## August 2016

### GRAD STUDENT ORIENTATION

The department will hold an orientation for all incoming MS and PhD students on Monday, August 22, 2016 from 9:30 AM - 1:00 PM Meet us in the lounge area of Hanes Hall, 3rd floor.

Find out more »## September 2016

### STOR Colloquium: Alfredo Garcia, ARO and University of Florida

Alfredo Garcia, Army Research Office (ARO) and University of Florida Iterative Mechanisms for Electricity Markets Abstract: We consider the problem of designing the rules by which dispatch and payment to electricity market participants are gradually adjusted while taking into account network and reliability constraints so as to ensure the market clears with an efficient outcome. Small adjustments (which require minimal information from market participants at each iteration) facilitate the identification of incentives for ensuring truthful reporting of private…

Find out more »### STOR Colloquium: Bin Hu, University of North Carolina at Chapel Hill

Bin Hu University of North Carolina at Chapel Hill, Kenan-Flagler Business School Is Reshoring Better than Offshoring? The Effect of Offshore Supply Dependence In this paper we investigate the effect of offshore supply dependence (OSD) on offshoring-reshoring profit comparisons. We find that OSD hampers a reshoring manufacturer's responsiveness to demand information updates and may significantly affect offshoring-reshoring comparisons, such that reshoring may yield lower profits than offshoring in many cases, including when offshoring has no baseline-cost advantage. We then show…

Find out more »### STOR Graduate Seminar: Steven Wolf and Gina-Marie Pomann

Graduate Seminar Wednesday, September 21st, 2016 120 Hanes Hall 3:30pm Steven Wolf and Gina-Maria Pomann Duke's Biostatistics Core Collaborating in Clinical Research with Duke’s Biostatistics Core The Biostatistics Core at Duke aims to work with an interdisciplinary network of clinical investigators conducting research at Duke by providing expertise in study design, implementation of statistical methodology, and interpretation of results. We actively participate on all aspects of statistical design and analysis, protocol development/grant applications with statistical considerations such as power/sample calculations,…

Find out more »## October 2016

### STOR colloquium: Nelson Antunes, CEMAT/University of Lisbon

Nelson Antunes CEMAT/University of Lisbon and University of Algarve Sampling Internet traffic: estimation of flow distributions In this talk, the focus is on recovering the flow (sequence of packets sharing common attributes) size and duration distributions from sampled Internet traffic using a number of previously introduced packet sampling algorithms. Assuming a basic probabilistic flow model, the distribution of flow durations is expressed in terms of the distributions of flow sizes and flow IATs (interarrival times between packets). The available estimation…

Find out more »### Graduate Student Seminar: Danianne Mizzy

Danianne Mizzy from the Science Library will speak and answer questions about resources and services available to all graduate students. Location: Hanes Hall 125

Find out more »### STOR colloquium: Joe Guinness, North Carolina State University

Joe Guinness North Carolina State University Permutation methods for sharpening Gaussian process approximations Vecchia's approximate likelihood for Gaussian process parameters depends on how the observations are ordered, which can be viewed as a deficiency because the exact likelihood is permutation-invariant. I take the alternative standpoint that the ordering of the observations is an aspect that can be tuned to sharpen the approximations. I show that advantageously chosen orderings of the observations can drastically improve the approximations. In addition to…

Find out more »### STOR colloquium: Dirk Lorenz, Braunschweig Technical University

Dirk Lorenz Braunschweig Technical University Probabilistic Image Models and Extensions of the Perona-Malik Filter The Perona-Malik model has been very successful at restoring images from noisy input. In this paper, we show how the Perona-Malik model can be reinterpreted and extended using the language of Gaussian scale mixtures. Specifically, we show how the expectation-maximization EM algorithm applied to Gaussian scale mixtures leads to the lagged-diffusivity algorithm for computing stationary points of the Perona-Malik diffusion equations. Moreover, we show how mean…

Find out more »### Graduate Seminar – Kai Zhang

Kai Zhang Statistics and Operations Research UNC-Chapel Hill BET on Independence We study the problem of model-free dependence detection. This problem can be difficult even when the marginal distributions are known. We explain this difficulty by showing the impossibility to uniformly consistently distinguish degeneracy from independence with any single test. To make model-free dependence detection a tractable problem, we introduce the concept of binary expansion statistics (BEStat) and propose the binary expansion testing (BET) framework. Through simple mathematics, we convert…

