MEng Thesis Research Opportunities

The following CSAIL Research Projects have expressed interest in potentially sponsoring a student working on a MEng Thesis. Please contact the researchers involved in these projects directly through their web sites.

Note: MEng thesis research opportunities are open only to current MIT MEng Students.

Applying Evolutionary Algorithms to Analog Circuit Design Automation or Parallel Programs:

In Spring 2007, the EVO-DesignOpt group will have paid UAP and UROP opportunities for students interested in genetic algorithms and how they are used to automate analog circuit design or map parallel algorithms to processor clusters.

Genetic Algorithm for Mapping Parallel Matlab Programs Project (NEW!) Currently, when a Matlab program is mapped across multiple processors, the configuration (bandwidth, routing) of the processor cluster is not considered. The goal of this project is to develop an algorithm that can find efficient mappings that *do* consider the processor topology. We are pursuing an artificial intelligence strategy: we will use a genetic algorithm to "evolve" mappings.

Relevant Experience: 6.034 and/or 6.846 and/or 6.046

Analog circuit automation Project: We are developing more accurate models for analog circuit sizing techniques. We are developing a scalable multi-objective genetic algorithm for analog sizing. Projects will involve teaming with a graduate students.

Required: 6.002, 6.003, 6.301/6.302, 6.034;
Desired: 6.775, 6.867, 6.253, 6.225 or equivalent

Send questions or application which includes CV via email to EVO-DesignOpt@csail.mit.edu. Please make the subject header of the mail "Student Research".

Finding and Understanding Chemical Structures in Documents

Professor Randall Davis

Indexing documents by keywords is a familiar and powerful technology in today's web-driven world. But what if the information you’re seeking is in a graphic, and is never described in words? Put slightly differently, full-text indexing has proven to be a powerful foundation for information retrieval; what if we could read and understand (and then index the information in) diagrams as well? Read More (PDF)

For more information, contact Professor Randall Davis (davis@csail.mit.edu).

Fresh Breeze: A Novel Multiprocessor Chip

Computation Structures Group, CSAIL
Jack B. Dennis, Professor Emeritus

Computer architects have found that putting several processor cores on the same chip is a better way of using silicon area than attempting to achieve greater performance by adding further complexity to a single processor. Moreover, the increased performance is obtained for significantly less energy consumption. However, the result so far is chips that are very difficult to program to realize their performance potential.

The Fresh Breeze Project is attacking this programmability problem using concepts from functional programming, principles of modular software construction, and global shared address spaces. Our approach is to incorporate three ideas that are significant departures from conventional thinking about multiprocessor architecture: Simultaneous multithreading promises performance advantages relative to contemporary superscalar designs through higher utilization of functional units. By implementing a shared global address space, the cost of implementing fine-grain cooperation of multiple processors can be greatly reduced. Also, the conventional distinction between "memory" and the file system can be abolished, simplifying programming, as has been demonstrated in Multics. A more radical departure from convention is the implementation of a cycle-free heap of information "chunks" that are created, used, and released, but never modified once created. Memory management will be done by efficient hardware mechanisms.

More information may be found at http://www.csg.csail.mit.edu/Users/dennis.

Topics suitable for Master of Engineering Projects include: performance analysis of specific applications on a Fresh Breeze system; memory management studies; design of an external shared memory system for a system built of Fresh Breeze chips; failure recovery in a Fresh Breeze system; implementation of load balancing; transaction processing applications; FPGA prototype implementation; compiler development.

For more information, contact Prof. Jack Dennis (dennis@csail.mit.edu).

Haystack Project

The Haystack project aims to develop new tools to help people organize, manipulate, and retrieve all the information they encounter on a day to day basis. A major focus is personalization, adapting over time to the specific information needs and preferences of individual users.

The research combines ideas from databases, human-computer interaction, and machine learning. We explore database tools to build a data representation rich and flexible enough to record all the information any individual consider important, and in particular make heavy use of Semantic Web technology for manipulating richly structured information on the world wide web. We apply ideas from human-computer interaction to develop interfaces that can present that rich data model and let the user work with it. And we apply ideas from machine learning to help the system observe and adapt to the preferences and perceptions of its user. We've built a number of tools including the Haystack "universal desktop client" for managing any kind of information you care about, an Ajax tool called Exhibit for creating fancy interactive web pages without any programming, and the "Jourknow" system for managing those scraps of information that don't seem to fit anywhere. You can find out more about these and other projects at the Haystack project page at http://haystack.csail.mit.edu .

We have openings for self-motivated MEngs who are interested in extending the capabilities of the system at all layers---the database back-end, the machine-learning core, or the user interface. Initiative is key as MEngs are given substantial flexibility to choose their own project. You will join a team of 6 graduate students and 5 undergraduates already working on the project. .

Contact:
Applicants should email Prof. David Karger (karger@csail.mit.edu)

MIT Center for Collective Intelligence

The Center for Collective Intelligence (http://cci.mit.edu) is focused on answering the question, How can people and computers be connected so that- collectively-they act more intelligently than any person, group, or computer has ever done before? The Center includes faculty from around MIT, including CSAIL, Media Lab, and Sloan. We expect to have opportunities for summer jobs, MEng, UROP, or other student work on a project to combine human and machine intelligence in flexible new ways to make accurate predictions about future events such as product sales, political events, and outcomes of medical treatments. Initial work will include developing a flexible web server and user interfaces for on-line markets of various types.

