars and an international workshop on probability and stochastic systems. His work has been published in numerous international physics and mathematics journals. Camia holds a PhD in physics from NYU. He received his MS at NYU, and his undergraduate degree with honors from the University of Bologna, Italy.

Title: Random Fractals

Abstract: Fractal-like
structures are common in nature. They have a property called self-similarity,
which means that each potion looks like the whole. The most famous mathematical
fractals, such as the Cantor, Julia and Mandelbrot sets or the Sierpinski
carpet, are typically produced by a deterministic process and contain
identical, scaled-down copies of themselves. On the contrary, natural
fractal-like objects usually look random and are only statistically self-similar,
in the sense that each portion is similar in shape but not identical to a
scaled version of the whole. In this talk I will explore how combining
self-similarity and randomness produces extremely interesting models whose
analysis requires a mixture of techniques from different areas of mathematics.
Such random fractals have many applications to various fields of mathematics,
the natural sciences and economics.

Dr. Dmitry Efimov

Visiting Assistant Professor,
Department of Mathematics and Statistics,
American University of Sharjah,
Sharjah, UAE

Biography: Dmitry Efimov graduated with honors
from the Faculty of Mechanics and Mathematics at Moscow State University (MSU) in
June 2004. He received his PhD in Mathematics from MSU in 2008. In February
2008, he passed the competitive selection for the position of Assistant
Professor at the Mathematical Analysis Department at MSU, and has occupied the
position since then. He is has been working as a Visiting Assistant Professor
in the Department of Mathematics and Statistics at American University of Sharjah
since September 2012.

Efimov's research area is in applied machine learning and data
mining. He is interested in automatic feature engineering and feature selection
methods, metrical data mining algorithms, boosting approaches. Efimov has obtained several interesting
results, such as a novel functional ensembling algorithm for binary
classification problems and a likelihood feature engineering algorithm. He is a
winner of several predictive modelling competitions (KDD Cup'2013: Author-Paper
Identification Challenge; Amazon.com: Employee Access Challenge; Predicting the
Strength of Social Ties). Efimov
has been ranked among the top 10 data mining researchers in the Kaggle world
ranking (https://www.kaggle.com/users).

He worked as a predictive analytics
consultant for Etihad Airways.

Title: Applied Machine Learning: basics and case studies.

Abstract: Databases
today keep increasing, and recent problems require the exploration of  terabytes of data. There is no doubt that they contain a lot
of hidden information of strategic importance. But when there are so many grains of sand, how do we draw meaningful
conclusions about the desert?

The
most relevant answer is machine learning and data mining, which are being used
in a huge
variety of problems: from pattern recognition in
engineering to connection recovering in social networks. The potential returns are enormous.
Innovative organizations worldwide are already using data mining to discover future higher-value customers,
to minimize losses due to error or fraud, and to plan product offerings to increase sales.

Data
mining is a process that uses a variety of mathematical approaches to find
patterns and
relationships in data, and machine learning is a set of
algorithms that can be used to make valid
predictions.

In my
lecture I will introduce basic concepts of machine learning and give several
practical examples where mathematical
methods help to extract valuable information from huge amount of data.

Conference Proceedings
Presenters may submit their papers or extended abstracts for inclusion in the conference proceedings.

Papers must be between two and six pages in length. Camera-ready manuscripts should be submitted by February 7, 2014. However, earlier submission is encouraged to enable sufficient time for editing to be discussed with the authors.

Paper Format and Templates

In the following you will find guidelines
and templates for submitting your paper to the RSCM'14 proceedings
electronically at [email protected]

1. If the paper is typeset using Latex,
please download the template package Latex Users.
In the package, you will find the following files:

• template latex RSCM.tex
• template latex RSCM.pdf
• dir.eps

2.  If your paper is written using
Microsoft Word, please download the  template packages Word Users. In the package, you will find the following files:

• template word RSCM.docx
• template word RSCM.pdf

Accommodation