Find out more »### STOR colloquium: Seyed Emadi, University of North Carolina at Chapel Hill

Impact of Delay Announcements in Call Centers: An Empirical Approach We undertake an empirical study of the impact of delay announcements on callers' abandonment behavior and the performance of a call center with two priority classes. A Cox regression analysis reveals that in this call center, callers' abandonment behavior is affected by the announcement messages heard. To account for this, we formulate a structural estimation model of callers' (endogenous) abandonment decisions. In this model, callers are forward-looking utility maximizers…

Find out more »## November 2016

### Probability Seminar: Jay Newby, UNC-CH

Probability Seminar Thursday, November 3, 2016 Hanes 125 4:15 PM Jay Newby University of North Carolina-Chapel Hill An artificial neural network approach to automated particle tracking analysis of 2D and 3D microscopy videos Tracking of microscopic species is one of the most utilized experimental technologies in materials science, biophysics, tissue engineering and nanomedicine. The goal is to draw inferences (e.g., viscous and elastic moduli, mesh spacings, passage times) by statistical analysis of particle traces. This in turn allows for…

Find out more »### STOR colloquium: Ivo Adan, Eindhoven University of Technology

Ivo Adan Technical University of Eindhoven and EURANDOM The Netherlands A rate balance principle We introduce a rate balance principle for general (not necessarily Markovian) stochastic processes, with special attention to birth-death like processes. This principle appears to be useful in deriving well-known, as well as new results for various queueing systems. Refreshments will be served at 3:00pm in the 3rd floor lounge of Hanes Hall

Find out more »### STOR colloquium: CANCELLED

This colloquium has been cancelled. We apologize for any inconvenience. STOR colloquium: Vanja Dukic, University of Colorado-Boulder

Find out more »### STOR colloquium: Stephen Becker, University of Colorado-Boulder

Stephen Becker University of Colorado Boulder Efficient robust PCA algorithms for the GPU We introduce the matrix completion problem and the similar robust PCA (RPCA) problem and discuss their relation to compressed sensing and some of their applications to collaborative filtering, background detection in videos, and neuroscience. We cover some standard algorithms to solve these problems, including proximal gradient descent, Frank-Wolfe/conditional-gradient, and Burer-Monteiro splitting. A natural idea to speed up the algorithms is to run them on the GPU…

Find out more »## December 2016

### Probability Seminar: Dieter Mitsche, Universite de Nice Sophia-Antipolis

“On the spectral gap of random hyperbolic graphs” Random hyperbolic graphs have been suggested as a promising model of social networks. A few of their fundamental parameters have been studied. However, none of them concerns their spectra. We consider the random hyperbolic graph model as formalized by Gugelmann et al. and essentially determine the spectral gap of their normalized Laplacian. Specifically, we establish that with high probability the second smallest eigenvalue of the normalized Laplacian of the giant component…

Find out more »### STOR colloquium: Elaine McVey, TransLoc/Insightus

Title: Commuting, voting, and the off-label use of data Abstract: The modern practice of data science often involves approaching datasets differently than in traditional statistics. Two analyses will be presented, both of which use combinations of public datasets in expected and "off-label" ways. One addresses the need to simulate realistic commuting patterns, and the other evaluates the effects of North Carolina voting site decisions. In the process of telling the stories of these two data science projects, we'll have…

Find out more »## January 2017

### Probability Seminar: Michael Perlmutter, UNC-CH

Michael Perlmutter UNC-Chapel Hill Department of Statistics and Operations Research Martingale Transforms and their Applications to Harmonic Analysis Martingale transform methods are a powerful tool for the study of many operators of classical interest in harmonic analysis such as the Riesz transforms and the Beurling-Ahlfors transform. In particular, these methods allow us to transfer D.L. Burkholder’s sharp constant, p*-1, for the boundedness of martingale transforms to a large class of analytic operators. I will discuss the history of such…

Find out more »### Grad Student Seminar

Siyun Yu Server Allocation at Virtual Computing Labs via Queueing Models and Statistical Forecasting The Virtual Computing Lab (VCL) is a cloud computing service that provides users remote access to software applications. The main challenge is to decide how many servers should be preloaded with which applications, and how many servers should be left flexible, to be loaded with the requested application on demand. If a preloaded server with a desired application is available, the user gets immediate access. If…

