Spring 2011 Special Topics Course Descriptions

NOTE: for descriptions of standard graduate computer science courses, see Graduate Course Descriptions.

G22.3033-001 Abstract Interpretation

The fast-growing volume and complexity of software embedded in safety, mission, and business-critical systems is driven by demands for increased functionality while being asked to function at unprecedented levels of reliability, safety, security, and scalability. In this context, automatic software analysis and formal verification to prove the absence of errors becomes a cost-effective complement to empirical validation and testing methods to detect the presence of bugs and flaws in computer systems. It is a basic requisite in the curriculum of advanced software engineers and researchers.

Abstract Interpretation is a theory of approximation of mathematical structures, in particular those involved in the semantic models of computer systems. Abstract interpretation has been be applied to the systematic construction of methods and effective algorithms to approximate undecidable or very complex problems in computer science such that the semantics, the proof, the static analysis, the verification, the safety and the security of software or hardware computer systems. In particular, abstract interpretation-based static analysis, which automatically infers dynamic properties of computer systems, has proven to be effective, precise, and scalable, and has been very successful these last years to automatically verify complex properties of real-time, safety critical, embedded systems.

The course is an introduction to abstract interpretation with applications to static analysis (the automatic, compile-time determination of run-time properties of programs) and software verification (conformance to a specification).

See the course homepage for more information.

G22.3033-002 Financial Computing

This course is intended to introduce the students to the basic concepts of Computational Finance and explore various relations between Computer Science and Finance. In particular, the course will introduce both theoretical and practical aspects of finance with an emphasis on the relation between real-life applications and these concepts. We will cover various issues like high-frequency market simulators, framework for performing statistical simulations, we will discuss and model various financial instruments. Strong emphasis will be put on efficiency and proper design. As such, Object Oriented concepts will be discussed and put to use in real life applications.

Prerequisites: Fundamental Algorithms, Programming Languages, background in calculus and linear algebra.

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G22.3033-003 *Cancelled*

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G22.3033-004 Data Mining: Concepts and Techniques

Data mining is the application of machine learning techniques for automatic analysis and extraction of useful knowledge from data repositories. The course will introduce concepts and techniques of data mining and data warehousing, including unsupervised and supervised learning, classification, clustering , association rules, decision trees, genetic algorithms, knowledge discovery in databases, OLAP (On-line Analytical Processing), the data warehouse, neural networks, statistical techniques, and rule-based systems.

PREREQUISITES: G22.1170 Fundamental Algorithms and a course on databases

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G22.3033-005 Special Topics in Algorithms

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G22.3033-006 Computational Systems Biology

The course focuses on statistically determining the relations between genotypes and phenotypes. We now know that human genome contains millions of SNPs (single-nucleotide polymorphisms), and thousands more variations in the number of copies of large and small segments of the genome (CNVs: copy number variation), which may either directly cause changes in phenotype (e.g., TAS) or which tag nearby mutations containing the key differences that influence individual variation (e.g., TASPs) and susceptibility to disease.

GWA (Genome-Wide Association) studies allow one to sample large number of SNPs from many patients, thus, capturing variation uniformly across the genome. Recently, there has been an enormous interest in such studies as they have succeeded in identifying risk and protective factors for asthma, cancer, diabetes, heart disease, mental illness and other human differences. For instance, in 2005, it was learned through a small scale GWAS that age-related macular degeneration is associated with variation in the gene for complement factor H, which produces a protein that regulates inflammation. One expects the GWAS to play a significant role in drug discovery and personalized medicine, and will be important in the modern models of health-care (e.g., evidence-based medicine). For instance, it was found that the genetic variants have different responses to various anti-hepatitis C virus treatments: for genotype 1 hepatitis C, treated with Pegasys combined with ribavirin, genetic polymorphisms near the human IL28B gene are associated strongly with responses to the treatment. One expects to find and catalogue many such facts.

This course will focus on the algorithmic, statistical and genetic aspects of this problem. Thus, we will develop specialized methods for Machine Learning (supervised and unsupervised), Classification, Model Selection, Multiple Hypotheses Testing and Experiment Design (pooling and group-testing).

Required Textbooks:

Applied Statistical Genetics with R: For Population-based Association Studies (Use R);
Author: Andrea S. Foulkes
Publisher/Edition (Yr. or No.): Springer; 1 edition (April 17, 2009).

Recommended textbooks:

Mathematical and Statistical Methods for Genetic Analysis;
Author: Kenneth Lange;
Publisher/Edition (Yr. or No.): Springer; 2nd edition (June 3, 2003).

Statistical Genetics of Quantitative Traits: Linkage, Maps and QTL
Authors: Rongling Wu, Changxing Ma, George Casella;
Publisher/Edition (Yr. or No.): Springer; 1 edition (July 31, 2007).

Essentials of Genomic and Personalized Medicine;
Authors: Geoffrey S. Ginsburg and Huntington Ph.D Willard,
Publisher/Edition (Yr. or No.): Academic Press; 1 edition (October 8, 2009).

Genetics: Analysis of Genes and Genomes (Hardcover)
Authors: Daniel Hartl and Elizabeth Jones;
Publisher/Edition (Yr. or No.): Jones & Bartlett Publishers; 7 edition (August 1, 2008).

See the course homepage for more information.

G22.3033-007 Web Development with Ruby on Rails

This course begins with an in-depth examination of the Ruby language and moves on to web development within the Ruby on Rails framework. An emphasis is placed on understanding the particular features of the Ruby language, how the language compares to others like Java and Python, and how it facilitates the creation of frameworks such as Ruby on Rails. This course is recommended for students with a strong interest in programming languages, web development frameworks, and software engineering. No experience with Ruby or Ruby on Rails is assumed.

See the course homepage for more information.

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