Between distance and proximity

My practice is a means of dealing with distance and desire— desire for intimacy and understanding, for clarity in communication, longing to get closer, to see further, to be near the ocean, to touch the horizon, desire for something certain, longing to let it go. The objects and videos I make are metaphors for a relationship between landscape and longing— gestures of reaching, stretching and trying to span a distance, trying to embody the intangible. Longing is often still present even at close proximity. I want the objects and videos I make to instill an urge to touch, to transgress or press against the boundary between beings. Through these gestures I’m thinking of ways to communicate touch across distance— how to feel presence through absence.Studio Ar

Implicitization of surfaces via geometric tropicalization

In this paper we further develop the theory of geometric tropicalization due to Hacking, Keel and Tevelev and we describe tropical methods for implicitization of surfaces. More precisely, we enrich this theory with a combinatorial formula for tropical multiplicities of regular points in arbitrary dimension and we prove a conjecture of Sturmfels and Tevelev regarding sufficient combinatorial conditions to compute tropical varieties via geometric tropicalization. Using these two results, we extend previous work of Sturmfels, Tevelev and Yu for tropical implicitization of generic surfaces, and we provide methods for approaching the non-generic cases.Comment: 20 pages, 6 figures. Mayor reorganization and exposition improved. The results on geometric tropicalization have been extended to any dimension. In particular, Conjecture 2.8 is now Theorem 2.

Empirical Likelihood: Improved Inference within Dynamic Panel Data Models

This paper proposes and analyses an hybrid of Owen's (1988, 1990, 1991) Empirical Likelihood (EL) and bootstrap, EL-bootstrap, as an alternative to the General Method of Moments (GMM) within dynamic panel data models. We concentrate on the finite-sample size properties of their overidentification tests. Our results show that EL-bootstrap may be a good alternative to GMM estimation within this setting. The practical usefulness of our findings is illustrated via application on an AR(1) univariate panel data model with individual effects using the cash-flow series of 174 firms in the United States.