Find out more »### STOR Colloquium: Santiago Balseiro, Duke University

Santiago Balseiro Duke University Dynamic Mechanisms with Martingale Utilities We study the dynamic mechanism design problem of a seller who repeatedly sells independent items to a buyer with private values. In this setting, the seller could potentially extract the entire buyer surplus by running efficient auctions and charging an upfront participation fee at the beginning of the horizon. In some markets, such as internet advertising, participation fees are not practical since buyers expect to inspect items before purchasing them. This…

Find out more »## February 2017

### STOR Colloquium: Julie Ivy, North Carolina State University

Julie Ivy North Carolina State University To be Healthy, Wealthy, and Wise: Using Decision Modeling to Personalize Policy in Health, Hunger Relief, and Education Decision making to satisfy the basic human needs of health, food, and education is complex, accomplishing this in such a way that solutions are personalized to the needs of the individual has been the focus of my research. This talk will present an overview of my research in the area of decision making under conditions…

Find out more »### STOR Colloquium: Peter Hoff, Duke University

Peter Hoff Duke University Adaptive FAB confidence intervals with constant coverage Abstract: Confidence intervals for the means of multiple normal populations are often based on a hierarchical normal model. While commonly used interval procedures based on such a model have the nominal coverage rate on average across a population of groups, their actual coverage rate for a given group will be above or below the nominal rate, depending on the value of the group mean. In this talk…

Find out more »### Graduate seminar: Walt DeGrange, CANA Advisors

Walt DeGrange is a Principal Operations Research Analyst for CANA Advisors where he leads operations research analysis across federal and commercial domains. He is also a faculty member at the University of Arkansas in the Operations Management graduate program, a MBA Executive Practicum Advisor at the NC State University Supply Chain Resource Cooperative, a MORS Board of Director and the Chairperson for the INFORMS SpORts Section. His analytics projects include work with the Navy, Marine Corps, St Louis Blues (NHL),…

Find out more »### STOR Colloquium: Gudrun Johnsen, University of Iceland

Gudrun Johnsen University of Iceland Title: If you look close enough you can see a whole lot: Data collection and analysis of the Parliamentary Investigation Commission looking into the Icelandic Banking Collapse in 2008 Abstract: The combined collapse of Iceland's three largest banks is the third largest bankruptcy in history and the largest banking system collapse suffered by any country in modern economic history, relative to GDP. In 2008 the Icelandic Parliament installed a Special Investigation Commission (SIC)…

Find out more »## March 2017

### STOR Colloquium: Mariana Olvera-Cravioto, University of California-Berkeley

Directed complex networks and ranking algorithms In the first part of this talk I will discuss a family of inhomogeneous directed random graphs for modeling complex networks such as the web graph, Twitter, ResearchGate, and other social networks. This class of graphs includes as a special case the classical Erdos-Renyi model, and can be used to replicate almost any type of predetermined degree distributions, in particular, power-law degrees such as those observed in most real-world networks. I will mention during…

Find out more »### STOR Colloquium: Zhiyi Zhang, UNC Charlotte

Zhiyi Zhang University of North Carolina at Charlotte Title: Statistical Implications of Turing’s Formula Abstract: This talk is organized into three parts. Turing’s formula is introduced. Given an iid sample from a countable alphabet under a probability distribution, Turing’s formula (introduced by Good (1953), hence also known as the Good-Turing formula) is a mind-bending non-parametric estimator of total probability associated with letters of the alphabet that are NOT represented in the sample. Many of its statistical properties were…

Find out more »### Hotelling Lectures: Aad van der Vaart, Leiden University

Nonparametric Bayesian methods: frequentist analysis Aad van der Vaart Leiden University We present an overview of Bayesian methods to estimate functions or high-dimensional parameter vectors, and discuss the validity (or not) of these methods from a non-Bayesian point of view. For instance, we consider using a Gaussian process as a prior for a regression function or (after exponentiation and normalisation) for a density function. We characterise the rate at which the corresponding posterior distribution can recover a true function as…

Find out more »### Hotelling Lectures: Aad van der Vaart, Leiden University

Nonparametric Bayesian methods: frequentist analysis Aad van der Vaart Leiden University A more detailed view of Bayesian methods to estimate functions or high-dimensional parameter vectors, and discuss the validity (or not) of these methods from a non-Bayesian point of view. For instance, we consider using a Gaussian process as a prior for a regression function or (after exponentiation and normalisation) for a density function. We characterise the rate at which the corresponding posterior distribution can recover a true function as…

