Summer EE 42/43/100 students, please click here for the course website.
About Me
I am in my sixth year of graduate school here at U.C. Berkeley. I'm currently working on my Ph.D. in electrical engineering. My research has me applying convex optimization and statistical estimation techniques to news articles. My advisor in these efforts is Prof. Laurent El Ghaoui. I have a B.S. in electrical engineering from the University of Virginia from the spring of 2005, where I completed a design thesis on blind modulation detection for digital communication signals.You can follow my public Twitter account at http://www.twitter.com/bgawalt.
You can email me at gawalt@eecs.berkeley.edu.
Publications & Conferences
- Luke Miratrix, Jinzhu Jia, Brian Gawalt, Bin Yu, Laurent El Ghaoui, “Summarizing large-scale, multiple-document news data: sparse methods & human validation,” UC Berkeley Dept. of Statistics Technical Report #801, May 2011. [abstract] [pdf]
- Saheli Datta, Brian Gawalt, Guan-Cheng Li, Luke Miratrix, Laurent El-Ghaoui, Bin Yu, Abigail De Kosnick, “Gaining Contextual Insights into Media from Keywords Derived from Machine-Learning Based Analysis,” Crossing Boundaries 2011, Berkeley, CA March 2011. [abstract]
- Brian Gawalt and Youwei Zhang and Laurent El Ghaoui, “Sparse PCA for Text Corpus Summarization and Exploration,” NIPS 2010 Workshop on Low-Rank Matrix Approximation, Whistler, BC, Dec. 2010. [pdf]
- Brian Gawalt and Jinzhu Jia and Luke Miratrix and Laurent El Ghaoui and Bin Yu and Sophie Clavier, “Discovering Word Associations in News Media via Feature Selection and Sparse Classification,” Proc. ACM International Conference on Multimedia Information Retrieval (MIR2010), Philadelphia, PA, Mar. 2010. [website] [Portal.ACM]
Personal Projects
Just some stuff I threw together in my spare time:- Mandelbrot Oscillations: A one-minute video demonstrating the recursively-calculated magnitudes of the iterations of the Mandelbrot set's complex quadratic polynomial, as a function of different values of c. (Jun. 2011)
- BART Fares and the Triangle Inequality: Finding routes on BART where it's actually more expensive to take a single, direct train than to take the train part way, leave the system, re-enter, and finish the route on a second train. (Jun. 2011)
- Get Drunk But Neither Broke Nor Fat: Considering calorie count and costs of alcoholic beverages. (Sep. 2010)
- Synthetic Shakespeare: I trained a Markov model on the digram transitions of the works of Shakespeare, and now I can sample new Shakespeare-sounding verses. (July 2010)
- 69 Love Songs, Illustrated: “Roses”: My contribution to the joint effort to illustrate all the songs from the Magnetic Fields' triple album. You can check out the video version at http://www.youtube.com/watch?v=jihng-wf-cw. (June 2010)
- RISK STATS: An almanac of the probable outcomes of battles in the game Risk. (Feb. 2010)
- The New York Times Columnist Comparator: A list of a few distinguishing keywords from the regular columnists of the New York Times Op/Ed section. (Updated daily from Oct. 2008 to Aug. 2009; no longer updating at present.)
- The BoingBoing Filter: A list of a few distinguishing keywords from the major contributers to BoingBoing. (Updated daily from Oct. 2008 to Apr. 2009; no longer updating at present.)
Graduate Student Instruction
A quick run-down of my TA gigs:- Fall 2005: CS150, Components of Digital Design (Prof. R. Katz)
- Spring 2006: CS150, Components of Digital Design (Prof. K. Pister)
- Fall 2006: EE100, Electronic Techniques for Engineers (Prof. B. Boser)
- Spring 2007: EE120, Signals and Systems (B. Ayazifar)
- Summer 2007: EE40, Introduction to Microelectronic Circuits (full-blown instructor!)
- Fall 2007: EE20, Structure and Interpretation of Signals and Systems (B. Ayazifar)
- Spring 2008: EE120, Signals and Systems (Prof. L. El Ghaoui)
Course Work
- Fall 2005: EE 221a, Linear System Theory (Prof. S. Sastry)
- Fall 2005: EE 226a, Random Processes (Prof. J. Walrand)
- Spring 2006: EE 225a, Digital Signal Processing (Prof. M. Gastpar)
- Spring 2006: PHYS 137a, Quantum Mechanics (Prof. J. E. Moore)
- Fall 2006: EE 227a, Introduction to Convex Optimization (Prof. L. El Ghaoui)
- Fall 2006: CS 294-10, Practical Machine Learning (Prof. M. Jordan)
- Spring 2007: EE 223, Stocastic Control Theory (Prof. V. Anantharam)
- Spring 2007: CS C281a, Statistical Learning Theory (Prof. P. Bartlett)
- Fall 2008: MBA 290g, International Trade and Competition in High Technology (Prof. C. Wu)
- Fall 2008: IS 257, Database Management (Prof. R. Larson)
- Spring 2009: CS 294-10, Bayesian Inference (Prof. M. Jordan)
- Spring 2009: MBA 295C, Opportunity Recognition (Prof. A. Issacs)