This talk will be a survey on the applications of random matrix theory in neuroscience. We will explain why and how we use random matrices to model networks of neurons in the brain. We are mainly interested in the study of neuronal dynamics, and we will present results that cover two parallel directions taken by the field of theoretical neuroscience. First, we will talk about the critical point of transitioning to chaos in cases of random matrices that aim to be more "biologically plausible". And secondly, we will see how a deterministic and a random matrix (corresponding to learned structure and noise in a neuronal network) can interact in a dynamical system.

Arakelov geometry studies schemes X over ℤ, together with the Hermitian complex geometry of X(ℂ).
Most notably, it has been used to give a proof of Mordell's conjecture (Faltings's Theorem) by Paul Vojta; curves of genus greater than 1 have at most finitely many rational points.
In this talk, we'll introduce some of the ideas behind Arakelov theory, and show how many results in Arakelov theory are analogous—with additional structure—to classic results such as intersection theory and Riemann Roch.

Given a morphism of schemes of characteristic p, we can construct a morphism from the exterior algebra of Kahler differentials to the cohomology of De Rham complex, which is an isomorphism when the original morphism is smooth.

We present some regularity estimates for viscosity solutions to a class of possible degenerate and singular integro-differential equations whose leading operator switches between two different types of fractional elliptic phases, according to the zero set of a modulating coefficient a = a(·, ·). The model case is driven by the following nonlocal double phase operator,

$$\int \frac{|u(x) − u(y)|^{p−2} (u(x) − u(y))} {|x − y|^{n+sp}} dy+ \int a(x, y) \frac{|u(x) − u(y)|^{ q−2} (u(x) − u(y))} {|x − y|^{n+tq}} dy$$

where $q ≥ p$ and $a(·, ·) = 0$. Our results do also apply for inhomogeneous equations, for very general classes of measurable kernels. By simply assuming the boundedness of the modulating coefficient, we are able to prove that the solutions are Hölder continuous, whereas similar sharp results for the classical local case do require a to be Hölder continuous. To our knowledge, this is the first (regularity) result for nonlocal double phase problems.

We will present three problems that we are interested in:

Forecast of volatility both at the instrument and portfolio level by combining a model based approach with data driven research
We will deal with additional complications that arise in case of instruments that are highly correlated and/or with low volumes and open interest.
Test if volatility forecast improves metrics or can be used to derive alpha in our trading book.

Price predication using physical oil grades data
Hypothesis:
Physical markets are most reflective of true fundamentals. Derivative markets can deviate from fundamentals (and hence physical markets) over short term time horizons but eventually converge back. These dislocations would represent potential trading opportunities.
The problem:
Can we use the rich data from the physical market prices to predict price changes in the derivative markets?
Solution would explore lead/lag relationships amongst a dataset of highly correlated features. Also explore feature interdependencies and non-linearities.
The prediction could be in the form of a price target for the derivative (‘fair value’), a simple direction without magnitude, or a probabilistic range of outcomes.

Modelling oil balances by satellite data
The flow of oil around the world from being extracted, refined, transported and consumed, forms a very large dynamic network. At both regular and irregular intervals, we can make noisy measurements of the amount of oil at certain points in the network.
In addition, we have general macro-economic information about the supply and demand of oil in certain regions.
Based on that information, with general information about the connections between nodes in the network i.e. the typical rate of transfer, one can build a general model for how oil flows through the network.
We would like to build a probabilistic model on the network, representing our belief about the amount of oil stored at each of our nodes, which we refer to as balances.
We want to focus on particular parts of the network where our beliefs can be augmented by satellite data, which can be done by focusing on a sub network containing nodes that satellite measurements can be applied to.

The space of complete collineations is an important and beautiful chapter of algebraic geometry, which has its origins in the classical works of Chasles, Schubert and many others, dating back to the 19th century. It provides a 'wonderful compactification' (i.e. smooth with normal crossings boundary) of the space of full-rank maps between two (fixed) vector spaces. More recently, the space of complete collineations has been studied intensively and has been used to derive groundbreaking results in diverse areas of mathematics. One such striking example is L. Lafforgue's compactification of the stack of Drinfeld's shtukas, which he subsequently used to prove the Langlands correspondence for the general linear group. 

In joint work with M. Kapranov, we look at these classical spaces from a modern perspective: a complete collineation is simply a spectral sequence of two-term complexes of vector spaces. We develop a theory involving more full-fledged (simply graded) spectral sequences with arbitrarily many terms. We prove that the set of such spectral sequences has the structure of a smooth projective variety, the 'variety of complete complexes', which provides a desingularization, with normal crossings boundary, of the 'Buchsbaum-Eisenbud variety of complexes', i.e. a 'wonderful compactification' of the union of its maximal strata.
 

A fine compactified Jacobian is a proper open substack of the moduli space of simple sheaves. We will see that fine compactified Jacobians correspond to a certain combinatorial datum, essentially obtained by taking multidegrees of all elements of the compactified Jacobian. This picture generalizes to flat families of curves. We will discuss a classification result in the case when the family is the universal family over the moduli space of curves. This is a joint work with Jesse Kass.

Let A be a Tannakian category. Any exact tensor functor defined on A is either zero, or faithful. In this talk, I want to draw attention to a derived analogue of this statement (in characteristic zero) due to Jack Hall and David Rydh, and discuss some remarkable consequences for certain classification problems in algebraic geometry.