Find out more »## April 2017

### STOR Colloquium: Hongtu Zhu, MD Anderson

Hongtu Zhu University of North Carolina at Chapel Hill, and The University of Texas MD Anderson Cancer Center Title: Statistical Challenges, Opportunities, and Strategies in Large-Scale Medical Studies With the rapid growth of modern technology, many biomedical studies have collected data across different sources (e.g., imaging, genetics, and clinical) in an unprecedented scale. The integration of such ultra high-dimensional data raises many statistical challenges, rendering most existing statistical methods and old data platform no longer suitable and thus underscoring…

Find out more »### Grad Student Seminar: Bryan Davis, Indeed.com

Bryan Gilbert Davis Indeed.com SEM Portfolio Optimization This talk will introduce the basic format and mechanisms of Search Engine Marketing and introduce the business motivations for its utilization. It will then delve into ongoing work at Indeed aimed at optimizing the distribution of budget over different queries, and will highlight the different modeling and engineering components of this work.

Find out more »### CANCELLED STOR Colloquium

Philip Ernst Rice University Title: Yule's "Nonsense Correlation" Solved! Abstract: In this talk, I will discuss how I recently resolved a longstanding open statistical problem. The problem, formulated by the British statistician Udny Yule in 1926, is to mathematically prove Yule's 1926 empirical finding of ``nonsense correlation.” We solve the problem by analytically determining the second moment of the empirical correlation coefficient of two independent Wiener processes. Using tools from Fredholm integral equation theory, we calculate the second…

Find out more »### STOR Colloquium: Ilse Ipsen, North Carolina State University

Ilse Ipsen North Carolina State University Randomized Algorithms for Matrix Computations The emergence of massive data sets, over the past fifteen or so years, has led to the development of Randomized Numerical Linear Algebra. Fast and accurate randomized matrix algorithms are being designed for applications like machine learning, population genomics, astronomy, nuclear engineering, and optimal experimental design. We give a flavour of randomized algorithms for the solution of least squares/regression problems and, if time permits, for the computation of…

Find out more »## May 2017

### GRADUATION CEREMONY

Following the University's Commencement ceremony on May 14th, the Department of Statistics and Operations Research will have a brief ceremony to recognize the graduates from our B.S., M.S., and Ph.D. programs. This ceremony will take place at 1:00 PM in the Genome Science Building, room G100 and will be followed by an informal reception.

Find out more »## August 2017

### STOR/BIOS Boot Camp

Boot camp for incoming graduate students of the Statistics & Operations Research, and Biostatistics departments. 10am-12pm Linear Algebra 1pm-3pm Analysis All sessions meet in Hanes 130

Find out more »### STOR/BIOS Boot Camp

Boot camp for incoming graduate students of the Statistics & Operations Research, and Biostatistics departments. 10am-12pm Linear Algebra 1pm-3pm Analysis All sessions meet in Hanes 130

Find out more »### STOR/BIOS Boot Camp

Boot camp for incoming graduate students of the Statistics & Operations Research, and Biostatistics departments. 10am-12pm Linear Algebra 1pm-3pm Analysis All sessions meet in Hanes 130

Find out more »### STOR/BIOS Boot Camp

### STOR/BIOS Boot Camp

### STOR/BIOS Boot Camp

### STOR/BIOS Boot Camp

### First Day of Classes

Classes begin for the Fall 2017 semester

Find out more »## November 2017

### STOR Colloquium: Danica Ommen, Iowa State University

Title: Different Paradigms of Interpretation for Forensic Value of Evidence Quantification Abstract: Currently, one of the major problems in the forensic science community is the confusion between different statistical paradigms. A quantification of the value of evidence is interpreted differently under each paradigm, and may even be the answer to different questions. It is our opinion that these issues need to be addressed before quantitative forensic analyses are considered a reliable science in the justice system. A related issue is the…

Find out more »## April 2018

### Ph.D. Defense: Dylan Glotzer

Ph.D. Thesis Defense Public Presentation* Tuesday, April 3rd, 2018 324 Hanes Hall 1:00 PM Dylan Glotzer Extreme value analysis, nonlinear random oscillators, and applications to ship motions in irregular seas (under direction of Vladas Pipiras) This talk will focus on primarily statistical approaches to the analysis of two extreme (rare) events of interest in Naval Architecture: a ship motion (e.g. roll) exceeding a large target angle, and the capsizing of a ship, both measured by relevant "metrics." The…

