Faculty Research Interests

Yali Amit

Computer vision, image analysis and speech recognition: Object detection, recognition and model registration algorithms in digital images and acoustic data using hierarchies of templates. Applications to optical character recognition, zip code reading, face detection and recognition, automatic anatomy identification in medical images, detection and recognition of acoustic signals. Computational efficiency is emphasized. Statistical modeling and analysis of the data for understanding the performance of the algorithms.

Parallel and biologically plausible neural architectures for implementing these algorithms involving interactions with research on biological visual and acoustic pattern recognition.

Laszlo Babai

I work in the fields of theoretical computer science and discrete mathematics; more specifically in computational complexity theory, algorithms, combinatorics, and finite groups, with an emphasis on the interactions between these fields. Asymptotic questions and probabilistic methods are common features in my work in each of these areas. The introduction of Las Vegas algorithms, interactive proofs, holographic proofs (proofs verifiable by spotchecks) are among the conceptual highlights. A recent example: methods of the complexity theories of Boolean circuits and branching programs have been brought to bear on the analysis of a popular random sampling technique in computational group theory.

Todd Dupont

My research deals with the analysis, evaluation and construction of numerical methods to approximate the solutions of partial differential equations (PDEs).

The question of how to make effective use of computers with multiple processing units is one that is being investigated in several ways. I have recently produced several schemes that involve decomposing the computational domain into subregions and organizing the computation so that the work on each of these subdomains can be done almost independently of the others. This work was for parabolic PDEs and I am studying its extension.

Including adaptivity in numerical methods can make them more robust and efficient. Most simulations of time dependent problems use adaptivity for the control of the time step, and substantial progress has been made by many people in understanding how to control the spatial mesh when approximating PDEs. I have worked on this for several years.

I am currently collaborating with physicists and mathematicians on questions related to instabilities and singularity development in the flow of fluids and psuedo fluids.

Pedro Felzenszwalb

My main research interests are in computer vision, geometric algorithms and AI.

Robby Findler

I work in programming languages. I'm interested in PDEs, contracts, and tools to help semantics engineers.

Ian Foster

In my research, I seek to develop tools and techniques that allow people to use high-performance computing technologies to do qualitatively new things. This involves investigations of parallel and distributed languages, algorithms, and communication; and also focused work on applications. I am particularly interested in using high-performance networking to incorporate remote compute and information resources into local computational environments.

John Goldsmith

I am interested in understanding the nature of symbolic representation, in both natural language and genomic sequences, through the development of software that induces structure from data.

In the area of natural language, the focus of my recent work has been the development of a program called Linguistica which induces the morphology (the word internal structure) of a language on the basis of a corpus from the language. We are currently working on languages as diverse as Somali and Swahili in addition to more familiar European languages. Our webpage is linguistica.uchicago.edu

Stuart Kurtz

I am interested in the theoretical exploration of the polynomial time degrees, especially focussing on degrees which consist of a single polynomial isomorphism type.

I am also interested in the study of randomness and its applications.

Gina-Anne Levow

My research concentrates on the use of intonation in spoken dialog and my interests range over natural language processing, spoken language systems, and human-computer interfaces.

My current work focuses on the effects of context on tone and intonation. This research develops a broader-context, articulatorily-motivated model of tone, utilizing a common framework across a range of language and tone typologies including Bantu languages, Chinese dialects, and English. Through unsupervised and weakly supervised machine learning, this work aims to automatically identify tone and pitch accent in natural speech. My work further aims to understand and exploit the synergistic interaction of discourse structure and spoken intonation. To this end, I have developed computational techniques that can automatically detect topic changes in monologue and dialogue as well as corrections in human-computer spoken interactions. The improved techniques for modeling and recognition of tone and intonation developed in this work will allow computational spoken language understanding systems to more fully exploit the information carried by pitch.

I also have continuing interests in information retrieval in text and speech across a range of languages, in domains from news to medicine.

Ketan Mulmuley

Current work: Developing an approach to P vs. NP and related problems through algebraic geometry and representation theory (Geometric complexity theory)

Please see papers at http://ramakrishnadas.cs.uchicago.edu

Michael O'Donnell

I am interested in all types of interaction between computation and logic: in software applications, in the foundations of computer science, and in the conceptual foundations of other fields.

I study models for the digital description and production of sound.

I am investigating minimal network infrastructure to support public key cryptography/signature, based on the "nym" idea of self-signed key records.

In the past, I designed and implemented the first lazy functional programming language, defined precisely by the rules of equational logic. I have also investigated computational semantics for nonclassical logics, leading to a new understanding of constructive logic as a logic of proofs that can be communicated accurately in spite of some discrepancies in the language.

John Reppy

My main area of research is in the design and implementation of advanced programming languages, including functional languages, object-oriented languages, and concurrent languages. My current research focus is on parallel language design and implementation for multicore architectures and real-time graphical applications.

L. Ridgway Scott

My current interests focus on bioinformatics, via the Digital Biology Projet, and the automatic generation of software to support scientific simulation, via the FEniCS project. The Digital Biology Project seeks to understand how protein systems function in a discrete fashion, especially in the presence of hydrophobic effects (which are very non-specific). FEniCS is a polymorhpic acronym for an international effort (www.fenics.org) that attempts to utilize mathematical structure inherent in scientific models to automate the generation of simulation software.

Janos Simon

My main research area is computational complexity -- estimating the amount of resources (such as memory, time, number of algebraic operations, or interprocess communication) that are needed to compute functions. One tries to get good upper bounds by exhibiting efficient algorithms and to develop mathematical methods to prove lower bounds. I am especially interested in lower bound techniques for parallel and for probabilistic models. I am also interested in dstributed computing, especially in fault tolerant distributed computations.

Robert Soare

My main research area is mathematical logic, especially the theory of recursive (i.e., computable) functions. I am studying the properties of recursively enumerable (r.e.) sets (those which can be generated by a computable procedure), particularly their algebraic structure, the degree of information they encode (Turing degree), their automorphisms, and their computational complexity properties. I am also working on the computable content of certain algebraic structures such as Boolean algebras and models of certain formal systems. Finally I am studying decision procedures for certain subclasses of the r.e. Turing degrees.

Rick Stevens

I am interested in the development of innovative tools and techniques that enable computational scientists to solve large-scale problems more effectively on the most advanced high-performance computers. Specifically, my research focuses on three principal areas: collaborative visualization environments, high-performance computer architectures, and performance modeling.

In the area of collaborative visualization, I am exploring the use of virtual reality in the visualization of scientific data and processes. My efforts include improving displays, recording, and playback of virtual reality experiences; developing new methods for tracking and control and close coupling with parallel supercomputers; and devising new ways of collaborating in virtual environments. Of particular interest to me is teleimmersion -- strategies for synthesizing networking and multimedia technologies to enhance the development of wide-area wide-area collaborative computational science.

In the area of high-performance computers, I am studying approaches to computing at the Petaflops Scale, focusing on analysis, modeling, and simulation tools for these ultra-high-performance computers. I am also particularly interested in algorithm and software for multithreaded computer architectures and for hierarchical processor and memory architectures.

In a related area, I am investigating analytic performance models that will help researchers understand the performance relationship between high-performance computer systems and scientific applications. My goal is to enable scientific simulations to achieve the very high performance potential of next-generation computer architectures with deep memory hierarchies.