Thomas S. Briggs

Dept. of Computer Science Princeton University 35 Olden St. Princeton, NJ 08544

Phone: (609) 986-8867 Email: tbriggs@cs.princeton.edu

Education

Sept. 2002 – present

Princeton University; Princeton, NJ.

• M.A. expected in Jan. 2005, Department of Computer Science
• Worked for Prof. Olga Troyanskaya designing and implementing machine-learning techniques
  for organizing / classifying high-throughput genetic interaction data.

Sept. 1998 – May 2002

Amherst College; Amherst, MA.

• Graduated magna cum laude, B.A. in Computer Science.
• GPA: 12 on a 14-point scale, corresponding with an A- average.
• Undergraduate thesis: “Automated Musical Transcription with Hidden Markov Models”
• Awarded associate membership in Sigma Xi

Experience

Summer 2004. Princeton University, Functional Genomics Group.

Research assistant to Prof. Olga Troyanskaya. Researched and implemented

a machine learning-based system to automatically determine parameters for

MAGIC, a Bayesian system for integrating high-throughput data sources.

Summer 2003. Princeton University, Sound Lab

Research assistant to Prof. Perry Cook. Conducted literature survey in contemporary

computer audition.

Summer 2002. Talent Identification Program. Duke University, Durham, NC.

Teaching assistant for the course “Introduction to Artificial Intelligence,” for gifted
high-school students. Collaborated with and supported teacher; led supplementary

discussion groups among students.

Summer 2001. Neural Systems Lab, University of Maryland at College Park.

Summer intern. Provided computer support for analysis of magnetoencephalographic

(MEG) pictures of a functioning brain.

Summer 2000. MIT Haystack Observatory, Atmospheric Sciences Group; Westford, MA.

Summer intern. Built a Web-based front end to the MADRIGAL database of upper-atmospheric

data, converted back-end from flat-file to relational database (SQL) format.

Technical Skills

Languages

C/C++ (including STL), Java, Perl, Matlab, Standard ML, HTML. Some SQL, Prolog.

Operating Systems

UNIX / Linux / Solaris, Windows.

Courses

In computer science: data structures, algorithms, theory, artificial intelligence,

computer graphics, computer sound/music, cryptography, operating systems design,

compilers, networking and distributed systems (at Amherst and Princeton).

In mathematics: statistics, calculus, linear algebra, discrete mathematics (incl.

combinatorics, basic probability, graph theory)

Projects and Teaching Experience

• Project in analysis of large-scale gene expression data using machine learning
  techniques (at Princeton)
• Project in analysis of neurological data (at UMD - College Park)
• Project in application of AI techniques to audio processing (undergrad thesis)
• Project in networking; Web-enabled database connectivity (at MIT Haystack)
• Teaching experience at Princeton (teaching assistant for CS 423: Information Security,
  under Prof. Edward Felten)
• Teaching experience with high-schoolers in T.I.P. summer program

References available upon request.