High-throughput methods based on chromosome conformation capture technologies have greatly advanced our understanding of the three-dimensional (3D) organization of genomes and demonstrated that genome architecture strongly influences gene regulation. However, methods to analyze the 3D chromatin spatial organization data are still in their infancy. In this talk, I will first present a wavelet approach for...

We explore the NYSE Trades and Quotes (TAQ) database that contains tick-by-tick transaction information of stocks traded in the New York Stock Exchange and NASDAQ stock markets. Consistent with asymmetric information models of market infrastructure, we analyze the role of trading intensity, as a proxy for latent information, on the value of financial assets. We...

Markov chain Monte Carlo (MCMC) produces a correlated sample for estimating expectations with respect to a target distribution. A fundamental question is when should sampling stop so that we have good estimates of the desired quantities? The key to answering this question lies in assessing the Monte Carlo error through a multivariate Markov chain central...

Here I will discuss some of the projects that the Brain Game Center is working on and areas where there are significant advantages to moving beyond traditional approaches to data analytics. Issues that we are trying to solve are how can one classify people into subgroups based upon a collection of tests? What rehabilitation approaches...

The complement system is a part of innate immunity that rapidly removes invading pathogens and impaired host-cells. Activation of the complement system is balanced under homeostasis by regulators that protect healthy host-cells. Impairment of complement regulators tilts the balance, favoring activation and propagation that leads to inflammatory and autoimmune diseases. To understand the dynamics of...

Adaptive Boosting or AdaBoost, introduced by Freund and Schapire (1996) has been proved to be effective to solve the high-dimensional binary classification or binary prediction problems. Friedman, Hastie, and Tibshirani (2000) show that AdaBoost builds an additive logistic regression model via minimizing the ‘exponential loss’. We show that the exponential loss in AdaBoost is equivalent...

The explosion of Internet of Things and cloud computing applications has generated a huge demand for multi-tenant collocation data centers everywhere, extending the Internet edge beyond the traditional hub locations. As one would expect, securing datacenters against cyber attacks is extremely important, and so is providing a reliable power supply to servers. While the threat...

It is well known that relationships between data points (i.e., context) in structured data can be exploited to obtain better recognition performance. In our recent work, we have explored a different, but related, problem: how can these inter relationships be used to efficiently learn and continuously update a recognition model, with minimal human labeling effort...

Microblogs data, e.g., tweets, reviews, news comments, and social media comments, has gained considerable attention in recent years due to its popularity and rich contents. Nowadays, microblogs applications span a wide spectrum of interests, including analyzing events and users activities and critical applications like discovering health issues and rescue services. Consequently, major research efforts are...

Increases in greenhouse gas concentrations are expected to impact the terrestrial hydrologic cycle through changes in radiative forcings and plant physiological and structural responses. As a result, projections of future changes in water resources become complicated due to the tight coupling between the biosphere and terrestrial hydrologic cycle. In recent years a number of physically...