Find out more »### Ph.D. Defense: Eric Friedlander

Ph.D. Thesis Defense Public Presentation Wednesday, April 4th, 2018 Gardner 210 1:00 PM Eric Friedlander Mean-Field Methods in Large Stochastic Networks (Under the direction of Amarjit Budhiraja) Analysis of large-scale communication networks (e.g. ad hoc wireless networks, cloud computing systems, server networks etc.) is of great practical interest. The massive size of such networks frequently makes direct analysis intractable. Asymptotic approximations using fluid and diffusion scaling limits provide useful methods for approaching such problems. In this talk, we study…

Find out more »### Ph.D. Defense: Yifan Cui

Ph.D. Thesis Defense Public Presentation Thursday, April 5th, 2018 103 New West 1:00 PM Yifan Cui Tree-based survival models and precision medicine (Under the direction of Dr. Michael R. Kosorok and Dr. Jan Hannig) Random forests have become one of the most popular machine learning tools in recent years. The main advantage of tree- and forest-based models is their nonparametric nature. My dissertation mainly focuses on a particular type of tree and forest model, in which the outcomes are…

Find out more »### Hotelling Lectures: Steven N. Evans, University of California – Berkeley

Steven N. Evans, Departments of Mathematics and Statistics, University of California at Berkeley Title: Some mathematical insights into aging and mortality Abstract: In 1825 Benjamin Gompertz noted that, to a reasonable approximation, mortality rates after maturity in the British population increased exponentially with age. This unexpected yet simple relationship has since been seen in many multi-cellular organisms. Recently, it has been observed that this exponential increase appears to level off in extreme old age. I will discuss ongoing work…

Find out more »## May 2018

### Ph.D. Defense: Leo Liu

Ph.D. Thesis Defense Public Presentation Thursday, May 10th, 2018 125 Hanes Hall 10:00 AM Leo Yu-Feng Liu Advanced Statistical Learning Techniques for High-Dimensional Imaging Data With the rapid development of neuroimaging techniques, scientists are interested in identifying imaging biomarkers that are related to different subtypes or transitional stages of various cancers, neuropsychiatric diseases, and neurodegenerative diseases. The scalar-on-image models have been proven to demonstrate good performance in such tasks. However, due to their high dimensionality, traditional methods may…

Find out more »## February 2019

## March 2019

### STOR Colloquium: Jonathan M. Lees, UNC-Chapel Hill

Jonathan M. Lees University of North Carolina at Chapel Hill Geophysical Time Series Analysis on Volcanoes: Can we quantify non-linearity? Most geophysical processes are aperiodic noisy, intermittent and transient. This requires specialized methods for time series analysis, that seek patterns in time series that vary in space and time. I present here examples from research on exploding volcanoes that exhibit tremor that appears to be resonant but likely results from nonlinear feedback systems. The physical models for these observations…

Find out more »## October 2019

### Statistics Seminar: Wen Zhou, Colorado State University

Estimation and Inference of a Heteroskedasticity Model with Latent Semiparametric Factors for Panel Data Analysis We consider estimation and inference of a flexible subject-specific heteroskedasticity model for analyzing large scale panel data, which employs latent semiparametric factor structure to simultaneously account for the heteroskedasticity across subjects and contemporaneous correlations. Specifically, the heteroskedasticity across subjects is modeled by the product of unobserved stationary process of factors and subject-specific covariate effect. Serving as the loading, the covariate effect is further modeled…

Find out more »## March 2020

### Ph.D. Defense: Weiwei Li

Ph.D. Thesis Defense Public Presentation Thursday, March 19th, 2020 12:30 PM Location: Virtual www.zoom.us/join Meeting ID: 604 122 248 Password: 244139 Weiwei Li Data Science Methods with Applications to Genetic Sequencing Data science methods is of increasing importance in modern genetic sequencing analysis. In this dissertation, we mainly focus on applying statistical modeling to structural variant detection problem and a new frame work for scalable and provable subspace clustering. In the first project, we discuss the optimal sampling strategy…