Contact: Prof. Thomas Malone (malone@mit.edu), Prof. Randall Davis (davis@csail.mit.edu), or Prof. Peter Szolovits (psz@mit.edu).

Network Optimization with Network Coding and Genetic Algorithms

This project has clear practical relevance: we plan to develop practical network coding algorithms that advantageously tradeoff throughput efficiency with memory demands, decoding effort and other commonly present real-world network constraints. It will be of interest to students who are taking 6.263 or 6.441, 6.829, and/or who have studied optimization (e.g. 6.251,6.252, 6.253, 6.255,15.053). It also is attractive to students to students who have an interest in genetic algorithms and Artificial Intelligence.

Terms: Fall and/or Winter 2007
Scope: M.Eng, 6.UAT, Senior of high standing or relevant experience
Software: Matlab or C/C++
Contact: Una-May O'Reilly, unamay@csail.mit.edu
Research Group: EVO-DesignOpt http://groups.csail.mit.edu/EVO-DesignOpt/index.htm

Parallelization of Matrix Operations via Genetic Algorithms for High Performance Embedded Computing:

Analyzing small world networks is but one of many interesting real-world problems that computationally translate to matrix operations on very large but sparse matrices. This project is attractive to students who like to understand how the big picture boils down to important computational issues. To date, sparse matrix operation mapping to a parallel high performance computer cluster is not distinguished from dense matrix mapping. This results in large inefficiencies due to the cost of null data movements on the cluster. In concert with Lincoln Labs, we have developed a fine grained cluster model in tandem with 2 genetic algorithms that is just starting to indicate that efficient sparse matrix mappings can be derived. We are interested in investigating, with a student, if mapping patterns or mapping heuristics can be evolutionarily discovered to be reused or exploited as new starting points for finding better mappings. We will look at different "classes" of sparse matrices derived from different real world applications and see if evolution can discover appropriate ways to map them.

Terms: Fall 2007
Scope: M.Eng, 6.UAT, Senior of high standing or relevant experience
Relevant Experience: 6.034 and/or 6.846 and/or 6.046, 6.338/18.337
Software: MATLAB
Contact: Una-May O'Reilly, unamay@csail.mit.edu
Research Group: http://groups.csail.mit.edu/EVO-DesignOpt/index.htm EVO-DesignOpt

The Program Analysis Group

The Program Analysis Group (PAG) has a number of projects at http://pag.csail.mit.edu/pag/projects.html. (Note: This URL is only accessible from the mit.edu domain.)

PAG's research aims to make software more reliable, more secure, and easier (and more fun!) to produce. Our work includes software engineering, static and dynamic program analysis, testing, security, type theory, programming language design, and verification. If you like building software, you will enjoy this research, which is about making programming less error-prone, less tedious, and more fun. If you ever have trouble building software, you will find the research results helpful, and you may be inspired to come up with new projects.

PAG does the best MEng research in CSAIL! An MEng thesis from PAG has won the Charles and Jennifer Johnson Thesis Award (for outstanding computer science M.Eng. thesis) in 4 of the last 6 years: 2002, 2003, 2006, and 2007.

Research in Genetic Algorithms

Genetic Algorithms are bio-inspired algorithms that search and optimize with an algorithmic version of Darwinian evolution. They are well suited for problems where there there is no derivative, convex optimization scales inefficiently, multiple objectives need to be satisfied or where machine learning algorithms or conventional optimization methods need a partner. We frequently tackle full scale real-world problems and address the research issues that arise in solving the with a genetic algorithm - typically minimizing computational cost and identifying best-possible solutions. The software development is modest but a student typical spends a lot of time "experimenting" with the algorithm to understand its behavior in a "genetic" sense and modify it for improvement using evolution-based concepts.

Terms: Fall and or Winter 2007
Scope: M.Eng, Junior or Senior of high standing or relevant experience, 6.UAT
Contact: Una-May O'Reilly, unamay@csail.mit.edu
Research Group: EVO-DesignOpt http://groups.csail.mit.edu/EVO-DesignOpt/index.htm

Secure Group Communication in Dynamic Mission-Critical Environments

We are looking for a research assistant to contribute to an ongoing research project in secure group communication in dynamic mission-critical environments. The project involves studying and experimenting with available solutions, as well as designing and prototyping new solutions (Java, C, and C++), which are driven by specific applications and environment characteristics.

A qualified student would have experience in network programming, practical network security, distributed systems, and cryptography.

A significant portion of research will be done on-site at MIT Lincoln Laboratory (www.ll.mit.edu), located in Lexington, MA. U.S. citizenship is required for this position.

Note: this position is now open.

Contact: Dr. Roger Khazan. (rkh@mit.edu).

User Interface Design Group

The User Interface Design Group is looking for students interested in designing, building, and evaluating novel user interfaces for programming, security, and the Web. Tired of tedious, unpredictable, or painful UI? Come help us fix it.

For more about UID Group projects, see http://uid.csail.mit.edu.

Contact: Rob Miller (32G-716), (rcm@mit.edu).