The Statistical Science Department encourages all to attend the defense of this dissertation. read more about Problems in Computational Advertising »
If you're applying for a Ph.D. program in Statistical Science, come have your application review by StatSci faculty and current Ph.D. students. Rain location: Old Chem 100 Lobby read more about Drop-in Ph.D. Application Workshop »
We will review physics-informed neural network and summarize available extensions for applications in computational mechanics and beyond. We will also introduce new NNs that learn functionals and… read more about Approximating functions, functionals and operators with neural networks for diverse applications »
Machine Learning Interviews read more about Machine Learning Interviews »
A central aim community ecology is to understand the processes that determine the assembly and dynamics of species assemblages at different spatiotemporal scales. To facilitate the integration… read more about Joint species distribution modelling: how to make more out of community data? »
Inference after model selection is currently a very active area of research. The polyhedral method (Lee et al., 2016) allows for valid inference after model selection if the model selection event can… read more about On the length of confidence intervals with conditional coverage »
Gong Jessie, UT Austin Bo Liu, Duke Morris Greenberg, U Toronto Gauri Kamat Christine Shen, Duke read more about Ph.D. Career Panel »
Ph.D. Career Panel Discussion for MSS students read more about Ph.D. Career Panel Discussion »
In this session, we will work on a data visualization makeover exercise. We will start with a plot that would benefit from a thorough makeover and update it, step-by-step, using the ggplot2 package… read more about +DS vLE: Break it, fix it, trash it, change it, plot, update it »
With increasing attention being paid to the relevance of studies for real-world practice (such as in education, international development, and comparative effectiveness research), there is also… read more about Methods for combining experimental and population data to estimate population average treatment effects »
The Human-Environmental Exchange in the Landscapes of Medieval Ireland [HELM] Project has concluded phase one of study, which successfully identified three medieval nucleated rural settlements from… read more about Data Dialogue: Using spatial data to recreate medieval and postmedieval settlement and landscapes in Ireland: preliminary results from the Human-Environmental Exchange in the Landscapes of Medieval Ireland [HELM] Project »
Communicating Effectively in a Professional SettingLed by Farnoosh Brock, Trainer & CoachStudents will explore their workplace identities and perceived pressures, as well as learning… read more about Communicating Effectively in a Professional Setting »
Registration link below - virtual eventPlease join 2nd Order Solutions (2OS) to learn about our Data Scientist and Business Analyst full-time and internship opportunities! 2OS is a consulting firm… read more about 2nd Order Solutions (2OS) Information Session »
Gaussian processes (GPs) are frequently used in machine learning and statistics to construct powerful models. However, when employing GPs in practice, important considerations must be made regarding… read more about On MCMC for variationally sparse Gaussian processes: A pseudo-marginal approach »
As a Manager of a newly formed Data Science team, Jonathan Weininger will share his experience building a Data Science team. This will include what it has been like to host 25+ interviews of data… read more about Home Depot Information Session »
Second-year Statistical Science Master's Students will give lightning talks about their summer internship experiences.Emre Yurtbay, Internship at FacebookLingyu Zhou, Internship at Voya Financial… read more about Internship Lightning Talks »
In this session, we will work on a data visualization makeover exercise. We will start with a plot that would benefit from a thorough makeover and update it, step-by-step, using the ggplot2 package… read more about +DS vLE: Break it, fix it, trash it, change it, plot, update it »
Stochastic epidemic models such as the Susceptible-Infectious-Removed (SIR) model are widely used to model the spread of disease at the population level, but fitting these models to data present… read more about Likelihood-based Inference for Stochastic Epidemic Models via Data Augmentation »
Lora B. Poepping, President, Plum Coaching & Consulting read more about Learn to Love LinkedIn »
Standard Bayesian inference is known to be sensitive to model misspecification, leading to unreliable uncertainty quantification and poor predictive performance. However, finding generally applicable… read more about Robust Inference and Model Selection using Bagged Posteriors »
2nd Order Solutions is a consulting firm that specializes in applying cutting edge analytics to the world of consumer lending. We build custom machine learning models and develop credit strategies… read more about Data Dialogue: 2nd Order Solutions »
Dr. Heidi Scott Giusto, Career Coach, Career Path Writing Solutions read more about Writing Effective Resumes Workshop »
Reinforcement learning (RL), which is frequently modeled as sequential learning and decision making in the face of uncertainty, is garnering growing interest in recent years due to its remarkable… read more about Breaking the Sample Size Barrier in Reinforcement Learning »
The US public has a constitutional right to access criminal trial proceedings. In practice, it is difficult to exercise this right as well as to quantitatively study federal sentencing disparities.… read more about Data Dialogue: Analyzing Racial Equity and Bias of Federal Judges through Inferred Sentencing Records »
Speakers:Eden Huang, Data Scientist and Daniel McCarthy, Senior Campus Recruiter read more about Liberty Mutual »