Find out more »### Ph.D. Defense: Duyeol Lee

Duyeol Lee Public Presentation via ZOOM Join URL: https://unc.zoom.us/j/955324595 Precision Finance and BERET Ongoing advances in financial theory, from modern portfolio theory to valuation of complex financial derivatives, have heavily relied on statistical methodologies. In particular, portfolio theory has become a basic model that must be considered by a variety of market participants, from large financial institutions to individual investors. Another important statistical topic in financial modeling is measuring the dependency among various risk factors and testing independence among them.…

Find out more »## April 2020

### STAN Undergraduate Advising Webinar

For all STAN majors and minors: Before registration opens on April 6, we would like to welcome you to an online webinar to address all of your registration questions. All of you are encouraged to attend. The more students who join this webinar, the more valuable this event will be for everyone, as we find many students have overlapping questions. This event will be held on April 1 at 6PM and can be accessed using the Zoom link below: Join…

Find out more »## August 2020

## September 2020

### STOR Colloquium: Themis Sapsis, MIT

Output-Weighted Active Sampling for Bayesian Uncertainty Quantification and Prediction of Rare Events Themis Sapsis We introduce a class of acquisition functions for sample selection that leads to faster convergence in applications related to Bayesian uncertainty quantification of rare events. The approach follows the paradigm of active learning, whereby existing samples of a black-box function are utilized to optimize the next most informative sample. The proposed method aims to take advantage of the fact that some input directions of the black-box function…

Find out more »## October 2020

### STOR Colloquium: Patrick Combettes, NCSU

Patrick Louis Combettes North Carolina State University Perspective Functions and Applications In this talk I will discuss mathematical and computational issues pertaining to perspective functions, a powerful concept that permits to extend a convex function to a jointly convex one in terms of an additional scale variable. Applications in inverse problems and statistics will be presented.

Find out more »### STOR Colloquium: Lihua Lei, Stanford

Lihua Lei Stanford University Hierarchical Community Detection for Heterogeneous and Multi-scaled Networks Real-world networks are often hierarchical, heterogeneous, and multi-scaled, while the idealized stochastic block models that are extensively studied in the literature tend to be over-simplified. In a line of work, we propose several top-down recursive partitioning algorithms which start with the entire network and divide the nodes into two communities by certain spectral clustering methods repeatedly, until a stopping rule indicates no further community structures. For these…

Find out more »## November 2020

### STOR Colloquium: Jacob Bien, USC

Jacob Bien University of Southern California Tree-Based Aggregation of Rare Features for Prediction It is common in modern prediction problems for many features to be counts of rarely occurring events. The challenge posed by such "rare features" has received little attention despite its prevalence in diverse areas, ranging from biology (e.g., rare species within a microbiome) to natural language processing (e.g., rare words within an online hotel review). We show, both theoretically and empirically, that not explicitly accounting for…

Find out more »### STOR Colloquium: Mayya Zhilova, Georgia Tech

Mayya Zhilova Georgia Institute of Technology Nonasymptotic Edgeworth-type expansions for growing dimension. In this talk I would like to discuss the problem of establishing higher order accuracy of bootstrapping procedures and (non-)normal approximation in the multivariate or high-dimensional setting. This topic is important for numerous problems in statistical inference and applications concerned with confidence estimation and hypothesis testing, and involving a growing dimension of random data or unknown parameter. In particular, I will focus on higher-order expansions for the…

Find out more »### STOR Colloquium: Kavita Ramanan, Brown University

Kavita Ramanan Brown University Large Deviations of Random Projections of High-dimensional Measures Properties of random projections of high-dimensional probability measures are of interest in a variety of fields, including asymptotic convex geometry, and high-dimensional statistics and data analysis. A particular question of interest is to identify what properties of the high-dimensional measure are captured by its lower-dimensional projections. While fluctuations of these projections have been well studied over the past decade, we describe more recent work on both annealed…

Find out more »## January 2021

### Friday Lunch

Informal lunch for the Fall 2020 graduate student cohort. Get to know each other better! Guests will include various faculty and graduate students from previous cohorts. Check your email for the Zoom link.

Find out more »## February 2021

### Friday Lunch

Informal lunch for the Fall 2020 graduate student cohort. Get to know each other better! Guests will include various faculty and graduate students from previous cohorts. Check your email for the Zoom link.

Find out more »### Friday Lunch

Informal lunch for the Fall 2020 graduate student cohort. Get to know each other better! Guests will include various faculty and graduate students from previous cohorts. Check your email for the Zoom link.

Find out more »