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Companies that fail to curb their carbon output may eventually face the consequences of asset devaluation and stock price depreciation, according to a new study out of the University of Waterloo.

The researchers further determined that the failure of companies within the emission-intensive sector to take carbon reduction actions could start negatively impacting the general stock market in as little as 10 years’ time.

Statistics and Actuarial Science professor and director of the Data Analytics Lab Ali Ghodsi has been named a 2018 Vector Institute Faculty Affiliate.

Uncovering the Mechanisms of General Anesthesia: Where Neuroscience Meets Statistics

General anesthesia is a drug-induced, reversible condition involving unconsciousness, amnesia (loss of memory), analgesia (loss of pain sensation), akinesia (immobility), and hemodynamic stability. I will describe a primary mechanism through which anesthetics create these altered states of arousal. Our studies have allowed us to give a detailed characterization of the neurophysiology of loss and recovery of consciousness, in the case of propofol, and we have demonstrated that the state of general anesthesia can be rapidly reversed by activating specific brain circuits. The success of our research has depended critically on tight coupling of experiments, statistical signal processing and mathematical modeling.

Researchers at the University of Waterloo have found that sentiments in the nursing notes of health care providers are good indicators of whether intensive care unit (ICU) patients will survive.

Hospitals typically use severity of illness scores to predict the 30-day survival of ICU patients. These scores include lab results, vital signs, and physiological and demographic characteristics gathered within 24 hours of admission.

Assessing financial model risk

Model risk has a huge impact on any financial or insurance risk measurement procedure and its quantification is therefore a crucial step. In this talk, we introduce three quantitative measures of model risk when choosing a particular reference model within a given class: the absolute measure of model risk, the relative measure of model risk and the local measure of model risk. Each of the measures has a specific purpose and so allows for flexibility. We illustrate the various notions by studying some relevant examples, so as to emphasize the practicability and tractability of our approach.

Some new phenomena in high-dimensional statistics and optimization

Statistical models in which the ambient dimension is of the same order
or larger than the sample size arise frequently in different areas of
science and engineering. Examples include sparse regression in
genomics; graph selection in social network analysis; and low-rank
matrix estimation in video segmentation. Although high-dimensional
models of this type date back to seminal work of Kolmogorov and

Constrained maximum likelihood estimation for model calibration using summary-level information from external big data sources.

Information from various public and private data sources of extremely large sample

Robust measurement of economic tail risk

We prove that the only tail risk measure that satisfies a set of economic axioms proposed by Schmeidler (1989, Econometrica) and a statistical requirement called elicitability (i.e. there exists an objective function such that a reasonable estimator must be a solution of minimizing the expected objective function) is the median shortfall, which is the median of the tail loss distribution and is also the VaR at a high confidence level.

Monitoring and Improving Surgical Quality

Some statistical issues related to the monitoring of surgical quality will be reviewed in this presentation. The important role of risk-adjustment in healthcare, used to account for variations in the condition of patients, will be described. Some of the methods for monitoring quality over time, including a new one, will be outlined and illustrated with examples.

Alumni

Carbon emissions will start to dictate stock prices

Ali Ghodsi Named a 2018 Vector Faculty Affiliate

David Sprott Distinguished Lecture Speaker: Dr. Emery Brown; Affiliation: Institute for Medical Engineering & Science

Nursing notes can help indicate whether ICU patients will survive

David Sprott Distinguished Lecture by Dr. Pauline Barrieu, London School of Economics and Political Science

David Sprott Distinguished Lecture by Martin Wainwright, University of California, Berkeley

Some new phenomena in high-dimensional statistics and optimization

David Sprott distinguished lecture by Raymond J. Carroll, Texas A&M University

Constrained maximum likelihood estimation for model calibration using summary-level information from external big data sources.

WatRISQ seminar by Steven Kou, National University of Singapore

Robust measurement of economic tail risk

David Sprott distinguished lecture by William Woodall, Virginia Tech

Monitoring and Improving Surgical Quality