I am in the forefront of the area I call ``physics meets theoretical computer science,'' whose goal is to determine fundamental limits on computer performance imposed by the laws of physics, and to determine the computational complexity of using various physical theories. Most fundamental limits on information flux and information storage density are due to me. I was the first to prove the algorithmicity of quantum mechanics (Coulombic or numerous other possible potentials, N point particles, Schrodinger equation). I also proved the non-algorithmicity of the same N-particle problem in classical mechanics (Newton's laws of motion and gravity); i.e. classical mechanics is actually harder than quantum mechanics! I also showed the non-algorithmicity of the PDEs of hydrodynamics (under certain assumptions, whose violation would also be devastating news).
I am also responsible (with coauthors) for the best (judged by their worst-case complexity bounds) algorithms now available for the traveling salesman problem in Euclidean spaces (either exact, or epsilon-approximate). These methods of course apply to many other geometrical problems; I'm only mentioning the traveling salesman problem since it is particularly well known.
With coauthors, I invented, and extensively tested, new methods, based on subtle uses of Bayesian decision theory and nonobvious algorithms, for playing games such as chess in the presence of imperfect evaluations. These were the first, and so far still the only, occasions, when a non-minimaxing procedure outplayed standard minimaxing methods (i.e. iterative-deepening alpha-beta search variants with good move ordering heuristics) under realistic tournament conditions. In some cases, the advantage was large. For example in the game of "othello", my new player played even with an alpha-beta player employing the same evaluation function, even when the latter was given 95 times more "thinking time" per game. (And the factor "95" seems to be increasing rapidly as both sides are given more thinking time. Both players were of strengths comparable to or greater than the Human world champion.)
I am the author of the largest comparative experimental study of voting systems, and the first such study to show a clear advantage for one voting system - "range voting" - over all competitors so far proposed. ("Impossibility theorems" such as the one which won Ken Arrow the Nobel Prize in economics, had previously been thought to make it impossible for there to be a "best" voting system. For various practical and theoretical reasons, that conclusion was wrong.) Range voting is a very simple procedure: You give a numerical score between 0 and 10 to each candidate, and the candidate with the highest summed score wins the election. Were democracies to adopt range voting instead of the much more flawed "plurality" system, their improvement in function would be enormous (and may be quantitatively estimated from my experimental results).
For more details on these, see my online papers collection www.math.temple.edu/~wds/homepage/works.html. For a longer, albeit somewhat dated, survey of my work, see www.math.temple.edu/~wds/homepage/smith-retrospective.ps.
Fast matrix algorithms. V.Strassen in 1969 found a way to multiply 2x2 matrices in only 7 (not 8) multiplications and hence NxN matrices in order N to the power 2.81 (not 3) operations. I have (1) found 25 new Strassen-like formulas, with record-smallest numbers of multiplications for their matrix sizes (2) used new techniques and ideas to do it, and discovered new empirical properties of these formulas as a side effect, (3) found ways to redo most of the matrix algorithms in Golub and Van Loan's classic book Matrix Computations (e.g. row orthogonalization, pseudo-inverse, generalized eigenproblem, SVD) in ways that are both asymptotically "fast," and also appear in many cases to be practical, and to have comparable numerical accuracy guarantees to the old methods. For more details, see my NSF grant application www.math.temple.edu/~wds/homepage/matgrant.pdf (also as ps).
"Idiot-proof networks." It appears that certain biological networks are remarkably tolerant to changes in their parameters. If you randomly chose the parameters of the electrical components in a radio in 1:1000 ranges, the probability that the radio would still work would be essentially zero. But if you do the same with the 50 chemical parameters of certain networks in Drosophila Melanogaster, the probability remains large that it still works! I have new principles of network design that correspond to and explain this. These principles probably underly the "design" of biochemical and neurological (and other, e.g. software, and electronic) networks. This could provide a new unifying principle in biology (a field sorely in need of such) and a new connection between math/CS and biology. Biologist Jonathan Miller (Baylor College of Medicine) and I plan to investigate to what extent these new principles are valid in nature; we are submitting a grant proposal.
16ons, 32ons, etc. "Numbers" are commonly regarded as a dense infinite set of things one may continuously multiply, divide, add, and subtract, and which include 1 and 0. You have probably heard of the real numbers, the complex numbers, Hamilton's quaternions, and Graves & Cayley's "octonions," which are 1,2,4, and 8-dimensional numbers, respectively. Famous theorems, finalized during the 1950s, had shown that, in fact, these were the only kinds of finite-dimensional numbers, thus apparently "closing the book" on this subject. In an upcoming paper, I will show that actually, the book has additional chapters. If certain weakened continuity and distributivity properties are permitted, there are a new kind of numbers forming a nonlinear 16-dimensional algebra, and containing all the previous kinds of numbers as subalgebras. I call these the "16ons." They are created from the octonions via a new kind of doubling process which may be continued forever to create 32ons, 64ons, etc. At each doubling, however, these things get "worse:" the complex numbers lose the property that the complex conjugate of z is the same as z; the quaternions lose commutativity ab=ba; the octonions lose associativity ab.c=a.bc; the 16ons lose certain one-sided cancellation and distributivity properties such as b.aa=ba.a and (b+c)a=ba+ca; and the 32-ons lose both the generic uniqueness of solutions x to division problems xa=b and the "Trotter limit formula" (underlying quantum mechanics - presumably a 16on-based quantum mechanics could be set up, but that would be impossible in the 32ons). Nevertheless all the 2power-ons retain many desirable properties forever, such as norm-multiplicativity |ab|=|a|.|b| and the other-sided distributivity and cancellation properties.
I hope to return to "physics meets CS" after the present projects are done. I have new approaches to gravitational physics and quantum electrodynamics with probably better computational complexity and rigor properties.